A Focus on the Look What We Found! Brand

Ambient Food, is there a student market? A focus on the Look What We Found! BrandWILLIAM HANRAHAN 060953199BSc MarketingNewcastle UniversityWednesday, April 22, 2009 Ambient Food, is there a student market? A focus on the Look What We Found! brandDissertation submitted in partial fulfilment for the BSc Marketing HonoursWILLIAM HANRAHAN 060953199BSc MarketingNewcastle UniversityWednesday, April 22, 2009William Hanrahan 5 ConfirmationI confirm that this dissertation is my own work and that all sources are fully references and acknowledged.Word Count: 12,000Signature:…………………………………………………… Date: …………………William Hanrahan 5 AcknowledgementsThe writer would like to thank several individuals for their assistance in completing this dissertation. Mr Karl Christensen, personal dissertation supervisor, for his guidance and support. Mr Eric Ruto and Mr Mitchell Ness for their comments and assistance regarding qualitative data collection. Professor Chris Ritson for his support throughout the last few years at Newcastle University. Finally, all students who participated in the survey, without their help this report would not have been possible.William Hanrahan 5 AbstractAmbient food is defined as ‘food that can be stored at room temperature’. Wet ambient meals form a small sector which can be found alongside ambient snacks in retailers. The products offer a similar level of convenience to other ready meals but most importantly without the need for refrigeration.Sales of ready meals are driven largely by consumer demand for convenience food. The advantage of ambient meals is that they can be microwaved in a few minutes and their storage is simplified. The demand for convenience food derives from a number of well established lifestyle trends which have left consumers feeling short on time and energy.The modern day consumer spends less time preparing and consuming meals and this has led to the rise of ‘fast food’ and convenience food market. Marketers are aware that student consumers do not evaluate all products in the same way.Even brands that are perceived to be very similar are often selectively purchased; this dissertation examines the factors that influence the purchasing decisions of convenience food made by Newcastle University students responsible for providing meals themselves.A review of relevant literature was conducted which suggested a questionnaire followed by cluster analysis was required to find out what students expected in convenience food and if student segments emerged that could be seen as potential niche market consumers. These methods were utilised to add depth to the empirical setting and context of the study.The report discusses findings from an online self-administered questionnaire concerning student’s attitudes towards food and convenience food shopping. The results showed that distinct student segments exist within the sample. These segments were different mainly through gender and what could be considered socio - cultural differences. These were mostWilliam Hanrahan 5 prominent in the students’ attitudes towards cooking time, weekly spend and attitudes towards the meals and soups sold by The Tanfield Food Group. After identifying the most effective ways to measure student consumers from past research, questionnaires were identified to be a useful tool and after extensive cluster analysis on the data the results showed the emergence of 4 similarly sized student cluster groups, these 4 clusters were profiled and the researcher offers his advice based on these cluster groups, it appears that student segments do exist for high end ambient foods and marketing implications follow in the discussion and executive report.Appendix ListAppendix 1: Literature Summary *Appendix 2: SPSS OutputAppendix 3: SPSS Cluster OutputAppendix 4: Survey Monkey SummaryAppendix 5: Executive Summary for the Tanfield Food Group Appendix 6: Social Networking GroupAppendix 7: Response from The Tanfield Food Group *List of TablesTable 1.3: Research ObjectivesTable 3.1: Theoretical Subject JustificationTable 3.4: Dimensions of Authentic British Food ProductsWilliam Hanrahan 5 * Not present in the electronic copyContentsAcknowledgements...... 4 Abstract...... 5 Appendix List...... 6 List of Tables...... 61.0 Introduction...... 91.1 Reasons for Study...... 9 1.1.1 Hypothesis...... 1 0 1.2 Aims and Objectives...... 11 1.2.1 Aims...... 1 1 1.2.2 Objectives...... 1 1 1.3 Research Design...... 12 1.4 Structure...... 1 32.0 Market Review...... 152.1 Challenges within the Market...... 15 2.2 Generic Strategies Matrix...... 17 2.3 Competitive Advantage...... 19 2.3.1 Differentiation Focus...... 19 2.3.2 Manufacturing Strategy...... 19 2.3.3 Value Chain...... 20 2.4 Learning Curve...... 24William Hanrahan 5 2.5 PEST Analysis...... 25 2.6 Summary...... 2 73.0 Theoretical Background...... 283.1 Introduction...... 2 8 3.2 Shopper Behaviour...... 30 3.3 Student Consumers...... 33 3.4 British and Regional Food...... 38 3.5 New Product Marketing...... 42 3.6 Cluster Analysis...... 444.0 Methodology...... 5 14.1 Introduction...... 5 1 4.2 Use of Secondary Data...... 51 4.3 Qualitative Research Methods...... 52 4.4 Quantitative Research Methods...... 52 4.4.1 Questionnaire Design...... 52 4.4.2 Data Collection...... 55 4.5 Cluster Analysis...... 56 4.5.1 Clustering Techniques...... 56 4.5.2 Optimisation Techniques...... 57 4.5.3 Applications of Cluster Analysis...... 57 4.5.4 Problems with Cluster Analysis...... 58William Hanrahan 5 4.5.5 Summary...... 5 8 4.6 Data Analysis...... 59 4.6.1 Questionnaire Response...... 60 4.6.2 Segmentation of Sample...... 60 4.6.3 Sample Size...... 605.0 Results...... 615.1 Descriptive Analysis...... 62 5.2 Cluster Analysis...... 84 5.2.1 Crosstabs Analysis...... 84 5.2.2 Crosstabs Testing Summary...... 94 5.2.3 Final cluster centres...... 95 5.2.4 Cluster responses Summary...... 96 5.2.5 Cluster Profiles...... 102 5.3 Cluster Summary and recommendations...... 1036.0 Discussion...... 10 66.1 Introduction...... 10 6 6.2 Summary of Key Results...... 106 6.3 Fulfilment of Objectives...... 1087.0 Conclusion...... 11 07.1 Limitations of the study...... 110William Hanrahan 5 7.2 Suggestions for Future Research...... 110 7.2.1 Improving Response Rate...... 110 7.2.2 Additional Questions...... 110 7.2.3 Multi-Dimensional Scaling...... 111 7.2.4 Focus Groups...... 111 7.3 Hypothesis...... 11 28.0 Study References...... 1139.0 Appendices...... 11 8SPSS Output SPSS Cluster Output Survey Monkey Summary Executive Summary for Tanfield Food Social Networking Group1.0 IntroductionThis chapter provides an overview of the rationale for the study as well as its aims and objectives. It gives a synopsis of the research design and outlines the structure of the dissertation.1.1 Reasons for studyIn 2006, Karl Christensen gave an interesting lecture about The Tanfield Food Group and in particular the Look What We Found! brand, this started my initial interest in the company and prompted me to begin trying various products within the range, all of which I was very impressed with. Two years later in another lecture Sharon Kuznesof asked the students,‘Who has heard of Look What We Found products?’ Only one person raised their hand, IWilliam Hanrahan 5 thought: ‘Surely far more students would be interested in this type of quality convenience food?’ and here an idea was born. The main reason for this study is to find out if students are a missed opportunity for ambient food producers such as The Tanfield Food Group and if possible, attempt to cluster the student market with preferred meal types of the ‘ideal’ student clusters.It made sense to conduct research about the group which is easily accessible, making it easier to get respondents, focus group members and obtain students opinions throughout the research. The researchers’ particular passion is food with an intention of working within the food sector after graduation, so it seemed the obvious choice. The research methods and analytical technique modules studied in stages 2 and 3 of the BSc Marketing programme were of particular interest, and it was decided to involve these where possible.The study was aimed at trying to segment the student group to find a potential market for this type of high quality convenience food.After an extensive search of literature relating to this topic, articles were found which could assist this research, and a gap was found in not only segmenting students by their shopping preferences but including more detailed questions and including the range of meals offered by The Tanfield Food Group through the Look What We Found! brand.1.1.1 HypothesisIt is expected that the research will identify various segments of student food consumers, from the researchers experience and having the benefit of belonging to the student group in which is being studied, he expects to find a handful of student segments, some which can be proposed and recommended to The Tanfield Food Group as being potential targetsWilliam Hanrahan 5 for ambient foods, while identifying some students group that would be unlikely customers for high quality ambient food products. It is hoped that these clusters can be formed, and that through the creation of an in-depth questionnaire these clusters can even be determined by their preferred meal choice. It is hoped that at least one cluster can be identified for recommendation to The Tanfield Food Group that is appropriately sized and suggests there is potential for marketing towards students.1.2 Aims and Objectives1.2.1 Aims1. This research project aims to investigate the most important factors influencingNewcastle University students’ purchasing decisions regarding convenience food, in particular ambient foods, identifying the different consumer segments which exist for their products. 2. Make marketing recommendations based on the findings of this report.1.2.2 ObjectivesThe objectives of the study are listed below: Provide a market overview for the Convenience Meal and Soup Market in the UK, to establish the reasoning behind the increasing consumption of convenience food andWilliam Hanrahan 5 in particular ambient foods, giving strategic marketing implications based on the findings. Give a detailed analysis of the vital factors of the key literature considered to be most important in shopping behaviour, student consumers, British/regional food and new product marketing and suggested analytical methods. Based on literature recommendations, conduct a questionnaire to obtain student responses, segment the sample into groups which share common characteristics, based on attitudes towards food and consumption of convenience food. Provide recommendations for The Tanfield Food Group which can improve the effectiveness of marketing to students. Identify the key segments that exist for the products and recommend marketing strategies to improve consumption.1.3 Research DesignQualitative: Using in-depth interviews to gain background information and understanding and also to facilitate questionnaire design. Quantitative: Survey of student attitudes towards convenience food shopping and preferred food attributes, descriptive and cluster analysis.Table 1.3 Objective Methodology Provide a market overview for the Convenience Meal and Soup Market in the UK, to establish the reasoning behind the increasing consumption of convenience food and in particular ambient foods, giving strategic marketing implications based on the findings. SecondaryWilliam Hanrahan 5 Give a detailed analysis of the vital factors of the key literature considered to be most important in shopping behaviour, student consumers, British/regional food and new product marketing. Secondary Conduct a questionnaire to obtain student responses, segment the sample into groups which share common characteristics, based on attitudes towards food and consumption of convenience food. Survey Provide Implications for Tanfield Food on how to market to students more effectively. Identify the key segments that exist for the products and recommend marketing strategies to improve consumption Both1.4 StructureThe report is structured into five main chapters, each of which serves to develop the understanding of the factors affecting the consumption of ambient foods.The following chapter, ‘Market Review’ consists of secondary research, which was the initial exploration of convenience foods, in particular the Look What We Found! brand and its position as a new ambient food concept within the market. This chapter is key for the justification of the study, in order to appeal to new markets, but also informs the reader of its exact position within the convenience meals and soup market.The subsequent chapter ‘The Literature Review’ consists of secondary research, the main subjects are split into five topics. Such research also served to supplement existingWilliam Hanrahan 5 knowledge concerning measuring student’s attitudes and this additional knowledge aided the design phase of the project. The research identified key factors which helped formulate the survey.Chapter 4 ‘Methodology’ provides a detailed explanation of and justification for the methodology and data analysis techniques employed in the context of the original research objectives. The chapter also emphasises the limitations of the methodology used, with particular reference to sample size and survey method.Chapter 5 ‘Results’ presents the results of the factor and cluster analysis of the survey data collected, whilst interpreting the significance of the findings, and the marketing implications of these findings; these are of use mainly to the ambient food producer, TheTanfield Food Group, in particular its Look What We Found! brand. But the results are of use to supermarkets, smaller convenience stores and other ambient food producers in determining the market potential of the produce.The final chapters 6 & 7 ‘Discussion and Conclusions’ provide a summary of the most important findings of the research, whilst evaluating the market potential of the products.The content of these chapters is directly related to evaluating the fulfilment of the original objectives.William Hanrahan 5 2.0 Market Review2.1 Challenges within the MarketThe main problem that The Tanfield Food Group face is changing the image of ambient food. Many consumers have a negative predisposition when it comes to purchasing this type of meal, not traditionally renowned for freshness or nutritional quality.The challenge they face is that although consumers are as busy as ever, they are more conscious about healthy eating and quality. Ready meals have been criticised over the fat, salt and additive content, and this has stalled a long period of strong and sustained growth.Increased TV and press coverage has sparked an interest from consumers with cooking andWilliam Hanrahan 5 the provenance of ingredients, championed by celebrity chefs such as Jamie Oliver andHugh Fearnley-Whittingstall.Tanfield Food Group have recently increased promotion of their products through TV campaigns and using direct marketing through emails to target niche consumers in what has usually been seen as an under promoted market. Moving away from typical perceptions of ambient foods to become associated with high end food products but with all the advantages of the positive characteristics of ambient foods. It seems they want to position themselves as a hybrid of ultra-convenience with slow cooked luxury.Importantly, ambient convenience food has not previously been seen as gourmet food, however The Tanfield Food Group use the finest natural ingredients from small artisan producers, developing a product with superior ingredients which they hope will appeal to consumers with an interest in food culture.The Tanfield Food Group are embracing the strengths of the ready meal market, creating a product that is consistent with modern lifestyles. They are offering more choices at a higher quality with a reduced salt and fat content, whilst attempting to distance themselves from current products in the market. This section will critically evaluate the strategic direction that The Tanfield Food Group seem to taking with its Look What We Found! brand within the ambient food market. It will examine factors that have influenced the brand and the strategic position that it has adopted. William Hanrahan 5 2.2 Generic Strategies Matrix‘If the primary determinant of a firm’s profitability is the attractiveness of the industry in which it operates, an important secondary determinant is its position within that industry.’Even though the ambient food market has below average profitability, an optimally positioned firm can generate superior returns. ‘A firm positions itself by leveraging its strengths’, Porter argued that a firm’s strengths ultimately fall into one of two headings: cost advantages and differentiation. By applying these strengths in either a broad or narrow scope, three generic strategies result: cost leadership, differentiation and focus.William Hanrahan 5 Figure 1 illustrates Porters generic strategies; this has been followed with a personal interpretation of where the Look What We Found! brand fits within the ambient meal and ambient soup market respectively.(Figure 1)William Hanrahan 5 The Look What We Found! brand appears to represent a similar area within both markets with a differentiation focus strategy. Looking at where other larger companies are placed within the matrix, this seems the correct place to be, however the soup market is becoming saturated with the entry of many similar products, The Tanfield Food Group need to continue their product development to retain a competitive advantage.2.3 Competitive Advantage‘A competitive advantage is an advantage over competitors gained by offering consumers greater value, either by means of lower prices or by providing greater benefits and service that justifies higher prices.’2.3.1 Differentiation Focus StrategyA differentiation strategy calls for the development of a product or service, offering unique attributes that are valued by customers and that they perceive to be better than, or different from the products of the competition. The Tanfield Food Group have added value from the uniqueness of their product offering, allowing them to charge a premium price.Because of unique attributes, if suppliers increase their prices then The Tanfield FoodWilliam Hanrahan 5 Group may be able to pass on the costs to customers who can’t easily substitute their product. The risks associated with a differentiation strategy include imitation by competitors and changes in customer tastes, which as shown on the Matrix for soups, have already, occurred. Through their product offering and marketing attempts, they are trying to strengthen their differentiation strategy by establishing a corporate reputation for quality and innovation. 2.3.2 Manufacturing StrategyA manufacturing strategy creates and adds value by helping a firm to establish and sustain a defensible competitive advantage, which is the unique position an organisation develops vis-à-vis its competitors. The Tanfield Food Group use advanced sous fide cooking techniques to find a comfort zone in the marketplace, this space they have occupied is strong as rivals cannot easily emulate them. This particular process is costly to set up and requires high levels of control and expense, The Tanfield Food Group have pioneered the ambient/niche market, this level of expertise they have gained within the manufacturing process has erected barriers to entry, strengthening their position, demonstrated with orders from companies such as Marks & Spencer to create products on their behalf.2.3.3 Value ChainThe Tanfield Food Group have created an effective value chain as a means of creating competitive advantage, Their goal is to create value that exceeds the cost of providing the product or service; thus generating a profit margin.William Hanrahan 5 (Figure 2) Inbound LogisticsThe Tanfield Food Group have scoured the country to find the best small scale specialist food producers, establishing close relationships ensuring high standards from their loyal and reliable suppliers. Because of their precise production methods, they can accurately calculate correct levels of inventory needed to reduce wastage, assist planning and increase efficiency. Importantly they can offer the mass market something unique, by securing deals with small scale food producers its likely in some cases they will have sole rights therefore protecting the supply chain and ensuring that potential competitors cannot offer the same product. This simply may occur as a result of The Tanfield Food Group choosing suppliers that don’t have the capacity to supply potential competitors, all the while ensuring a totally unique product offering, a farmer’s market style product but with the benefit of an easily accessible supermarket or convenience store.OperationsThe cooking process ensures the food is cleared of any viable bacteria, making the food safe for storage over longer periods. This is important as consumer food knowledge is at an all time high, with the average consumer becoming increasingly aware of preservative, additive, sugar and salt content. Outbound LogisticsThe Tanfield Food Group ensure their products have an extended shelf life, this enables small specialist shops to stock their range without needing to worry about speed of stockWilliam Hanrahan 5 turnover, it’s also great convenience to the consumer, who can keep the product in a cupboard until needed. This product is especially relevant in today’s society as reducing food waste is a major issue, according to the FSA, ‘wasting food costs the average family £420 a year’ and has serious environmental implications.Marketing and SalesA core strategy of The Tanfield Food Group is based on building a brand identity for theLook What We Found brand! Primarily through their brand personification through the use of the individual farmers on the front of the pack, the first person speech as the brand name, ‘Look What We Found!’ it’s a very interesting and innovative idea. The Look what we found! brand has featured heavily in various newspapers and magazines, especially the magazines who have readers considered to be in their target markets.Recently, The Tanfield Food Group began a quirky TV advertising campaign within theNorth East, aimed at increasing exposure to the brand and getting buyers to continue buying the product. At this early stage of the products life cycle, a key focus it’s importantly to attract new customers. It is hoped that this research can indicate, if possible, improved methods to target suitable student groups which can assist in future marketing planning.Service Part of their philosophy is to listen to what customers want, through the website there is an online blog and a newsletter sent through email to inform customers about new products.Market Leader Strategies: ValueWilliam Hanrahan 5 Tanfield Food Group appear to be aiming to take market share away from the chilled and frozen convenience food sector, based on their ability to deliver a particular value proposition within the high end - ambient food market. The Tanfield Food Group provide a value proposition to every potential customer, this is ‘quality without compromise’. The diagram below shows how factors such as Good Idea, Fair Price and EmotionalConsiderations are considered when a consumer values a product. They have attempted to appease these groups with a skilful integration, focussing on delivering one type of value excellently The Tanfield Food Group are offering the best product to their chosen customers, focussing on a single value discipline, where it directs its energy and emphasis.(Figure 3) Market Leader Strategies: CostsAs their placing in the generic strategies matrix suggests, The Tanfield Food Group have benefited from their differentiation strategy with the ability to charge a premium price for their products. They usually cost around £1.60 for soups and around £2.99 for the meals, cheap enough to compete, but priced high enough to make reasonable returns and suggest quality through a sustainable price. Initially prices were set much higher in independent stores but didn’t at such a premium didn’t sell, this demonstrates one of the challengesWilliam Hanrahan 5 that the Tanfield Food Group face in offering such a product, and showing the necessity to strengthen the brand and look to new market segments.2.4 Learning Curve‘For many production processes, LRAC (long-run average costs) decline substantially as cumulative total output increases. This decline is caused by use of better production equipment and procedures, decreasing labour requirements as workers become more proficient in their jobs, etc. Experience of the manufacturing process leads to improved production methods and a fall in LRAC which reflect the effects of the firm’s learning curve.Learning through production experience allows the firm to produce output moreWilliam Hanrahan 5 efficiently, which is at a lower LRAC, at each output level.’ This definition of learning curve advantages can be applied to The Tanfield Food Group; over a short space of time have rapidly increased production along with quality. (Figure 4)2.5 Political, Behavioural, Environmental, Sociological and Technological AspectsPolitical Government spending on encouraging healthy eating, 5 a day campaigns, lower salt. Foods Standard Agency –Consumer attitudes survey Behavioural Changing lifestyles, less time has encouraged quick hassle free meals Consumers seem to care more about quality food and diet than everWilliam Hanrahan 5  Moving away from unhealthy fast food One third of all students are heavy to medium users of fast food restaurants (Kuznesof et al. 2002) heavier users than non students. Students in general are more conscious of diet and health issues compared with non-student peers. There has been an increase in consumers visiting farm shops and markets as they try to re-connect with the source of their food. The Tanfield Food Group have taken this factor on board using personalisation through by identifying farmer’s names and printing photo’s so that consumers feel some connection with the origin of products.Economic Quite costly meals, can this be justified effectively Recession – will this effect sales, people going for cheaper alternatives Students are predominantly from ABC1 social class categories, mostly funded from student loans so have cash available for such purchases. Research suggests (Ness et al. 2002) that only 23% of the 18-24 year old group are motivated by price.Sociological Will people accept ambient foods, currently associated with tinned goods and not high quality products? Will people replace fresh chilled with ambient foods of The Tanfield Food Group? How can perceptions be changed to make people buy instead? Students are at an influential part of their lives and this offers possibilities for The Tanfield Food Group so attract students and keep them as loyal lifelong purchasers.William Hanrahan 5 Technological Advanced retorting technology, maybe the make people more aware of the process, as it seems currently misunderstood by consumers. The pouches can be microwaved, boiled and meals have a long shelf life, useful for the unpredictableness of students’ lives or some of the extreme activities they may participate in. What about rivals offering similar or alternative meals? - Focus on meal types. For the first time, in-container sterilization can be completed in a few minutes to allow the production of fresher, better tasting long shelf life ambient foods. Food quality is comparable with pasteurized foods and with aseptic processed foods over a wide range of products. Process and capital costs are lower than for most other sterilization processes. Other retorting processes are much slower and subject the food to a long exposure to heat, producing discoloration and that over-cooked note found in many canned and bottled foods. Today’s consumers demand more. They are looking for fresher, more nutritious and more natural tasting and looking foods, with better colour, texture and mouth feel. Strong growth in premium categories indicates that consumers seek enhanced quality.William Hanrahan 5 2.6 SummaryThe Tanfield Food Group realised the need for differentiation, price competition is simply not possible when competing against firms like Heinz and Baxter’s. Through differentiation, they have carved out a lucrative position in the market.“Eating habits of the 21st century have evolved to accommodate the growing importance of work and leisure, and the subsequent move away from rigorous housekeeping and domestic routine” Mintel (2008). Chilled and Frozen Ready Meals - UKThe increased proportion of working women, longer working hours and hectic social lives have all contributed to this demand for convenience food, which either eliminates the need to cook entirely, or shortens and simplifies meal preparation. Until recently, the range of ambient ready meals on offer has been focused on young people, with lower expectations. The market for luxury gourmet convenience food has been focused on the chilled sector, leaving a gap in the market for a quality ambient food product. This niche for ‘cash-rich, time-poor’ individuals has been filled with the introduction of the Look What We Found! range. The Tanfield Food Group need to continue expanding their product range, target new markets and create new products, while at the same time ensuring high quality, natural ingredients which should contribute to building a strong brand and create customer loyalty.This market review recommends targeting new markets such as the student market, as it is expected for certain student groups to be willing to purchase such niche products. The next section of the research will assess the related literature.William Hanrahan 53.0 Theoretical Background3.1 IntroductionThe literature review identifies as range of factors which influence consumers purchasing decisions, there are also many significant factors impacting consumer choice, it is therefore critical to gain a comprehensive understanding of these issues in order to form sensible conclusions as to what can be done.Key literature will be reviewed in the topics of shopping behaviour, to better understand how shoppers act, and how in previous work they have been studied. Then specifically students, how previous research has studied this important consumer group, the methods and techniques used in some segmentation studies and the results obtained from these studies. British and regional food literature has been selected to understand more about how it is perceived, what academic research has taken place dealing with this topic, and what insights can be made. As the products offered by The Tanfield Food Group are a new product concept, literature in the topic of new product marketing was consulted to find what recommendations have been made and how new products had been used in literature for assistance with this study. Finally, as initial reading suggested cluster analysis as an analytical technique in order to segment the student market, it makes sense to study some key literature using cluster analysis, therefore some key pieces of cluster analysis literature were considered to fully grasp the concept and find out if it was a suitable method to use for this study.William Hanrahan 5 Table 3.1 Theoretical Subject JustificationSubject Area Justification To gain an understanding of how shoppers have been profiled in the past, how consumers behaviour has been collected regarding choice, Shopper Behaviour and consumers attitudes towards convenience foods. Reviewing literature based on the student food shopper, looking at the research methods used to collect students responses. The current classifications of different student types and analysis of student Student Consumers consumers. Finding out what consumers perceive authentic British and regional food to be, how past literature has dealt with this speciality food and what methods consumers preferences have been measured, in relation British and Regional Food to local foods. Literature from this topic has been used to see how new products are dealt with in literature, how marketing planning is used for new products, hopefully this can be useful for suggesting a marketing plan New Product Marketing for The Tanfield Food Group Literature using Cluster analysis was used to help improve the researchers understanding of the uses and limitations of the method. Looking at how it's been used in past studies to make sure it’s correct Cluster Analysis for this research project.William Hanrahan 5 3.2 Shopper Behaviour Determinants of store brand choice: a behavioural analysis (Baltas, 1997) Profiling the recreational shopper – (Bellenger and Korgaonkar, 1980) Convenience Food: Space and Timing (Warde, 1999)Baltas (1997) compares private label products with own label products, as the TanfieldFood Group’s, Look What We Found! brand is a private label product the articles managerial implications were as follows, ‘In short, it is almost impossible to beat private label’ prices on a regular basis, and therefore competitive advantage for national brands relies on superior quality and highly differentiated images via advertising, product innovation, creative and aesthetically pleasing designs. Sustaining high quality and high levels of marketing expenditures are vital for manufacturers. For example, the empirical study indicates specific consumer characteristics that lead to store brand proneness, for example the association of store loyalty and retailer loyalty programs to own- brand purchasing. Store brands represent an important part of the total market for many grocery categories especially in the UK. Baltas (1997) states that 39% of total grocery sales are of store brands and this suggests that for some categories own brand dominance must be almost total.Today, the advent of store loyalty cards and related schemes helps to reinforce the position of the supermarket in consumers’ minds. Not only do they see television advertising promoting the brand but they have a positive financial incentive to remain customers of the store. Brand owners need to put the emphasis on product development and promotional strategies that sustain and justify the price premium over own branded goods.William Hanrahan 5 Such strategies require not merely good advertising and a regular stream of product developments bur a demonstration of the superiority of the branded product. In some categories where strong brands exist (washing powders, coffee and soft drinks) the brand owners have succeeded in at least slowing down the growth of own-brand purchases. In each case promotional strategies emphasise the uniqueness of the brand and in doing so reinforce the risk associated with a switch to own-label products. Managers promoting brands under threat from own-label products need to pay attention to the motivations of consumers switching to store brands. Finally that assuming the brand is strong enough to resist such attacks may be a big mistake and positive steps are needed to secure the future of many brands.Bellenger and Korgaonkar (1980), point out the importance and nature of recreational shopping of today’s retailer. The recreational shopper is defined in terms of preferences for the use of leisure time in shopping. This shopper type, which accounts for 69% of the sample, has a profile that suggests atmospherics and in store merchandising as most effective strategies. The underlying determination of retail patronage, of why people buy at certain stores, has been a topic of study for many years. The question is important from a retailer’s perspective because its answers provide a basis for building a successful strategy to attract shoppers and generate sales. Understanding and fulfilling shoppers’ requirements are the essence of building retail patronage. The Journal tests a number of hypothesis based on those recreational shoppers are hypothesised to perceive higher value in gathering information than convenience shoppers. As compared with the latter: In terms of shopping behaviour, recreational shoppers ‘engage more in non-planned purchases’ InWilliam Hanrahan 5 terms of informational gathering – recreational shoppers tend to be information seekers; this propensity is reflected in their TV viewing and newspaper and magazine readership.The implications of this journal indicate that recreational shoppers are very important to the retail trade. They represent a significant percentage of the shopping public and a disproportionate number of women. This journal was interesting as it attempted to profile the recreational shopper, a similar target of this research. The findings were considered relevant to this study as obviously respondents will fall into these categories of shopper mentioned. It was interesting to read about initial profiling of shoppers, to see how it had can be done; the use of questionnaires seemed to generate sufficient information to allow the author to generate valuable conclusions.Warde (1999) argues that the emergence of convenience food reflects the re-ordering of the time-space relations of everyday life in contemporary society. It is suggested that the notion of convenience food is highly contested. Britons are ambivalent about serving and eating convenience food. However, many people are constrained to eat what they call convenience food as a provisional response to intransigent problems of scheduling everyday life. A distinction is drawn between modern and hypermodern forms of convenience, the first directed towards labour saving or time comparison, the second to time-shifting. It is maintained that convenience food is a modern search for the reduction of toil. Convenience food is required because people are too often in the wrong place; the impulse to time-shifting arises from the compulsion to plan ever more complex time-space paths in everyday life. The problem of timing supersedes he problem of shortage of time.Some of the more general social implications of such a claim are explored.William Hanrahan 5 3.3 Student Consumers An analysis of the adolescent consumer (Moschis and Churchill Jr, 1979) The student food shopper – (Ness et al., 2002) Innovative Consumers and Market Mavens (Goldsmith et al., 2003)Moschis and Churchill Jr (1979) found that adolescents in higher social classes had significantly greater economic motivations for consumption. Thus marketing communications stressing the economic or functional aspects of the product may be relatively more effective when directed at adolescents in middle social classes than at lower social classes. The combined effects of social class and age on the teenager’s materialistic orientations suggest that message content emphasizing the expressive aspects of consumption may be relatively more appealing to younger, lower-class and older, middle class teenagers. The effectiveness of marketing communications may differ according to the age of the adolescent, the findings also suggest that the importance of product attributes considered in decision making may vary with age, for example younger adolescents had more favourable attitudes toward product attributes such as price than their older counterparts. Consequently, marketers may benefit in isolating by age group the significant product attributes used in young peoples’ consumer decision making processes and adjusting their marketing and promotional mixes accordingly.William Hanrahan 5 A beneficial paper to this research was that from Ness et al (2002), this paper was of great help to learn more about the 18- 24 year old student group, it influenced many of the questions to be used in the questionnaire. Initial reading of this journal early into the research stage helped identify the importance of targeting to student groups and find out even if this focus should be continued. But reading more about student lifestyle characteristics carried the impetus forward. The research identified students as a meaningful segment, with a population of 1.9 million, showing this to be a significant market. Methods to access students included NUS identity cards, which offer the potential for student offers, something to be investigated in the questionnaire but predicted to be a key marketing offer.Cluster analysis was done to identify two student food shopper segments, different in both attitudes and food shopping behaviour, the results of factor analysis identified five dimensions key to importance of store features, an area which will be useful when combined with this studies focus on convenience food product features.Cluster analysis was seen here as a good way to segment consumers, so It was decided from its successful use here that this study would implement a similar method to split students up but this time by convenience food product features.The results of both secondary and primary stages of the study suggest that students represent an interesting body for segmentation and targeting by food marketers and retailers. The secondary research suggests that the kinds of offers that would appeal to students would be based upon special offers and linked promotions.The research suggests it would be feasible for food retailers to devise marketing schemes to cater specifically for students at individual store basis, this study intends to do just that, utilising a questionnaire of Newcastle based students to identify student segments toWilliam Hanrahan 5 identify the most effective student segments ‘innovative student consumers’ who would be willing to try new products such as the Look What We Found! brand and to arrange a set of questions to identify specific meals from The Tanfield Food Group and the best ways to advertise these products. The research used from Mintel (1999). Student lifestyles, proved interesting, revealing how students are more conscious about a healthy diet than non students, but still tend to be medium to heavy users of fast food, partly because of the cost, partly because they can avoid the necessity of cooking. This suggests that students may need a healthier form of fast food, a more nutritious, wholesome meal, and affordable but without the hassle of cooking, which seems to fit The Tanfield Food Groups product offering. An area that should be focused on is a recommendation of developing marketing schemes to address educational as well as commercial motives, for example in the form of special offers and linked promotions for meal suggestions aimed at promoting a good healthy student diet linked to the Look What We Found! range, for example a soup and main meal deal combination with healthy options to accompany this. Students are regarded as a prospective target for current marketing activity and as a potentially lucrative segment with which to form longer term marketing relationships.Commercial marketers have focussed on student lifestyle characteristics and subsequently, on targeting student segments. According to Mintel (1999). Student lifestyles, there are segments within the student group defined and characterised as: Smugly Sheltered – Financed entirely by parents without cash constraints  Trust fund kids- Financed from investments or sponsorship  Strongly self sufficient – self supporting, no parental support  Independent but cushioned – financed from a variety of sources and parental support  Parentally restricted – Parental support but inadequate for social needs.William Hanrahan 5 These student groups were most insightful and it is thought that this will have some influence on how the questionnaire is carried out, however as this information is already available, detailed financial information such as where students are funded from will not be included, more importantly to this study is the actual levels of spending on food, as this is more focused than a general view of students.The focus of student food shoppers is to be applied to The Tanfield Food Group, studying student attitudes with a specific goal of identifying certain types of consumers, as the student food shopper journal did, however with a clearer focus to link ambient foods, and even the range of meals offered.Consumer researchers describe two types of student consumer, ‘the consumer innovator’ and the ‘market maven’, Goldsmith et al., (2003) looked into the relationship between these two groups and measured attributes such as opinion leadership, price sensitivity, and self-reports of time and money spent shopping.The questionnaire analysis identified that not enough students were aware of ambient food brands such as Seeds of Change or Look What We Found!, it seems that by looking at what makes an innovative consumer or market maven it may help these retailers seeking to maximize sales and profit by appealing to these more favourable customer types. These buyers spend the most, require the least marketing effort, and spread positive word of mouth.Consumer Innovators are buyers who wish to learn about and own the newest products, they are knowledgeable and somewhat price insensitive. Importantly they influence later buyers by serving as models to be imitated and as opinion leaders, as ambient food in thisWilliam Hanrahan 5 way is considered to be new and different, the consumer innovator has traits which include openness to experience, which suggests likelihood to try new things.Market Mavens have information about many kinds of products and places to shop. They seek shopping information from many other sources, and influence other consumers. They are quite knowledgeable about shopping and are eager to share their expertise and opinions with other consumers.This article concluded that retail management should make an effort to create long term relationships with innovative shoppers and tailor strategies to their unique characteristics and concerns. They are knowledgeable about shopping and are interested in it. They can be attracted by interesting information and will spread the word to other, less involved customers. Providing product relevant information through personal contact, websites or direct mail may also help win their loyalty. Promotional efforts that feature something‘new’ would be interesting both to market mavens and consumer innovators. Both types of consumers are important to the retail success of new products, and this includes ambient food products such those offered by The Tanfield Food Group.William Hanrahan 5 3.4 British and Regional Food Authentic British Food products: a review of consumer perceptions (Groves, 2001) Regional foods: a consumer perspective (Kuznesof et al,. 1999) Measuring Convenience: Scots’ perceptions of local food and retail provision (Fitch, 2004)Groves (2001) suggests what consumers perceive to be authentic British food products and this has enabled some suggestions for The Tanfield Food Group to consider. British food is constantly evolving in order to fulfil the demands of each generation. Thus the concept of an authentic British food product is becoming increasingly unclear. This paper therefore addresses what today British consumers actually perceive to be authentic British foods.The data gathered from the focus groups revealed that British perceptions of authenticity relate to both artisans as well as mass produced branded products. Interestingly, dimensions were identified that affect consumer perceptions of authentic British food, theTanfield Food Group could make use of these dimensions in the future when trying to decide new authentic British meal types.William Hanrahan 5 Table 3.4: Dimensions of authentic British Food Products Dimensions of authentic British food products Definition of dimension Originally grown, reared or manufactured in 1. Uniqueness to Britain Britain The presence of traditional association 2. Cultural and/or traditional association between Britain and the product. 3. Characteristics of the production process A natural, or the original production process The assurance of authenticity from a trusted 4. The presence of an authority body Dependent on individual's own criteria for 5. Desired extrinsic attributes specific extrinsic attributesPractical consequences of a product being deemed an authentic British product were identified in this study, authentic food products were thought to be more expensive.Consumers expected and were more willing to pay higher prices for authenticity – due to the price premium and the luxury position; these products may only achieve the status as an occasional purchase rather than featuring in a consumers regular household food shopping. Consumers also had higher expectations of both the overall quality and taste of an authentic British food product, therefore it’s necessary for producers of authentic foods to develop and maintain superior standards of overall quality as consumers are less likely to tolerate products of a lower quality, particularly is the financial outlay was high, prohibiting, against repeat performance. Consumers appear to value the authenticity of foods as it represents a transparent method of production that can be trusted and also a higher quality end product. Thus, by forming perception based on the characteristics of the product and purchase situation, consumers are able to make judgements of a product’s authenticity.William Hanrahan 5 Kuznesof et al (1999) looked at regional foods, and interestingly found how different age groups had alternative visions of regional food as associations of regional food with an older generation were corroborated by the younger discussants who frequently referred to them as the sort of foods eaten at their parental home: “when we mention regional inBritain we have always mentioned family occasions, Sunday lunch and Christmas dinner”;“regional food is more of a home-cooked thing”. In addition, younger generations were generally believed to be spending less time preparing and cooking foods (these activities were considered time-consuming activities with regard to regional food) and lacked the basic cookery skills. “As long as schools teach technology instead of cookery, I think regional dishes will die out because people are not learning to cook anymore”. Many of the discussant descriptions of regional foods corroborate extant studies in related areas. An important aspect of regional foods is that of consumer perceptions of product authenticity, a number of interconnected factors are known to affect perceived authenticity including those relating to the individual, the product, the purchasing and consumption environments. This has specific implications for the delivery of authenticity as perceived by the consumer, especially in terms of the product concept, its method of distribution and also through the communication of aspects of “regionality”. This is particularly important as policy-driven definitions of classifications of authentically regional products may vary from those arrived at by consumers. Amongst the sample of consumers, there was an identifiable “generation gap”, particularly with respect to the production, purchase and consumption of regional dishes, which is closely associated with the older generation and their knowledge and cookery skills. The variation in perceptions between the older and younger participants indicates the potential for market segmentation of regional food products and recipes to address the different consumer needs. The fact thatWilliam Hanrahan 5 consumers perceive differences in regional foods is a powerful message for potential product differentiation on aspects of “regionality”. Such a unique selling point, assuming organizations can position their products as “authentic”, may give businesses a competitive advantage. However, the positive research messages appear to be mainly for the low- volume, high-value, and specialist food retailer. This is especially the case where authenticity can be communicated by the place of origin, the place of purchase, product attributes such as packaging, appearance and ingredients, and can be targeted particularly to those consumers with a personal interest in and knowledge of foods.This exploratory study has raised a number of areas for further investigation, of which two are highlighted. Firstly, many factors are known to contribute to an individual’s understanding of regional food. These factors need to be explored further with a view to uncovering their relative importance in purchasing behaviour. Secondly, perceived authenticity appears to be related to consumer acceptance of the “Regionality” of a food, and also to perceptions of quality. Here the issue of “traceability” as a potential factor affecting perceived quality and authenticity of regional foods presents itself as a valuable area for further investigation.Key to the Look What We Found! brand concept is the portability from one regional food concept to the next, thus providing a limitless product portfolio. Literature was studied to give a basic understanding of what makes regional food regional in the eyes of the consumer. As a result of this portability it was decided to include a question in the surveyWilliam Hanrahan 5 asking for students favourite cuisine type, for example this could lead to an ‘Italian’ LookWhat We Found range. 3.5 New Product Marketing Awareness, use and effectiveness of models and methods for new product development (Nijssen and Lieshout, 1995) Strategic Marketing Planning for Radically New Products (Cooper, 2000) Time, food shopping and food preparation: some attitudinal linkages (Davies and Madran, 1997)Nijssen and Lieshouts (1995) deal with the methods offered to improve a company’s performance of new product development; these methods include brainstorming, focus groups, in home use test, limited roll out. Four popular questions of new product development include:1. Which product should be designed?2. How must the product be designed?William Hanrahan 5 3. How should the product be introduced on the market?4. What is the anticipated success rate of the new product?Cooper (2000) outlines an approach to marketing planning for radically new products, disruptive or discontinuous innovations that change the dimensionality of the consumer decision. With a radically new product, Cooper (2000) suggested that the planning process should begin with an extensive situational analysis. The situational analysis pays particular attention to political, behavioural, economic, sociological, and technological sources, this lead to a detailed pest analysis being created in the initial market review for The TanfieldFood Group. When deciding to use cluster analysis, Davies and Madran (1997) showed good examples of its use regarding the segmentation of consumers by shopping attitudes, although this, like most research into the topic focuses on attitudes to time. The methodology of this research was useful, and identified two groups of consumer. One group clearly saw mealtimes as significant activities and found cooking enjoyable, and even with time pressures they would still commit time to cooking nice meals, showing a substantial group in society still see food shopping and meal preparation as important activities. Only 10% of the sample were students so this doesn’t really go into enough depth, hence the reason for conducting this research. Existing academic research emphasizes the importance of retailers making shopping for food easier and less time- consuming, Berry (1979).Some consumers in the UK would support such advice, but others will not. The latter take their meals more seriously than might be assumed in a fast food and microwave oriented society, retailers and food suppliers cannot afford to ignore this segment. The marketingWilliam Hanrahan 5 implications offered based on the Look What We Found! brand used the recommendations taken from these journals, completing a PEST analysis of the findings and conducting an in- depth market review seemed like a useful suggestion and will be implemented.3.6 Cluster Analysis Cluster Analysis in Marketing Research: Review and Suggestions for Application (Punj and Stewart, 1983)  Identifying Purchase Driving attributes and Market segments for PC’s using conjoint & cluster analysis (Lonial and Zaim, 2000)Cluster analysis is used in this paper to distinguish the product benefit related market segments for personal computers; this paper recognises cluster analysis and how identifying and understanding customers is crucial to business success in competitive markets.These literature reviews are relevant to the study, for this reason they can justify the use of cluster analysis as an analytical technique for data analysis. The first paper goes in depth about the subject and suggestions for best practice, whereas the other cluster analysis paper has a focus of PCs, although very different from this topic, the core values are stillWilliam Hanrahan 5 the same and differentiation is still a key value so it was decided to use this paper after a comprehensive search for food related cluster analysis papers brought little else.Nothing very similar has been published so this dissertation will be useful to help develop analytical methods of cluster analysis in relation to student segmentation.This paper deals with the classification method of cluster analysis with regards to marketing, the first paper reviewed is titled ‘Cluster analysis in marketing research: review and suggestions for application, from the journal of marketing research, published in 1983.The paper was written to address the authors concerns over lack of knowledge and classification of cluster analysis within marketing, an example is used to demonstrate this lack of knowledge, helping the authors to provide evidence to justify this paper and setting out what they intend to accomplish.This paper was written nearly 20 years after cluster analysis was identified as a method of classification, so this paper was written as an up to date summary at the time. Cluster analysis was constantly being added to and new types and methods were being used, making the subject confusing. This seemed to be dissuading academics and marketers from using the method, which could have led to an extinction of the form of data analysis. The paper looks at its applications to marketing problems, in reference to the initial concerns of the sceptics of cluster analysis.Stewart and Punj feel that cluster analysis has been often overlooked and potentially underused, and understood, not because of ineffectiveness, but because of the confusing array of names and methods of cluster analysis confronting the marketing researcher.Stewart and Punj define two general sets of issues that confront a marketing research seeking to use cluster analysis, the first they do not address as they state this area has beenWilliam Hanrahan 5 recently been covered. This is understandable and they choose to focus on the second set of issues, they state that are ‘more practical and pertain to the actual use of clustering procedures for data analysis’. The intention of this paper is to ‘use both theoretical and empirical findings to suggest which clustering options may be most useful for a particular research problem.’ The authors then decide to restrict their treatment of cluster analysis to the more common of the two approaches, classification. This is what cluster analysis has most frequently been used for and again allows Punj and Stewart to further narrow their focus of the broad subject of cluster analysis. Punj and Stewart define cluster analysis as a statistical method for classification, which makes no prior assumptions about important differences within a population. They state that it’s a purely empirical method of classification and as such is primarily an inductive technique.The area of classification was discussed as a fundamental importance to the philosophy of science in 1959, 1953 (Kemey and Kator), Cluster analysis provides one, empirically based means for explicitly classifying objects. Such a tool is particularly relevant for the emerging discipline of marketing which is still dealing with problems of how best to classify consumers, products, media types and usage occasions. This paper was prompted byWinds 1978 paper 5 years previous to this, which suggested future research was needed for the evaluation of the conditions under which various data analytical techniques are most appropriate.Punj and Stewart also quote Wind (1978), that grouping methods may be incorrect and the writers attribute this to the lack of research on this topic. The author Purj’s earlier work in1982 highlights the need for a better classification of relevant buyer characteristics. William Hanrahan 5 Cluster analysis has been employed in the development of potential new product opportunities. ‘By clustering brands / products, competitive sets within the larger market structure can be determined’, Thus a firm can examine its current offerings ‘Vis a Vis’ those of its competitors. The paper gives examples of cluster analysis in practice ‘in the problem of test market selection’ to show its uses and the advantages of cluster analysis for identification. A key point mentioned in this paper relates to how cluster analysis has the benefit of data reduction, which allows more easily manageable groups and easier presentation. Fisher (1969) argued that cluster analysis is more appropriate whenever data is too numerous or to detailed to be manageable. The journal uses a table to describe some recent applications of cluster analysis to marketing studies, this table seems as fantastic way to present the applications of cluster analysis, accompanied with sections ‘purpose of research’, ‘nature of data’ and ‘clustering methods used’. This has the major benefit in the clarity of the data presented, and makes the table particularly easy to understand when comparing, for example when looking for a similar study to this dissertation research. The paper offers a balanced view of the subject with a section demonstrating the problems with cluster analysis; a confusing problem is related to the origins of cluster analysis and the amount of different names and the problem of cluster definition. An interesting section of this journal is the empirical comparisons of method, this is evaluation of clustering methods, and involves comparing the results of differing methods applied to the same data sets. A conclusion of note is that the authors draw from the empirical findings is on the performance of clustering algorithms, as a clustering algorithm includes more and more observations, its performance tends to deteriorate, probably the result of outliers, suggesting that clustering all observations may not be good practice. Some valuable lessons can be taken from thisWilliam Hanrahan 5 literature, is has firstly helped to develop the researchers knowledge of cluster analysis, the paper has helped to identify potential clustering methods that the research shall use and also provided useful advice on what to avoid. Clustering analysis has much to offer as an aid for developing classification systems. To the extent of that classification is both the first and last step in scientific investigation; cluster analysis should hopefully have an increasing application in marketing. The work is a theoretical study, it is using past research and the knowledge of the writers’ are discussing the topic of cluster analysis, the authors main aims are to explore the area of cluster analysis, to review the subject, attempt to amalgamate and streamline 20-30 years of work on the subject and make suggestions for the application of cluster analysis, aimed mostly at marketing professionals. The claims by the authors are backed up comprehensively from a variety of sources, infact over 50 references are used within the text. Further reading into the topic led to a book titled Clustering andClassification (1996) written ten years on from this paper still shows major problems of developing effective clustering methods and carries on many of the similar points from thePunj and Stewarts 1986 paper. The focus of this research was to demonstrate the application of the statistical techniques of conjoint and cluster analysis to product positioning and market segmentation, in the context of PCs. This next paper is titled‘Identifying purchase driving attributes and market segments for PC’s using conjoint and cluster analysis. The paper is more recent from 2000, taken from the Journal of Economic and Social Research. This paper is an empirical study looking in depth at various forms of classification to segment markets and although the subject of PC’s is different from the focus of ready meals, it still bears some similarities in the subject of competitive advantage that this paper uses. As the journal uses two forms of classification for identification It will be interesting to see how the authors find these two types of analysis, the paper beginsWilliam Hanrahan 5 with a justification for adding value for business success, which involves identifying and understanding customers, their needs, wants and product preferences. This is what the questionnaire is attempting, using cluster analysis to identify market segments with similar product attributes with similar product attribute benefit affinities and in this paper cluster analysis is used to recognise the product benefit related market segments for personal computers. The paper gives a justification for advanced analysis for identification, stating the better the identification the more likely the case of adopting the correct strategies, for example, competitive advantage. This article was easy to understand, giving comprehensive definitions of relatively basic business terms, suggesting this paper is aimed at a larger target then simply marketing professionals, but students or businesses. It is a very good introduction into why a firm would want to analyse and identify its products and its market, making a few assumptions such as a market oriented firm, which is most likely if this type of analysis is taking place. This paper gives a background into the advantages of why a firm would want to use identification, not directly linked initially to a method but to set the scene of what would happen if it was to be done successfully.The two objectives of this paper are; ‘Using conjoint analysis to identify the most relevant attributes of personal computers and the relative importance of these attributes in influencing the purchase of PC’s’. & ‘Using cluster analysis for identifying the key benefit segments in the university/college market for PCs’. So also the added benefit of this paper is its similarity in terms of target market, as university students are the target group in this research. The paper gives an in-depth discussion of the research techniques used, firstly conjoint analysis, citing many references to past research on the subject in a variety of situations. ‘The nature of the product must be understood in terms of the salient attributes of the product and the relative importance of these attributes in influencing theWilliam Hanrahan 5 product or brand choice.’ This has lead to the creation of a questionnaire asking students to rate particular features of food on a Likert scale to enable the identification of their opinions in this particular market. Cluster analysis is defined as ‘a technique used for combining observations into relatively homogenous groups or clusters. For example, cluster analysis can be used to group respondents into clusters representing respondents who are very similar on given measures of interest’ (Sharma 1996: 187) This paper introduces several clustering alternatives and related algorithms, split into 3 categories, selecting the appropriate measures of similarity, choosing between a hierarchical or non-hierarchical clustering technique and specifying the number of clusters to be created and the distance measure to be used. This certainly is a lot clearer way of defining the differences in cluster analysis than the previous paper, although not going into much detail it gives a clear definition then explains where to find further explanation. The exact specifications for the cluster analysis research are as follows: To use quick cluster from the SPSS statistic package, to cluster the study participants of the questionnaire on the basis of the similarity of their utility functions for convenience food related attributes. When the individual utility functions of the student participants are clustered, it should be possibly to identify convenience related benefit segments and estimate their relative sizes. When these segments are viewed in tandem with the corresponding product attributes of importance, appropriate target market segments can be selected, and the ideal products for these segments created and positioned.’ The sample size is relatively small, however it is a fairly representative sample of the university faculty, consisting of mostly students who were in a good position to state their attribute related product preferences as many had recently purchased a PC, this hasWilliam Hanrahan 5 led to include questions such as ‘Do you regularly buy Convenience Food?’ The literature gives a three cluster solution, finally the text ends with a discussion of results, and some intelligent insights are made throughout this study, giving suggestions of its further use and limitations of the research. The paper concludes that the techniques, when properly used can be very useful in improving product positioning and market segmentation strategies.The final paper uses 6 sources for referencing, not a vast amount but it seems the paper was still successful in achieving its objectives. Both papers have helped in gaining a better understanding of cluster analysis and as a literature review they complimented each other well. 4.0 Methodology4.1 IntroductionThe previous chapter helped to gain an initial market understanding of the area of interest; this facilitated the informed development of a questionnaire. A questionnaire was deemed necessary in order to obtain new data based on Newcastle University students in areas which had previously not been studied in depth.William Hanrahan 5 The next stage consisted of a survey of Newcastle university students, where only students who were responsible for preparing their own meals could complete the full questionnaire, conducted electronically. The methodology is designed with the intention of yielding information that will allow the primary objectives of the study to be answered. Data was analysed initially based on descriptive analysis, then using cross tabulation and finally cluster analysis.4.2 Secondary Data collectionPreliminary research was carried out on secondary data to investigate the theories associated with students’ attitudes towards ambient food and identify limitations of previous research. Academic articles were found using computer databases, search engines and the reference section of other articles. Research into Ambient food and trends were gathered from Mintel (2004). Ambient Ready Meals – UK.The review of secondary data proved invaluable in the exploratory research phase, supplementing existing knowledge regarding factors affecting the consumption of convenience foods, whilst the analysis of previously employed research techniques provided an impartial base to inform the development of a questionnaire. Knowledge gathered through secondary sources proved important in refining the research objectives and hypotheses, and was also intended to follow on from, the theoretical basis of consumers’ behaviour with regard to their consumption of ambient meals and soups.William Hanrahan 5 Despite the value of secondary data analysis in the context of this research, it must be acknowledged that there are inherent limitations with secondary data; most importantly the fact that the research was collected under a different context for a differing purpose.4.3 Qualitative ResearchQualitative research is a non-numerical, descriptive way to collect and interpret information. The qualitative research was used to provide a deep understanding of all the key areas of this topic. Especially useful was a transcript from an interview between SharonKuznesof and Keith Gill (July 2007)4.4 Quantitative Research4.4.1 Questionnaire DesignThe questionnaire employed attitudinal Likert scales, with the primary intention of the questionnaire being able to yield end data which would facilitate the fulfilment of objectives to find out about students preferences and to segment the student population into clusters, a survey was preferred to a series of in-depth interviews on the basis of both practical and theoretical benefits offered by this research method. Employing a questionnaire was deemed to be more efficient in relation to both time and cost effectiveness, whilst this approach also facilitated the employment of cluster analysis thus allowing for the identification of the most important factors affecting purchasing decisions.The quantitative data was collected using a questionnaire. The findings from the literature review and in depth market review were used to design the questionnaire. TheWilliam Hanrahan 5 questionnaire was developed to cover the studies objectives research questions and hypotheses. It was appreciated that the design and development of the questionnaire was very important and required considerable thought in order to generate meaningful and reliable data.All but one question were closed questions, ensuring that responses could be statistically analysed. The closed questions also meant that the responses were straightforward for the respondent. All the questions provided data that was nominal or interval, five point scales were used from some of the questions; these were selected as they gave the consumers a range to choose from without being too confusing. The questions were designed to avoid bias, so the phrasing was carefully considered to avoid suggesting that some answers were more acceptable than others.Screening questions were selected to ensure that the respondents were Newcastle university students and responsible for purchasing meals while at university. These screening criteria were designed to ensure that all respondents were appropriate for the survey. If students weren’t eligible to complete the questionnaire then the questionnaire was designed not to allow students to progress to the next stage and instead ended the questionnaire. This resulted in a high percentage of complete and eligible responses.The questionnaire was designed into sections and made as user friendly as possible, the questions were designed using ordinal scales and five point Likert scales to measure attitudinal variables, the sections of the questionnaire were as follows:William Hanrahan 5  Screening questions  Importance of food features  Soup type preference  Meal type preference  Marketing  Financial  The Tanfield Food Group Meal and Soups  DemographicPilot testing was conducted to ensure the wording of questions was appropriate and the length of the questionnaire did not result in respondent fatigue. The pilot test used 5 random respondents to assess the practicality of the questionnaire, also to gather an approximate time of completion for the survey. It was found that on average it took 5 minutes’ to complete the test, and the survey received a positive response.The survey was send online which allowed easy distribution within the University network.The aim of the questionnaire and use of data findings were explained to the participant in the survey link. Respondents were informed that the questionnaire would take about 5 minutes to complete and that all answers were to be confidential.To aid questionnaire design the researcher consulted Dr Eric Ruto, who had substantial knowledge on this subject, he provided useful suggestions for improvement.The questionnaire was based on a questionnaire used in ACE2004 relating to supermarket shopping, the questionnaire was analysed to provide insightful conclusions and recommendations. Where possible a similar format for the questions was followed and this ensured that the questionnaire was designed effectively, Dr Eric Ruto checked the final questionnaire and was happy with its format.William Hanrahan 5 4.4.2 Data CollectionOn-line self administered questionnaires posted on a commercial website were sent to 350Newcastle University students (contacted via a Facebook group set up – Appendix 6). Personal email sent using students email list to students from a range of departments, sent to about 700 Newcastle university students generating 111 responses, a response rate of15%, this method was less time consuming than one to one surveys, the answers were automatically saved to an Excel files and transferred into SPSS for analysis.4.5 Cluster AnalysisCluster analysis helps to segment people into different target markets. Cluster analysis was conducted in order to examine how the group can be positioned in the market according to the student sector. Cluster analysis involves determining the number of clusters, identifying the membership of each group and profiling the characteristics of each group.William Hanrahan 5 Certain criteria places the objects within the different groups, these criteria can be that objects should be as similar as possible and / or objects belonging to different groups should be as dissimilar as possible. The most common application of cluster analysis is in segmentation of consumers or products. Basic data is used to create a closeness of the objects; the method is determined by the properties of the data, non metric data using similarity measures with metric data using distance measures. 4.5.1 Clustering TechniquesHierarchical clustering begins with ungrouped objects and merges them into a successively smaller number of groups. This is referred to as divisive clustering. At first each object occupies its own cluster, so the researcher must decide the appropriate number of clusters retrospectively. This procedure employs the information on a distance matrix and a merger takes place between the objects so that at each stage the number of clusters is reduced by one. The Gower diagram is good for determining the appropriate number of clusters, but doesn’t show much more, usually the agglomeration schedule is used in conjunction with the dendrogram and Gower diagram to decide the number of clusters. There are many specific hierarchical techniques; some have been covered in the literature review.4.5.2 Optimisation techniquesBecause of the dissertation objectives, it was necessary to pay close attention to pre selecting the clusters as ideally the research could identify around three to five equally sized clusters. The two stages involved are the initial grouping of data and application of a clustering criterion to reach a final solution. The whole point of clusters is to obtain aWilliam Hanrahan 5 profile of the clusters; these are obtained from variables used in the analysis as target variables, and other variables such as demographic, behavioural and attitudinal variables.Profiles are established by examining statistically significant differences between clusters, and the method of establishing these differences depends on the measurement properties of the profile variables. If the profile variable is a nominal variable then it’s recommended to conduct a test of the nominal cluster identity variable with the nominal profile variable using a Chi square contingency test using Crosstabs. The Profiles will then be summarised in the form of a table to provide identification of the distinct characteristics of each cluster and hence to a descriptive label for the cluster.4.5.3 Applications of Cluster Analysis to MarketingThe intention of this cluster method is to identify groups of Newcastle university students based distinctive features, including sex, finance, eating and lifestyle characteristics. The segments can be identified on the basis of their perceptions of products, the benefits they seek from products to fit in with their lifestyles.4.5.4 Problems with Cluster AnalysisCluster analysis is associated with problems, the main issues are that decisions made by the researcher may have a strong effect on the solution; this is because the decisions about the cluster shape and size are made by the researcher.4.5.5 SummaryCluster analysis is a useful technique to establish data groups, but the analysis is very much in the researcher’s hands, they have many choices, similarity or distance measures, hierarchical or non hierarchical approaches and the algorithm to be used. This helped to realise the depth that the first paper went into in order to inform marketers about theWilliam Hanrahan 5 particular decisions that need making. It seems that following past examples is a good way to go, look at a past study, has it worked? What was the subject? Can this be replicated in this study?It is hoped that cluster analysis of the questionnaire results will result in finding appropriately sized student clusters. The reason for using this type of data analysis is that if clusters can be identified then this could prove to The Tanfield Food Group that there is a viable student market, or possibly isn’t. As found in the market review, new markets should be explored, why not start with the lucrative student market? The aim of cluster analysis is to group objects (e.g. people, products) on the basis of numerical measures of the objects. The technique is concerned with deciding the number of clusters, identifying the membership of each group, and profiling the characteristics of each group. Cluster analysis has two main applications in marketing; the selection of test markets, and the identification of consumer of product segments.4.6 Data AnalysisThe analysis employed SPSS 15.0 for Windows, conducting cluster analysis with the aim of identifying the underlying properties of the data, and establishing whether respondents fell into distinct segments which could facilitate more informed targeting.William Hanrahan 5 Results from the questionnaires were entered into SPSS using simple coding methods, giving numbered responses to each individual question’s answer. Cluster analysis was then carried out. The cluster analysis was carried out by running 6, 5, 4 , 3, 2 cluster solutions –4 was decided upon as it contained similar amounts of students as opposed to some of the small sized clusters that originated when running all the other cluster solutions.Once the number of clusters had been established, crosstabs were used to study behavioural profiles. Descriptive statistics such as tables and graphs were presented to clearly compare and describe data. Statistics were used to identify levels of significance and determine whether the data represents real relationships. The five per cent significance level was used throughout the analysis.4.6.1 Questionnaire ResponseOf the 131 participants to the survey there were 108 useable responses for analysis.4.6.2 Segmentation of sampleWilliam Hanrahan 5 The objectives of the study attempted to find if differing segments of students exist, and if so could they be a viable target as a consumer of ambient food such as The Tanfield FoodGroup.4.6.3 Sample SizeAlthough the target for responses was 100, it seemed that obtaining more responses would be beneficial and result in more reliable results, after consulting with an experienced lecturer the researcher was assured that the sample size was large enough to allow fair results, however since carrying out this study, the researcher has learnt of many other ways to yield high response levels that had not been considered, these will be mentioned in the conclusions of the research.5.0 ResultsThe data analysis process has been designed with the intention of satisfying the objectives of the report. This chapter presents the results of questionnaire SPSS analysis, offeringWilliam Hanrahan 5 interpretation of the data which is subsequently used as a basis for answering these objectives.The chapter is structured divided into a series of subsections in order to clarify each of the distinct stages of the analysis. This section presents the results and interpretation of the descriptive analysis, providing a summary of the subjects derived in each phase of the process. The following section presents the results of the cluster analysis, subsequently interpreting the data with the intention of establishing the most important factors when purchasing ambient foods, as well as establishing the differing consumer segments which exist for this product. Selected tables from the SPSS output is included in Appendix 2 and the majority ofSPSS cluster analysis output is located in Appendix 3.5.1 Descriptive Analysis – Key Results SummarySPSS 15.0 was used to analyse behavioural and demographic questions.Fig 2 FrequenciesWilliam Hanrahan 5 Regularly Buy SoupValid Cumulative Frequency Percent Percent Percent Valid Yes 55 49.5 49.5 49.5 No 56 50.5 50.5 100.0 Total 111 100.0 100.0 From the student sample it’s almost a 50/50 split between students regularly purchasing soup, this question was used to check that a high enough sample were actually regular consumers, even so, this shows the potential of students who currently don’t regularly purchase soup. This seems like a good potential market, students who want a fairly quick and easy ‘fix’ of vegetables to help them stay health and avoid the regular colds that are so often associated with university life.Most Likely Soup PurchaseValid Cumulative Frequency Percent Percent Percent Valid Canned 55 49.5 49.5 49.5 Ambient 9 8.1 8.1 57.7 Dried 16 14.4 14.4 72.1 Chilled Fresh 31 27.9 27.9 100.0 Total 111 100.0 100.0 Canned Soup is the most likely soup purchase among the sampled student group, it is predicted because of its low price and ease of storage, Chilled fresh is a popular choice amongst the more health conscious consumers while dried and ambient are less popular as a likely soup purchase.Food Features - Locally SourcedValid Cumulative Frequency Percent Percent Percent Valid Very 19 17.1 17.1 17.1 UnimportantWilliam Hanrahan 5 Unimportant 40 36.0 36.0 53.2 Neither 26 23.4 23.4 76.6 Important 24 21.6 21.6 98.2 Very Important 2 1.8 1.8 100.0 Total 111 100.0 100.0 The feature of being locally sourced isn’t particularly important, with ‘Unimportant’ coming through at 36% of responses, 23.4% answered Important and Very important, showing that this is considered in the purchase decision, it will be interesting to see if the group who find this as an important factor belong to a cluster, as this may have useful marketing implications.Food Features - Quality of FoodValid Cumulative Frequency Percent Percent Percent Valid Unimportant 3 2.7 2.7 2.7 Neither 11 9.9 9.9 12.6 Important 62 55.9 55.9 68.5 Very 35 31.5 31.5 100.0 Important Total 111 100.0 100.0 As expected, this is quite an important part of a student’s choice in food, with 87.4% putting Quality of food as important or very important. It is vital therefore that the quality of the product is displayed when appealing to this group. Or using the opposite case, if students feel the product isn’t a quality product, and then many students will be put off.Food Features - Value for MoneyValid Cumulative Frequency Percent Percent Percent Valid Very 1 .9 .9 .9 UnimportantWilliam Hanrahan 5 Unimportant 1 .9 .9 1.8 Neither 11 9.9 9.9 11.7 Important 52 46.8 46.8 58.6 Very Important 46 41.4 41.4 100.0 Total 111 100.0 100.0 Again this isn’t a surprising set of results, as 88.2% place an importance and high importance on value for money, it will be interesting to see in the cluster analysis if the other 11.8% sampled who don’t place as high an important of value for money will be located in a similar cluster, and learn more about this justification for this answer.Food Features - ChoiceValid Cumulative Frequency Percent Percent Percent Valid Very 1 .9 .9 .9 Unimportant Unimportant 8 7.2 7.2 8.1 Neither 15 13.5 13.5 21.6 Important 77 69.4 69.4 91.0 Very Important 10 9.0 9.0 100.0 Total 111 100.0 100.0 Student place choice as quite important with almost 70% of respondents placing this attribute as important, it’s a quite ambiguous question to ask, but it suggests that in a range of meals offered by a particular brand if they are expected to become loyal customers as opposed to making occasional purchases then the company must be prepared to offer a reasonable level of choice to the consumer in order to keep the consumer happy and satisfied. Food Features - PackagingValid Cumulative Frequency Percent Percent Percent Valid Very 20 18.0 18.0 18.0 UnimportantWilliam Hanrahan 5 Unimportant 47 42.3 42.3 60.4 Neither 29 26.1 26.1 86.5 Important 14 12.6 12.6 99.1 Very Important 1 .9 .9 100.0 Total 111 100.0 100.0 Students don’t place a high importance on Packaging, with 86.5% of students placing it as very unimportant, unimportant or neither. Look What We Found! products do have an innovative packaging style but this is also relating to its ease of storage more than anything.This result highlights that compared to Quality and Nutrition and the other factors, in comparison the aesthetics of the pack are not really of key importance to students. Food Features - Ease of StorageValid Cumulative Frequency Percent Percent Percent Valid Very 2 1.8 1.8 1.8 Unimportant Unimportant 21 18.9 18.9 20.7 Neither 31 27.9 27.9 48.6 Important 46 41.4 41.4 90.1 Very Important 11 9.9 9.9 100.0 Total 111 100.0 100.0 This is an interesting result, over 50% of students found that ease of storage was an important aspect of the shopping behaviour, It’s suspected this figure is high as many students living in shared houses will have limited space and this makes ease of storage a more important factor. This is positive for the ambient food market where ease of storage is a key attribute. Food Features - Ease of UseValid Cumulative Frequency Percent Percent Percent Valid Very 1 .9 .9 .9 UnimportantWilliam Hanrahan 5 Unimportant 15 13.5 13.5 14.4 Neither 34 30.6 30.6 45.0 Important 52 46.8 46.8 91.9 Very Important 9 8.1 8.1 100.0 Total 111 100.0 100.0 Earlier it was noted that the lifestyle of a student suggests a higher preference for easier methods of food preparation, where things like speed and ease mean the student can focus on other aspects of student life.54.9% placed an important – very important regarding Ease of use, again this will be interesting when it comes to clustering the data to see if a connection can be with a cluster group and those students who see ease of use as an important or unimportant aspect of convenience food shopping.Food Features - Cooking TimeValid Cumulative Frequency Percent Percent Percent Valid Very 2 1.8 1.8 1.8 Unimportant Unimportant 14 12.6 12.6 14.4 Neither 34 30.6 30.6 45.0 Important 49 44.1 44.1 89.2 Very Important 12 10.8 10.8 100.0 Total 111 100.0 100.0 For similar reasons as before, cooking time is not surprisingly quite high importance, with54.9% of the sample seeing cooking time as either important or very important. So far the results seem to suggest that there seems to be potential for ambient food products to be targeted to this student group. Food Features - Nutritional ValueValid Cumulative Frequency Percent Percent Percent Valid Very 1 .9 .9 .9 UnimportantWilliam Hanrahan 5 Unimportant 6 5.4 5.4 6.3 Neither 15 13.5 13.5 19.8 Important 55 49.5 49.5 69.4 Very Important 34 30.6 30.6 100.0 Total 111 100.0 100.0 Around 20% of the sample doesn’t place much importance on the nutritional value of purchasing food, 50% find nutritional value and 34% see nutritional value as Very important. It would be interesting to see how these three groups will be placed in the clusters, there is potential to see if a particular cluster takes nutritional value more seriously than others.Brand Info - Look What We FoundValid Cumulative Frequency Percent Percent Percent Valid Never Heard 88 79.3 79.3 79.3 of Have heard, 9 8.1 8.1 87.4 Not Sure Why Have heard, know 11 9.9 9.9 97.3 products Have heard, 3 2.7 2.7 100.0 tried products Total 111 100.0 100.0 This result is surprising; it really shows the potential that ambient foods have within the ambient food market, in terms of the brand which is the reason for the focus on the LookWhat We Found brand. Nearly 80% of students have never heard of the brand, 8% have heard of the brand but weren’t sure why. 10% have heard of the product and around 2% have actually tried the product.Regular Buy MealValid Cumulative Frequency Percent Percent PercentWilliam Hanrahan 5 Valid Yes 74 66.7 66.7 66.7 No 37 33.3 33.3 100.0 Total 111 100.0 100.0 This question asks the student sample whether they regularly purchase convenience meals,2/3’s of the sample do regularly purchase convenience meals; this suggests that the student group should be quite receptive to a new form of convenience meal, depending on it meeting the relevant necessary attributes.Most Likely Meal PurchaseValid Cumulative Frequency Percent Percent Percent Valid Chilled 53 47.7 47.7 47.7 Ambien 13 11.7 11.7 59.5 t Tinned 4 3.6 3.6 63.1 Frozen 37 33.3 33.3 96.4 Dried 4 3.6 3.6 100.0 Total 111 100.0 100.0 This question looks into the current preferences of students and asks which single type of meal would they be most likely to purchase, chilled was most popular achieving nearly 50% of the responses, Frozen received a third, while Ambient food followed at 11.7%, this is quite high when considering that many consumers don’t fully understand the ambient food market very well, but it scored higher than ambient tinned food.Food Decision MakingValid Cumulative Frequency Percent Percent Percent Valid You 61 55.0 55.0 55.0 Jointly with 20 18.0 18.0 73.0 Others Depends 30 27.0 27.0 100.0 Total 111 100.0 100.0 William Hanrahan 5 The question asking about food decision making was asked simply for the reason that it could be of use to know the most common purchasing form, which may help marketers when deciding advertising campaigns to appeal more to individuals or to groups.It will also be interesting to see if the buying individually or in group affects the cluster that these students fall into.Usual Shop - Marks and SpencerValid Cumulative Frequency Percent Percent Percent Valid Yes 41 36.9 36.9 36.9 No 70 63.1 63.1 100.0 Total 111 100.0 100.0 36.9% of students listed Marks & Spencer as one of their 3 most common shopping destinations. This is quite high and suggests that a particular segment of Newcastle consumers shop here, cluster analysis will later identify if any connections can be made.Usual Shop - Morrison’sValid Cumulative Frequency Percent Percent Percent Valid Yes 41 36.9 36.9 36.9 No 70 63.1 63.1 100.0 Total 111 100.0 100.0 36.9% of students listed Morrison’s as one of their 3 most common shopping destinations.This is quite high and suggests that a particular segment of Newcastle consumers shop here.Usual Shop - Sainsbury'sValid Cumulative Frequency Percent Percent Percent Valid Yes 36 32.4 32.4 32.4 No 75 67.6 67.6 100.0 Total 111 100.0 100.0 William Hanrahan 5 32.4% of students listed Sainsbury’s as one of their 3 most common shopping destinations. This is quite high and suggests that a particular segment of Newcastle consumers shop here, cluster analysis will later identify if any connections can be made.Usual Shop - TescoValid Cumulative Frequency Percent Percent Percent Valid Yes 91 82.0 82.0 82.0 No 20 18.0 18.0 100.0 Total 111 100.0 100.0 82% of students listed Tesco’s as one of their 3 most common shopping destinations. This is very high and suggests that most Newcastle student consumers shop here, if it turns out that there is a student market for brands such as Look What We Found! then Tesco must surely be considered as a key stockist.Usual Shop - WaitroseValid Cumulative Frequency Percent Percent Percent Valid Yes 7 6.3 6.3 6.3 No 104 93.7 93.7 100.0 Total 111 100.0 100.0 6.3% of students listed Waitrose as one of their 3 most common shopping destinations.This is low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - OtherValid Cumulative Frequency Percent Percent Percent Valid Yes 6 5.4 5.4 5.4 No 105 94.6 94.6 100.0 Total 111 100.0 100.0 5.4% of students listed other retailers as one of their 3 most common shopping destinations. This is low and suggests students in Newcastle usually tend to shop at theWilliam Hanrahan 5 outlets mentioned in the questionnaire, however maybe negative associations related to‘other’ put students off, while answers such as Online Shops, Market Stalls, this could have resulted in a more varied set of results.BudgetValid Cumulative Frequency Percent Percent Percent Valid Yes 48 43.2 43.2 43.2 No 63 56.8 56.8 100.0 Total 111 100.0 100.0 The researcher thought it would be useful in determining the different clusters to ask the question to find out if students used a budget; this could have useful implications if the analysis shows a link to the groups.Average Weekly SpendValid Cumulative Frequency Percent Percent Percent Valid Up to £15 29 26.1 26.1 26.1 £16 - 30 60 54.1 54.1 80.2 More than 22 19.8 19.8 100.0 £30 Total 111 100.0 100.0 The researcher thought it would be useful in determining the different clusters to ask the question to find out students average weekly spend, the highest frequency of the results was in the £16-30 category, at 54%, 26% spent ‘Up to £15’ while the smallest category was the ‘more than £30’ at 20%. Hopefully this will be connected to the cluster groups, with average weekly spend linked to membership of particular clusters.Time spent preparationValid Cumulative Frequency Percent Percent Percent Valid 0 - 15 12 10.8 10.8 10.8William Hanrahan 5 Minutes 16 - 30 58 52.3 52.3 63.1 Minutes 31 - 45 36 32.4 32.4 95.5 Minutes 46-59 4 3.6 3.6 99.1 Minutes 1 Hour + 1 .9 .9 100.0 Total 111 100.0 100.0 The researcher thought this question could give some worthwhile results if a link could be made between the usual time a student spend preparing his/her meal and there cluster group. It’s hard to say who would be more likely to purchase ambient meals out of this group as the answer simply suggests at the moment how long they are taking, not actually if they would like to spend less time than they are currently doing. It was also worthwhile information to know, however 95% of students currently spend 0 – 45 minutes making dinner. Maybe those who spend 0 – 15 minutes will be part of a cluster that are more keen on convenience food then those who may ‘enjoy’ spending a longer time cooking meals. Special offer AttractionValid Cumulative Frequency Percent Percent Percent Valid Yes 106 95.5 95.5 95.5 No 5 4.5 4.5 100.0 Total 111 100.0 100.0 Of all the university students sampled - 95% were attracted by special offers to purchase, this shows how important special offers are to students and has strong marketing implications.To understand how Newcastle students felt about Look What We Founds! Current range of meals and soups, students were asked to rate their purchase likelihood for each meal. This should hopefully give recommendations for the most desired product which to focusWilliam Hanrahan 5 marketing attempts on and later cluster analysis may be able to link different clusters with favoured meal choices.The researcher accepts that this area is a niche market and that as the meal choices are not the normal convenience meal products that on the questionnaire the meals are likely to get quite a poor response of purchase likelihood, the key point is to identify the largest areas of potential and also hopefully identify a cluster later on that’s more receptive to this meals and market to them accordingly.Purchase Likelihood - MeatballsValid Cumulative Frequency Percent Percent Percent Valid Very 30 27.0 27.0 27.0 Unlikely Unlikely 34 30.6 30.6 57.7 Neither 22 19.8 19.8 77.5 Likely 20 18.0 18.0 95.5 Very Likely 5 4.5 4.5 100.0 Total 111 100.0 100.0 Meatballs had a fairly negative response, with 77.5% Indifferent, Unlikely and Very Unlikely to purchase this option, however finding more about the remaining 22.5% could be of use to Tanfield.Purchase Likelihood - FellsideValid Cumulative Frequency Percent Percent Percent Valid Very 43 38.7 38.7 38.7 UnlikelyWilliam Hanrahan 5 Unlikely 42 37.8 37.8 76.6 Neither 13 11.7 11.7 88.3 Likely 12 10.8 10.8 99.1 Very Likely 1 .9 .9 100.0 Total 111 100.0 100.0 The Fellside meal didn’t seem too popular with the Newcastle students, with 88.3%Indifferent, Unlikely and Very Unlikely to purchase this option. Over 11% were Likely orVery likely to purchase this meal.Purchase Likelihood - ChilliValid Cumulative Frequency Percent Percent Percent Valid Very 42 37.8 37.8 37.8 Unlikely Unlikely 34 30.6 30.6 68.5 Neither 21 18.9 18.9 87.4 Likely 14 12.6 12.6 100.0 Total 111 100.0 100.0 The Chilli meal didn’t seem too popular with the Newcastle students, with 87.4%Indifferent, Unlikely and Very Unlikely to purchase this option. Quite a small amount around 12% was Likely to purchase this meal.Purchase Likelihood - HotpotValid Cumulative Frequency Percent Percent Percent Valid Very 46 41.4 41.4 41.4 Unlikely Unlikely 33 29.7 29.7 71.2 Neither 12 10.8 10.8 82.0 Likely 18 16.2 16.2 98.2 Very Likely 2 1.8 1.8 100.0 Total 111 100.0 100.0 71.2% of the sample said they were Very Unlikely or Unlikely to purchase this Hotpot meal while 18% were likely or very unlikely to purchase the meal. Purchase Likelihood - StewWilliam Hanrahan 5 Valid Cumulative Frequency Percent Percent Percent Valid Very 55 49.5 49.5 49.5 Unlikely Unlikely 30 27.0 27.0 76.6 Neither 14 12.6 12.6 89.2 Likely 12 10.8 10.8 100.0 Total 111 100.0 100.0 This seems quite an unpopular choice within the student group, with half the sample beingVery unlikely to purchase this meal. It seems fair to say from that, students have a strong negative disposition against this meal. Only 10.8% of the student sample put down ‘likely’ as purchase likelihood.Purchase Likelihood - Old Spot PorkValid Cumulative Frequency Percent Percent Percent Valid Very 48 43.2 43.2 43.2 Unlikely Unlikely 29 26.1 26.1 69.4 Neither 20 18.0 18.0 87.4 Likely 13 11.7 11.7 99.1 Very Likely 1 .9 .9 100.0 Total 111 100.0 100.0 The highest frequency in this group was very unlikely at 43.2% of the sample, 26.1% were unlikely, while 30.6% answered Neither, Likely and Very Likely.Purchase Likelihood - Rabbit in LeekValid Cumulative Frequency Percent Percent Percent Valid Very 52 46.8 46.8 46.8 Unlikely Unlikely 31 27.9 27.9 74.8William Hanrahan 5 Neither 12 10.8 10.8 85.6 Likely 12 10.8 10.8 96.4 Very Likely 4 3.6 3.6 100.0 Total 111 100.0 100.0 74.8% of the sample responded with Very Unlikely and Unlikely, leaving a neutral and positive dispositional selection of 25.2% students.Purchase Likelihood - StroganoffValid Cumulative Frequency Percent Percent Percent Valid Very 51 45.9 45.9 45.9 Unlikely Unlikely 23 20.7 20.7 66.7 Neither 18 16.2 16.2 82.9 Likely 15 13.5 13.5 96.4 Very Likely 4 3.6 3.6 100.0 Total 111 100.0 100.0 66.7% of the sample responded Very Unlikely and Unlikely, leaving the remaining third asIndifferent, Likely and Very likely to purchase the stroganoff meal. With 17.1% either Likely or Very likely to purchase from this simple description.Purchase Likelihood - CasseroleValid Cumulative Frequency Percent Percent Percent Valid Very 34 30.6 30.6 30.6 Unlikely Unlikely 26 23.4 23.4 54.1 Neither 24 21.6 21.6 75.7 Likely 25 22.5 22.5 98.2 Very Likely 2 1.8 1.8 100.0 Total 111 100.0 100.0 The casserole meal received quite a high response of Likely and Very Likely at almost 25% of the sample with around 20% being indifferent. Almost half the students sampled therefore could potentially purchase the casserole meal, although very likely is a tiny proportion at 1.8%, a more definite set of responses would provide better justification.William Hanrahan 5 Purchase Likelihood - Velvet PorterValid Cumulative Frequency Percent Percent Percent Valid Very 39 35.1 35.1 35.1 Unlikely Unlikely 28 25.2 25.2 60.4 Neither 17 15.3 15.3 75.7 Likely 19 17.1 17.1 92.8 Very Likely 8 7.2 7.2 100.0 Total 111 100.0 100.0 The velvet porter meal is interesting, depending on how the cluster analysis works out, this could have some valuable results, there is a strong divide between Very Unlikely at 35% and Likely and Very Likely at 24.3%. It will be interesting to see if other variables have an effect on the type of student that answers Unlikely/Likely of purchase likelihood of this question.Soup Likelihood - Beef and TomatoValid Cumulative Frequency Percent Percent Percent Valid Very 36 32.4 32.4 32.4 Unlikely Unlikely 24 21.6 21.6 54.1 Neither 18 16.2 16.2 70.3 Likely 28 25.2 25.2 95.5 Very Likely 5 4.5 4.5 100.0 Total 111 100.0 100.0 54% of the sample responded Very Unlikely and Unlikely to Beef and Tomato soup, 16.2% were indifferent, while almost 30% responded likely and Very likely, this is quite a good response and suggests it could be a popular choice amongst students.Soup Likelihood - Hum and PeaFrequency Percent Valid CumulativeWilliam Hanrahan 5 Percent Percent Valid Very 32 28.8 28.8 28.8 Unlikely Unlikely 31 27.9 27.9 56.8 Neither 11 9.9 9.9 66.7 Likely 29 26.1 26.1 92.8 Very Likely 8 7.2 7.2 100.0 Total 111 100.0 100.0 Here 33.3% are Likely and Very likely to purchase this soup type, while 28.8% are Very unlikely to do so; this shows quite a strong variance between the two extremes. Potentially the cluster analysis will show these two variances by locating the different students’ preferences in separate clusters.Soup Likelihood - ParsnipValid Cumulative Frequency Percent Percent Percent Valid Very 33 29.7 29.7 29.7 Unlikely Unlikely 31 27.9 27.9 57.7 Neither 16 14.4 14.4 72.1 Likely 20 18.0 18.0 90.1 Very Likely 11 9.9 9.9 100.0 Total 111 100.0 100.0 Almost 30% of student respondents answered Likely or Very likely for Parsnip soup, again with a large variation of nearly 30% responding Very Unlikely to Parsnip soup.Soup Likelihood - ChickenValid Cumulative Frequency Percent Percent Percent Valid Very 15 13.5 13.5 13.5 Unlikely Unlikely 18 16.2 16.2 29.7 Neither 19 17.1 17.1 46.8 Likely 45 40.5 40.5 87.4 Very Likely 14 12.6 12.6 100.0 Total 111 100.0 100.0 William Hanrahan 5 The most popular soup out the selection is chicken soup, with 53.1% of the sample answering Likely or Very Likely, and just 13.5% answering very unlikely.Soup Likelihood - MushroomFrequenc Valid Cumulative y Percent Percent Percent Valid Very 43 38.7 38.7 38.7 Unlikely Unlikely 26 23.4 23.4 62.2 Neither 16 14.4 14.4 76.6 Likely 21 18.9 18.9 95.5 Very Likely 5 4.5 4.5 100.0 Total 111 100.0 100.0 23.4% of the sample responded likely or Very likely, while 62.2% responded Very Unlikely and Unlikely to the mushroom soup.Soup Likelihood - Tomato and CheeseValid Cumulative Frequency Percent Percent Percent Valid Very 16 14.4 14.4 14.4 Unlikely Unlikely 23 20.7 20.7 35.1 Neither 21 18.9 18.9 54.1 Likely 42 37.8 37.8 91.9 Very Likely 9 8.1 8.1 100.0 Total 111 100.0 100.0 Not surprisingly this option proved quite popular with the student sample, 35% said they were very unlikely and unlikely to purchase the soup, but 45.9% responded as being Likely or Very likely to purchase the soup.William Hanrahan 5 How Often Eat Out Per MonthValid Cumulative Frequency Percent Percent Percent Valid 0 - 2 37 33.3 33.3 33.3 3 - 5 49 44.1 44.1 77.5 6- 10 21 18.9 18.9 96.4 11+ 4 3.6 3.6 100.0 Total 111 100.0 100.0 3 Distinct groups appear here, 33.3% eating out 0 – 2 times per month, 44% eating out 3 –5 times per month, with almost 20% heading out 6 – 10 times per month. Only 4% of the student sample eats out more than 11 times per month so that isn’t a key group.Preferred cuisineValid Cumulative Frequency Percent Percent Percent Valid Indian 23 20.7 20.7 20.7 Chinese 20 18.0 18.0 38.7 Italian 35 31.5 31.5 70.3 French 3 2.7 2.7 73.0 British 14 12.6 12.6 85.6 Mexican 10 9.0 9.0 94.6 Spanish 6 5.4 5.4 100.0 Total 111 100.0 100.0 This question was used as it was thought that it could lead to recipe ideas and food style recommendations for The Tanfield Food Group, the four most popular groups were Italian with 31.5%, Indian with 20.7%, Chinese with 18% and British with 12.6%Spending HabitsValid Cumulative Frequency Percent Percent Percent Valid Yes 18 16.2 16.2 16.2 No 93 83.8 83.8 100.0 Total 111 100.0 100.0 William Hanrahan 5 In order to demonstrate the strength of the student market, it was considered that by asking if the credit crunch had affected student shopping behaviour, it would either help distinguish the various cluster groups and also show as a whole how students behave regarding convenience foods during economic problems, interestingly students seemed to be relatively unaffected with 83.8% of the sample saying no. New Product MarketingValid Cumulative Frequency Percent Percent Percent Valid Newspaper 1 .9 .9 .9 TV 25 22.5 22.5 23.4 Radio 1 .9 .9 24.3 Magazines 6 5.4 5.4 29.7 Billboards & 1 .9 .9 30.6 Posters In Store 48 43.2 43.2 73.9 Free Samples 13 11.7 11.7 85.6 Word of Mouth 16 14.4 14.4 100.0 Total 111 100.0 100.0 This question seeks to find the best methods to communicate to students, in store promotions were most popular with 43.2%, followed by 22.5% on TV and 11.7% for FreeSamples.William Hanrahan 5 GenderValid Cumulative Frequency Percent Percent Percent Valid Female 61 55.0 55.0 55.0 Male 50 45.0 45.0 100.0 Total 111 100.0 100.0 The sample contained 55% Females and 45% of Males, so quite a fair mixAccommodationValid Cumulative Frequency Percent Percent Percent Valid Parents 1 .9 .9 .9 University 6 5.4 5.4 6.3 Non University Accommodatio 104 93.7 93.7 100.0 n Total 111 100.0 100.0 94% of the sample lived in Non University accommodation; the remaining 6% were living inUniversity accommodation or with parents, the questionnaire used qualifying questions which meant that respondents had to be responsible for providing their own meals otherwise they wouldn’t be allowed to fill in the questionnaire. This resulted in mostly respondents from non university accommodation, i.e. students living in private rented flats.Term Time LocationValid Cumulative Frequency Percent Percent Percent Valid Heaton 9 8.1 8.1 8.1 Jesmond 76 68.5 68.5 76.6 Sandyford 9 8.1 8.1 84.7 Fenham 4 3.6 3.6 88.3 City Centre 7 6.3 6.3 94.6 Castle Leazes & 3 2.7 2.7 97.3 Spital Tongues Other 3 2.7 2.7 100.0 Total 111 100.0 100.0 William Hanrahan 5 Year of StudyValid Cumulative Frequency Percent Percent Percent Valid 1 Year 6 5.4 5.4 5.4 2 Years 19 17.1 17.1 22.5 3 Years 81 73.0 73.0 95.5 More than 3 5 4.5 4.5 100.0 Years Total 111 100.0 100.0 Most of the respondents were in their third year of study at 73%, The reasons for this disproportionate amount is for a few reasons, firstly because the fact that the researcher was a third year, and showing the strength of offering the survey link through online social networking sights, most respondents came from this source. Also the researcher sent out an email over OWA to various students but it seems that third year students are more understanding of the need for dissertation responses as many of them are sending out dissertations themselves, as a result are the most frequent group who responded to the questionnaire.William Hanrahan 5 5.2 Cluster Analysis 5.2.1 Crosstabs Analysis Cluster Number of Case * GenderCase Processing SummaryCases Valid Missing Total N Percent N Percent N Percent Cluster Number of Case * Gender 111 100.0% 0 .0% 111 100.0%Cluster Number of Case * Gender Cross tabulationGender Female Male Total Cluster Cluster 1 Count 30 10 40 Number of % within Cluster Case Number of Case 75.0% 25.0% 100.0% Cluster 2 Count 10 15 25 % within Cluster Number of Case 40.0% 60.0% 100.0% Cluster 3 Count 4 15 19 % within Cluster Number of Case 21.1% 78.9% 100.0% Cluster 4 Count 17 10 27 % within Cluster Number of Case 63.0% 37.0% 100.0% Total Count 61 50 111 % within Cluster Number of Case 55.0% 45.0% 100.0%Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 18.273(a) 3 .000 Likelihood Ratio 18.998 3 .000 Linear-by-Linear 2.616 1 .106 Association N of Valid Cases 111 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.56.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .376 .000 N of Valid Cases 111 A Not assuming the null hypothesis. b using the asymptotic standard error assuming the null hypothesis. Cluster Number of Case * How Often Eat OutWilliam Hanrahan 5 Case Processing SummaryCases Valid Missing Total N Percent N Percent N Percent Cluster Number of Case * How Often Eat 111 100.0% 0 .0% 111 100.0% Out Per MonthCluster Number of Case * How Often Eat Out Per Month Cross tabulationHow Often Eat Out Per Month 0 - 2 3 - 5 6- 10 11+ Total Cluster Cluster 1 Count 13 17 7 3 40 Number of % within Cluster Case Number of Case 32.5% 42.5% 17.5% 7.5% 100.0% Cluster 2 Count 8 11 5 1 25 % within Cluster Number of Case 32.0% 44.0% 20.0% 4.0% 100.0% Cluster 3 Count 5 10 4 0 19 % within Cluster Number of Case 26.3% 52.6% 21.1% .0% 100.0% Cluster 4 Count 11 11 5 0 27 % within Cluster Number of Case 40.7% 40.7% 18.5% .0% 100.0% Total Count 37 49 21 4 111 % within Cluster Number of Case 33.3% 44.1% 18.9% 3.6% 100.0%This shows that Cluster 1 is twice as likely as the usual student sample to go out more than 11 times per month. Cluster 2 follow the average levels of eating out per month, but eat out a little more Cluster 3 is a lot more likely to go out 3 – 5 times per month Cluster 4 never go out more than 11 times per month and are more likely than the average to be in the 0 – 2 times eating out per month group.Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 4.612(a) 9 .867 Likelihood Ratio 5.841 9 .756 Linear-by-Linear 1.075 1 .300 Association N of Valid Cases 111 a 6 cells (37.5%) have expected count less than 5. The minimum expected count is .68.Cluster Number of Case * Soup Purchase TypeWilliam Hanrahan 5 Case Processing SummaryCases Valid Missing Total N Percent N Percent N Percent Cluster Number of Case * Most Likely 111 100.0% 0 .0% 111 100.0% Soup PurchaseCluster Number of Case * Most Likely Soup Purchase CrosstabulationMost Likely Soup Purchase Canned Ambient Dried Chilled Fresh Total Cluster Cluster 1 Count 18 3 8 11 40 Number of % within Cluster Case Number of Case 45.0% 7.5% 20.0% 27.5% 100.0% Cluster 2 Count 13 3 3 6 25 % within Cluster Number of Case 52.0% 12.0% 12.0% 24.0% 100.0% Cluster 3 Count 11 2 1 5 19 % within Cluster Number of Case 57.9% 10.5% 5.3% 26.3% 100.0% Cluster 4 Count 13 1 4 9 27 % within Cluster Number of Case 48.1% 3.7% 14.8% 33.3% 100.0% Total Count 55 9 16 31 111 % within Cluster Number of Case 49.5% 8.1% 14.4% 27.9% 100.0%Cluster 1 students are more likely to purchase dried foods than the other clusters groups, Cluster 2 students are more into ambient food products with 64% of the sample choosing canned and other Ambient meals as the most likely soup purchase.Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 4.258(a) 9 .894 Likelihood Ratio 4.604 9 .867 Linear-by-Linear .003 1 .959 Association N of Valid Cases 111 a 7 cells (43.8%) have expected count less than 5. The minimum expected count is 1.54.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .192 .894 N of Valid Cases 111 a Not assuming the null hypothesis. b using the asymptotic standard error assuming the null hypothesis.Cluster Number of Case * Meal Purchase TypeCase Processing SummaryWilliam Hanrahan 5 Cases Valid Missing Total N Percent N Percent N Percent Cluster Number of Case * Most Likely 111 100.0% 0 .0% 111 100.0% Meal PurchaseCluster Number of Case * Most Likely Meal Purchase Cross tabulationMost Likely Meal Purchase Chilled Ambient Tinned Frozen Dried Total Cluster Cluster 1 Count 17 5 2 15 1 40 Number of % within Cluster Case Number of Case 42.5% 12.5% 5.0% 37.5% 2.5% 100.0% Cluster 2 Count 11 3 0 10 1 25 % within Cluster Number of Case 44.0% 12.0% .0% 40.0% 4.0% 100.0% Cluster 3 Count 9 3 1 6 0 19 % within Cluster Number of Case 47.4% 15.8% 5.3% 31.6% .0% 100.0% Cluster 4 Count 16 2 1 6 2 27 % within Cluster Number of Case 59.3% 7.4% 3.7% 22.2% 7.4% 100.0% Total Count 53 13 4 37 4 111 % within Cluster Number of Case 47.7% 11.7% 3.6% 33.3% 3.6% 100.0%Cluster 1 is most likely to purchase chilled meals, closely followed by frozen meals in their cluster Cluster 2 is most likely out of all the clusters to purchase frozen food, but they are also chilled meal fans Cluster 3 is most likely than the other clusters to purchase ambient foods, less likely to purchase frozen and dried meals Cluster 4 students are very likely to purchase Chilled meals with 60% of its members, they are less likely to purchase frozen foods but more likely to purchase dried. Chi-Square Tests Asymp. Sig. (2- Value df sided) Pearson Chi-Square 6.511(a) 12 .888 Likelihood Ratio 7.916 12 .792 Linear-by-Linear 1.105 1 .293 Association N of Valid Cases 111 a 12 cells (60.0%) have expected count less than 5. The minimum expected count is .68. Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .235 .888 N of Valid Cases 111 a Not assuming the null hypothesis. b using the asymptotic standard error assuming the null hypothesis. Cluster Number of Case * Average Weekly SpendCrosstabAverage Weekly Spend TotalWilliam Hanrahan 5 Up to £15 £16 - 30 More than £30 Cluster Cluster 1 Count 15 19 6 40 Number of % within Cluster Case Number of Case 37.5% 47.5% 15.0% 100.0% Cluster 2 Count 4 17 4 25 % within Cluster Number of Case 16.0% 68.0% 16.0% 100.0% Cluster 3 Count 1 14 4 19 % within Cluster Number of Case 5.3% 73.7% 21.1% 100.0% Cluster 4 Count 9 10 8 27 % within Cluster Number of Case 33.3% 37.0% 29.6% 100.0% Total Count 29 60 22 111 % within Cluster Number of Case 26.1% 54.1% 19.8% 100.0%Cluster 1 – Most likely spend = £16-30 Least – More than £30Cluster 2 – Most likely spend = £16-30 Least – Equally low result for other answersCluster 3 – Most likely spend - £16- 30 Least – 5% - Responded £0-15Cluster 4 – Equal Distribution between 3 LevelsIn the ‘up to £15’ average weekly spend category Cluster 1 students have the highest frequency; Cluster 3 students have the lowest frequency.In the ‘up to £16 - 30’ average weekly spend category Cluster 3 students have the highest frequency, with 73.7% of cluster 3 members spending this amount. Cluster 4 students are the lowest frequency in this category; just 37% of this cluster spends £16 – 30, around half the amount of cluster 3 students.In the ‘More than £30’ average weekly spend category, Cluster 4 students have the highest frequency of this group with 30% of the cluster 4 students responding to this, they are twice more likely to spend at this high level than Cluster 1.Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 12.661(a) 6 .049 Likelihood Ratio 13.965 6 .030William Hanrahan 5 Linear-by-Linear 2.020 1 .155 Association N of Valid Cases 111 a 3 cells (25.0%) have expected count less than 5. The minimum expected count is 3.77.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .320 .049 N of Valid Cases 111 a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.Cluster Number of Case * Budget CrosstabBudget Yes No Total Cluster Cluster 1 Count 19 21 40William Hanrahan 5 Number of % within Cluster Case Number of Case 47.5% 52.5% 100.0% Cluster 2 Count 8 17 25 % within Cluster Number of Case 32.0% 68.0% 100.0% Cluster 3 Count 8 11 19 % within Cluster Number of Case 42.1% 57.9% 100.0% Cluster 4 Count 13 14 27 % within Cluster Number of Case 48.1% 51.9% 100.0% Total Count 48 63 111 % within Cluster Number of Case 43.2% 56.8% 100.0%Cluster 1 – This is a pretty even split between cluster members who use and budget and those who don’t. Cluster 2 – Cluster 2 members are much more likely not to use a budget than any other cluster with almost 70% of this cluster not using a budget. Clusters 3 – Students in this cluster are less likely to use a budget with almost 60% of the group not using a budget. Cluster 4 - This is a pretty even split between cluster members who use and budget and those who don’t.Chi-Square Tests Asymp. Sig. (2- Value df sided) Pearson Chi-Square 1.858(a) 3 .602 Likelihood Ratio 1.893 3 .595 Linear-by-Linear .014 1 .907 Association N of Valid Cases 111 a 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.22.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .128 .602 N of Valid Cases 111 a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.Cluster Number of Case * Time spent preparation CrosstabTime spent preparation Total 0 - 15 16 - 30 31 - 45 46-59 0 - 15 Minutes Minutes Minutes Minutes 1 Hour + Minutes Cluster Cluster 1 Count 5 25 8 2 0 40William Hanrahan 5 Number of Case % within Cluster Number of Case 12.5% 62.5% 20.0% 5.0% .0% 100.0% Cluster 2 Count 2 14 7 1 1 25 % within Cluster Number of Case 8.0% 56.0% 28.0% 4.0% 4.0% 100.0% Cluster 3 Count 2 9 8 0 0 19 % within Cluster Number of Case 10.5% 47.4% 42.1% .0% .0% 100.0% Cluster 4 Count 3 10 13 1 0 27 % within Cluster Number of Case 11.1% 37.0% 48.1% 3.7% .0% 100.0% Total Count 12 58 36 4 1 111 % within Cluster Number of Case 10.8% 52.3% 32.4% 3.6% .9% 100.0%Cluster 1 members are more likely to spend 16 – 30 minutes preparing their meals, out of all the other clusters they are most likely to spend the least time preparing mealsCluster 4 are most likely to spend the longest time preparing meals, with Over 50% spending longer than 30 minutes preparing meals.Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 11.461(a) 12 .490 Likelihood Ratio 11.761 12 .465 Linear-by-Linear 1.791 1 .181 Association N of Valid Cases 111 a 12 cells (60.0%) have expected count less than 5. The minimum expected count is .17.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .306 .490 N of Valid Cases 111 a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.Cluster Number of Case * Special offer Attraction CrosstabSpecial offer Attraction Yes No Total Cluster Cluster 1 Count 38 2 40William Hanrahan 5 Number of % within Cluster Case Number of Case 95.0% 5.0% 100.0% Cluster 2 Count 24 1 25 % within Cluster Number of Case 96.0% 4.0% 100.0% Cluster 3 Count 17 2 19 % within Cluster Number of Case 89.5% 10.5% 100.0% Cluster 4 Count 27 0 27 % within Cluster Number of Case 100.0% .0% 100.0% Total Count 106 5 111 % within Cluster Number of Case 95.5% 4.5% 100.0%Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 2.913(a) 3 .405 Likelihood Ratio 3.707 3 .295 Linear-by-Linear .324 1 .569 Association N of Valid Cases 111 a 4 cells (50.0%) have expected count less than 5. The minimum expected count is .86.Cluster Number of Case * Spending HabitsCrosstabSpending Habits Yes No TotalWilliam Hanrahan 5 Cluster Cluster 1 Count 5 35 40 Number of % within Cluster Case Number of Case 12.5% 87.5% 100.0% Cluster 2 Count 4 21 25 % within Cluster Number of Case 16.0% 84.0% 100.0% Cluster 3 Count 1 18 19 % within Cluster 5.3% 94.7% 100.0% Number of Case Cluster 4 Count 8 19 27 % within Cluster Number of Case 29.6% 70.4% 100.0% Total Count 18 93 111 % within Cluster Number of Case 16.2% 83.8% 100.0%Chi-Square TestsAsymp. Sig. (2- Value df sided) Pearson Chi-Square 5.661(a) 3 .129 Likelihood Ratio 5.623 3 .131 Linear-by-Linear 2.051 1 .152 Association N of Valid Cases 111 a 3 cells (37.5%) have expected count less than 5. The minimum expected count is 3.08.Symmetric MeasuresValue Approx. Sig. Nominal by Nominal Contingency Coefficient .220 .129 N of Valid Cases 111 a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.5.2.2 Cross Tab Testing SummaryAssociative analysis is being used to determine where stable relationships exist between variables. William Hanrahan 5 Null Hypothesis is rejected – Gender and Student Cluster are associatedNull Hypothesis is rejected – Average weekly spend and student cluster are associatedNull Hypothesis is accepted – Soup type purchased and student cluster are independentNull Hypothesis is accepted – Budget and student cluster are independentNull Hypothesis is accepted – Preparation time and student cluster are independentNull Hypothesis is accepted – Special offer attraction and student cluster are independentNull Hypothesis is accepted – changing spending habits and student cluster are independentNull Hypothesis is accepted – How often eating out and student cluster are independentNull Hypothesis is accepted – Most likely meal and student cluster are independentThe Cross tabs analysis has proved very useful in determining two very interesting factors that shows that Gender and Average Weekly spend are both associated with the cluster that students are part of. So we can see from this hypothesis testing that the two key variables that influence the cluster membership are gender and average weekly spend. 5.2.3 Final Cluster CentresFinal Cluster Centres Cluster 1 2 3 4 Food Features - Locally Sourced 3 2 3 3 Food Features - Quality of Food 4 4 4 4 Food Features - Value for Money 4 4 4 4William Hanrahan 5 Food Features - Choice 4 4 4 4 Food Features - Packaging 2 2 2 2 Food Features - Ease of Storage 4 3 3 3 Food Features - Ease of Use 4 3 3 4 Food Features - Cooking Time 4 3 3 4 Food Features - Nutritional Value 4 4 4 4 Purchase Likelihood - Meatballs 2 3 3 3 Purchase Likelihood - Fellside 1 2 3 3 Purchase Likelihood - Chilli 1 2 3 3 Purchase Likelihood - Hotpot 1 2 3 2 Purchase Likelihood - Stew 1 2 3 2 Purchase Likelihood - Old Spot Pork 1 2 3 2 Purchase Likelihood - Rabbit in Leek 1 2 3 2 Purchase Likelihood - Stroganoff 1 2 3 2 Purchase Likelihood - Casserole 1 3 3 3 Purchase Likelihood - Velvet Porter 1 2 4 3 Soup Likelihood - Beef and Tomato 1 3 3 3 Soup Likelihood - Hum and Pea 2 4 3 3 Soup Likelihood - Parsnip 2 3 3 3 Soup Likelihood - Chicken 2 4 4 4 Soup Likelihood - Mushroom 2 2 3 3 Soup Likelihood - Tomato and Cheese 3 3 3 3 Regularly Buy Soup 2 2 1 1 Regular Buy Meal 1 1 1 1 New Product Marketing 7 8 8 2Distances between Final Cluster CentresCluster 1 2 3 4 1 4.893 6.402 6.500 2 4.893 3.623 5.743 3 6.402 3.623 6.040 4 6.500 5.743 6.040 5.2.4 Clusters Responses SummaryFood Features – Locally SourcedCluster 1 -Neither Cluster 2 –Unimportant Cluster 3 - Neither Cluster 4 – NeitherWilliam Hanrahan 5 Clusters don’t really alter much in this area; in general none of the student sample placed a high importance on locally sourced food. Cluster 2 were least interested in locally sourced food.Quality of FoodCluster 1 -Important Cluster 2 –Important Cluster 3 - Important Cluster 4 – ImportantAll student groups here are united in their importance rating of food qualityValue for MoneyCluster 1 -Important Cluster 2 –Important Cluster 3 - Important Cluster 4 – ImportantAll student groups here are united in their importance ratingChoiceCluster 1 -Important Cluster 2 –Important Cluster 3 - Important Cluster 4 – ImportantAll student groups here are united in their importance ratingPackagingCluster 1- Unimportant Cluster 2 – Unimportant Cluster 3 - Unimportant Cluster 4 – UnimportantAll student groups here are united in their importance ratingEase of StorageCluster 1 -ImportantWilliam Hanrahan 5 Cluster 2 - Neither Cluster 3 - Neither Cluster 4 – NeitherCluster 1 Place an importance on the ease of storage of this type of product, where clusters 2, 3, 4 all had a ‘Neither’ Important or UnimportantEase of UseCluster 1 -Important Cluster 2 –Neither Cluster 3 - Neither Cluster 4 – ImportantCluster 1 and 4 placed an important rating on ‘Ease of Use’ Cluster 2 and 3 placed ‘Neither’ as a responseCooking TimeCluster 1- Important Cluster 2- Neither Cluster 3- Neither Cluster 4 - ImportantCluster 1 and 4 placed an important rating on ‘Cooking Time’ Cluster 2 and 3 were given ‘Neither’ as a responseNutritional ValueCluster 1 -Important Cluster 2 –Important Cluster 3 - Important Cluster 4 – ImportantAll student groups here are united in their importance rating. Meal Purchase LikelihoodMeatball Purchase LikelihoodCluster 1 - Unlikely Cluster 2 – Neither Cluster 3 - Neither Cluster 4 – NeitherWilliam Hanrahan 5 Cluster 1 are the most unlikely group to purchase Meatballs Clusters 2, 3, 4 predominantly answered ‘Neither’ as a response Fellside Purchase LikelihoodCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – NeitherThis meal choice wasn’t favoured by the student group sampled, in particular Cluster 1 who responded with ‘Very unlikely’. Cluster 2 responded ‘Unlikely’, while 3, 4 responded ‘Neither’Beef Chilli Con CarneCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – NeitherCumbrian Lamb HotpotCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – UnlikelyMutton StewCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – UnlikelyOld Spot PorkCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – UnlikelyRabbit in LeekWilliam Hanrahan 5 Cluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – UnlikelyStroganoffCluster 1 – Very Unlikely Cluster 2 –Unlikely Cluster 3 - Neither Cluster 4 – UnlikelyCasseroleCluster 1 – Very Unlikely Cluster 2 –Neither Cluster 3 - Neither Cluster 4 – NeitherVelvet PorterCluster 1 - Very Unlikely Cluster 2 –Unlikely Cluster 3 - Likely Cluster 4 – NeitherThis is an interesting selection as all clusters gave a different response for this meal choice, obviously a controversial choice with responses ranging from Very Unlikely to Likely. Cluster 1 responded with Very Unlikely, Cluster 2 were Unlikely Cluster 4 contained students mostly answering neither, While cluster 3 contained students who mostly answered likely.SoupsBeef and TomatoCluster 1 - Very Unlikely Cluster 2 –NeitherWilliam Hanrahan 5 Cluster 3 - Neither Cluster 4 – NeitherCluster 1 students were ‘Very Unlikely’ to purchase this soup, while Cluster 2, 3, 4 Students didn’t really have a preference, answering ‘Neither’.Ham and PeaCluster 1 -Unlikely Cluster 2 –Likely Cluster 3 - Neither Cluster 4 – NeitherParsnipCluster 1 -Unlikely Cluster 2 –Neither Cluster 3 - Neither Cluster 4 – NeitherChickenCluster 1 -Unlikely Cluster 2 –Likely Cluster 3 - Likely Cluster 4 – LikelyMushroomCluster 1 - Unlikely Cluster 2 – Unlikely Cluster 3 - Neither Cluster 4 – NeitherTomato and CheeseCluster 1 -Neither Cluster 2 – Neither Cluster 3 - Neither Cluster 4 – NeitherWilliam Hanrahan 5 Regularly buy SoupCluster 1 -No Cluster 2 - No Cluster 3 - Yes Cluster 4 – YesClusters 1 and 2 aren’t regular Soup purchasers, this should be remembered when it comes to the marketing implications as suggestions as to how this purchasing behaviour could be altered if necessary. Clusters 3 and 4 are mostly respondents who regularly buy soup.Regularly buy Convenience MealsCluster 1 – Yes Cluster 2 – Yes Cluster 3 - Yes Cluster 4 – YesAll the following clusters contained mainly ‘Yes’ responses, showing that Convenience meals are regularly bought predominantly by all the student clusters.Methods of Product MarketingCluster 1 – In Store Cluster 2 – Free Samples Cluster 3 – Free Samples Cluster 4 – TVCluster 1 respondents put ‘In Store’ as the marketing method that would be most appropriate to target themselves. Cluster 2 and 3 both identified ‘Free Samples’ as being a key method of how to be targeted. Cluster 4 said that TV would be the most effective way to target them for new products. These are interesting results as it will result in interesting marketing implications as potentially these groups need to be targeted in different ways.5.2.5 Cluster ProfilesWilliam Hanrahan 5 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Size (%) 37 22 17 24 Female Genders 75% Equal Male 80% Equal Eat out How often eating out Most - - Eat out least Soup type preference Dried Canned Canned Chilled Fresh Meal type preference Chilled Frozen Ambient Chilled Around More than Average Spend £15 £16 - £30 £16 - £30 £30 Around Average Time (minutes) 16-30 16-30 30 31 - 45 Credit Crunch effecting spending 12.5% Yes 16% Yes 5% Yes 30% Yes Special Offer Attraction Yes Yes Yes 100% YesLocally Sourced Food Unimportant Quality of Food Important Important Important Important Value for Money Important Important Important Important Choice Important Important Important Important Ease of Use Important Ease of Storage Important Cooking Time Important Important Nutritional Value Important Important Important Important Attitude towards meal Very purchase Unlikely Unlikely Likely Likely Velvet Porter, Velvet Casserole, Particular meals - - Porter Beef Chilli C.C Very Not regular Attitude towards soups Unlikely user Likely Likely Ham and Particular soup - Pea Chicken Chicken Delia Smith 21st and Jamie Century Pot Noodle Male Oliver Cluster Name: Woman Student Foodie wannabe 5.3 Cluster Summary and Recommendations Cluster 1- (21ST Century Women) are obviously a very female dominated group and they don’t seem to be a likely target segment, they didn’t respond strongly to theWilliam Hanrahan 5 current meal choice, giving a ‘very unlikely’ response to most of The Tanfield FoodGroup’s current Soup and Meal options. This group was most interested in the ‘Ease of storage’; they rated this as important, demonstrating how females care more about the shape of product the aesthetics than most males. They spend less money on food at the home and choose to go out more and spend their budgets on meals out. Although quality, value for money were seen as important factors the recommendation from looking at Cluster 1, is to avoid targeting this group. This group seem to be the new generation of females preferring going out and spending money on what there perceive to be more important, living the ‘Sex and the City’ lifestyle.  Cluster 2 (Pot Noodle Students) are a mixed sex group of students, with seemingly lower standards of taste preferring Canned soups and Frozen meals, ‘the typical student’ , they responded that Locally sourced food was unimportant to them and responded ‘Unlikely’ to most of the food offered, expect Ham and Pea which they were responded as a ‘likely purchase’. I don’t see this group as a likely target, they go out for meals occasionally and spend the average time cooking and monthly spend between £16 – 30 pounds. Cluster 3 (Male Foodies) are a very male dominated group, spending longer on preparing meals than clusters 1 and 2 demonstrating more interest in cooking, they seem not to be affected at all by the credit crunch, with only 5% saying they hadWilliam Hanrahan 5 changed spending habits, and they were attracted by special offers. Quality of Food,Value for money and choice were all important factors to this group, they were impressed with the meals on offer by The Tanfield Food Group, and in particular theVelvet Porter meal. They felt the same about Soups, as regular purchasers they favoured the Chicken soup. After looking at this group in depth, this group seems like an ideal target, they were the most likely group to purchase Ambient meals, but still don’t seem to have much knowledge about the products offered by TheTanfield Food Group. As the minority group of 17% of students this segment is still large enough to be viable as part of the 1.9 million students (Ness, 2002) in the UK.This small segment has been identified as ‘Aspiring males’ – those males who enjoy good wholesome food, likely to play sports and are taking a keener interest in food, thanks to a revival in cooking from some strong males figures as Hugh FernleyWhittingstall and Gordon Ramsey. Cluster 4 (Jamie Oliver & Delia Wanabees’) contain 24% of the student sample, and is of equal distribution of males and females, they have the highest average spend at over £30 a month, suggesting they like to purchase quality food, although30% of its students have been affected by the credit crunch, suggesting that they may need to alter their higher levels of spending, as a result they are very influenced by promotions, with 100% of the segment admitting to be influenced by special offers. To them, Quality of food, value for money, nutritional value and choice are all important, while they may be quite a busy set of consumers, they still choose to allocate a lot of time to cooking, spending an average time cooking of 31William Hanrahan 5 – 45 minutes, suggesting they really enjoy cooking and enjoy good food, however when looking at convenience foods they placed the highest importance of all the groups on ease of use and cooking time, suggesting they when they want to take a break from the toil of their usual meals with long preparation times, they want something as easy as possible. They eat out least, probably due to the fact that they realise they can cook better meals in their homes, and for that reason choose to spend the money they save on other social activities, or simply on better ingredients in their own cooking. However it shows that on the occasion that they do want a night off, The Tanfield Food Groups range could be the ideal option.When purchasing convenience food they usually go for Chilled foods, but placed a‘likely’ preference to purchasing meals offered by ‘The Tanfield Food Group’. For the meals they chose Velvet Porter, Casserole, Beef Chilli Con Carne, and Chicken soup. It seems acceptable to class this group as ‘True Foodies’, probably from higher socioeconomic backgrounds.The researcher simply needs to think about the diverse range of students that he has come into contact with to make these summarised groups, although they may be slightly stereotypical, much of what has been said is backed up through the cluster response summary. However, some imagination has been used to add a creative element to fill in the gaps and create a clearer picture for the reader.6.0 Discussion6.1 IntroductionWilliam Hanrahan 5 The research has now been completed, and this has allowed the creation of recommendations to be provided for The Tanfield Food Group. The final chapters are structured into three main sections; the following section addresses each of the five primary objectives in turn, drawing upon primary and secondary data to satisfy each of the objectives. The section provides a summary of the most noteworthy findings of the report with the report concluding by highlighting areas where further research is recommended.6.2 Summary of Key ResultsA key objective of marketing is to define market segments so that the product can be differentiated from rival products to serve the needs of a given segment in the best way possible. In this study, Newcastle University student’s perceptions and preferences for convenience food using cluster analysis were explored. This analytical technique was particularly useful for segmenting the student consumer.The study suggests that student clusters do exist, four equally sized segments emerged from the sample: ‘ Male Foodies’, ‘Delia Smith and Jamie Oliver wannabes’, ‘Pot NoodleStudents’ and ‘21st Century Women’. These are the researchers personal interpretations of the clusters identified. In terms of suitability for The Tanfield Food Group meals and soups, the market review identified the need for niche food consumers and Male Foodies, DeliaSmith and Jamie Oliver wannabe’s seem to be the ideal student food groups that fit into this niche. Previous to this study little was known about student groups and although segmentation had occurred, this had only been done on financial methods, but not relating to their preferences and attitudes towards convenience food, in particular the ambient food market.William Hanrahan 5 Hypothesis testing on the cross tabulations revealed that the two key attributes of Gender and Average weekly spend were what made the student cluster different from each other, explaining why clusters emerged that either ranged from low weekly spending on food to high weekly spending on food and through the in depth questions it enabled the identification of particular meals that The Tanfield Food Group could now choose to focus their marketing on within the student target.The key question can now be answered, is there a market for ambient food for students?Yes, It seems so, throughout the research it was clear that a segment of students were willing to purchase convenience food and pay a premium price for it, the question was ‘how big was this segment?’ The research identified the segment to be larger than anticipated, with around 40% of the Newcastle student sample falling into the ‘Male Foodie’ and ‘Delia and Jamie Oliver wanabee’ groups. The implication for marketers is that the student convenience market cannot be seen as a whole, as clear student segments exist when linked to convenience food shopping. 6.3 Fulfilment of ObjectivesWilliam Hanrahan 5 1) Provide a market overview for the Convenience Meal and Soup Market in the UK, to establish the reasoning behind the increasing consumption of convenience food and in particular ambient foods, giving strategic marketing implications based on the findings.The market review provided the researcher with strategic insights into the convenience and ambient food market, with recommendations to suggest new niche markets which led to proposal of student market. Mintel databases on Ambient Ready Meals, British Lifestyles, Chilled and Frozen Ready Meals, Soup and Student lifestyles were used which provided lots of information into their markets and enabled a broad market overview.2) Give a detailed analysis of the vital factors of the key literature considered to be most important in shopping behaviour, student consumers, British/regional food and new product marketing.A comprehensive reading list was used, containing insightful articles from the Journal ofMarketing and British Food Journal, based on the topics of shopper behaviour, student consumers, British food, cluster analysis and new product marketing. Some articles were very useful especially those which conducted primary research collecting shoppers opinions, the methods used were closely followed in this research. Literature on the subject of Cluster analysis showed how it can be used and it seemed to be the ideal research method to segment the student sample.William Hanrahan 5 3) Based on literature recommendations, conduct a questionnaire to obtain student responses, segment the sample into groups which share common characteristics, based on attitudes towards food and consumption of convenience food.A questionnaire was conducted and yielded a good set of results, after cluster analysis was used and cross tabulated with some attributes, it was seen that the clusters were linked to gender and levels of spending on shopping. Final cluster centres were created which allowed creation of cluster profiles, these clusters differed by attitudes towards foods and four equally sized clusters were identified.4) Provide Implications for Tanfield Food on how to market to students more effectively. Identify the key segments that exist for the products and recommend marketing strategies to improve consumptionIt was clear from the results that the student market is made up of clear market segments, once analysis had been completed, an executive summary was created for Keith Gill,Founder of Tanfield food, specifically focused on the Tanfield Food Group brand, marketing implications were provided. The researcher is happy that the objectives set out at the beginning of this study were fully carried out to the best of his ability and he was pleased with the outcome of the study, feeling some interesting insights into student segments had been gained.William Hanrahan 5 7.0 Conclusion7.1 Limitations of the StudyThis study has certain limitations some of which can be viewed as future research items. Although a sufficiently large sample from the University was used in the study, the samples weren’t considered to be representative of the overall British student consumer. They represent Newcastle University student consumer’ perceptions only, a more representative sample might consider a greater selection of North East universities for example Northumbria, Teesside, Sunderland and Durham Universities, this would be a good representation of North East university students, it could then consider the differences between the universities in detail.7.2 Suggestions for Future Research7.2.1 Improving Response RateA larger sample of responses for the questionnaire would have resulted more reliable results, frustratingly, after the data collection was completed the researcher realised many ways which could have resulted in more respondents, the most effective seemed to be the use of a small note attached to each individual computer screen in the library computer room, asking the student sat at the computer for a few minutes of their time, speaking to the students who used this method said it was successful.7.2.2 Additional QuestionsThe wide range of questions yielded a good set of results which allowed for easy data handling and made it simpler to see the variations in cluster groups, it would be interesting to use more open ended questions such as ‘Please state your favourite meal’. Questions William Hanrahan 5 like this could have been useful for providing The Tanfield Food Group with new meal recommendations.7.2.3 Multi-Dimensional ScalingMultidimensional scaling can produce a visual representation of the subjective dimensions that are not directly shown in the data. By showing the objects visually on a map it can be easily used by anyone to associate close together objects as similar or close in terms of preference. The marketing applications of this type of quantitative analysis include brand/product positioning and new product development. Useful insights can be gained from the output of this type of analysis. It could have been used to see how consumers perceive The Tanfield Food Group products within the market in relation to their rivals.7.2.4 Focus GroupsThe next stage of this study would have been to contact those student members who responded they were willing to be part of a focus group, and who were assigned to the niche student clusters, groups 3 and 4. It would have been interesting to arrange two focus groups based of each cluster group, then discuss the current product range and get suggestions from them for meals they would like to purchase in this food format. Subject areas like packaging and price would be interesting, the results from this study could be fed back to them and it would be worthwhile to confirm the conclusions to find their opinions on this. Students placed British cuisine as fourth place as their preferred choice, with Italian being a very popular choice. Future focus groups could look at finding some Italian meal options and use this as a point of discussion and comparison against their current product lines.William Hanrahan 5 7.3 HypothesisThe hypothesis in the first section was accepted, as expected it was possible to identify suitable student groups to The Tanfield Food Group and the analysis was used to back up to findings sent to the Director, Keith Gill of Tanfield Food.William Hanrahan 5 8.0 Study ReferencesBagozzi, R. (1994). Principle of Marketing Research, Oxford, UK: Blackwell.Baltas, G. (1997). Determinants of store brand choice: a behavioural analysis. Journal of Product & Brand Management, Vol.6, No.5, pp. 315-324.Bárcenas, P., Pérez-Elortondo,F., Salmerón, J. And Albisu. (1998). Recalled preference of Spanish consumers for smoked food. Journal of Nutrition and Food Science, No.6, November/December, pp.338-342.Bellenger, D. And Korgaonkar. (1980). Profiling the Recreational Shopper. Journal of Retailing, Vol.56, No.3, pp.77-92.Bergadaa, M. (1990). The Role of Time in the Action of the Consumer. Journal of Consumer Research, Vol.17,December, pp.289-302.Buttle, F. And Coates. (1980). Shopping Motives. The Service Industries Journal, pp.71-81.Chettamrongchai, P. And Davies, G. (2000). Segmenting the market for food shoppers using attitudes to shopping and to time. British Food Journal, Vol.102, No.2, pp.81-101.Cooper, L. (2000) Strategic Marketing Planning for Radically New Products. Journal of Marketing, Vol.64, January, pp. 1-16.Davies, G. And Madran, C. (1997). Time, food shopping and food preparation: some attitudinal linkages. British Food Journal, pp.80-88.DC West, JB Ford, E Ibrahim (2006) Strategic marketing: creating competitive advantage: Oxford University Press.William Hanrahan 5 Doyle, P. And Fenwick, I. (1974-1975). How Store Image Affects Shopping Habits in Grocery Chains. Journal of Retailing, Vol.50, No.4, Winter, pp.39-52.Fitch, D. (2004). Measuring convenience: Scots’ perceptions of local food and retail provision. International Journal of Retail & Distribution Management, Vol.32, No.2, pp. 100 – 108.Gardner, B. And Levy, S. (1955). The Product and the Brand. Harvard Business Review, March – April, pp.33 – 38.Goldsmith, R., Flynn, L. And Goldsmith, E. (2003). Innovative Consumers and Market Mavens. Journal of Marketing, Fall, pp.54 – 64.Groves, A. (2001). Authentic British food products: a review of consumer perceptions. International Journal of Consumer Studies, Vol.25, No.3, pp.246-254.Iyer, E. (1989). Unplanned Purchasing: Knowledge of Shopping environment and time pressure. Journal of Retailing, Vol.65, No.1, pp.40-57.Jankowicz, A.D (2005) Business Research Projects, Fourth edition, Thomson learning.Kara, A,. Kaynak, E. And Kucukemiroglu, O. (1997). Marketing strategies for fast-food restaurants: a customer view. British Food Journal, pp. 318-324.Kover, A. (2008). Qual vs Quant... again!. International Journal of Advertising, Vol 27, No. 4, pp.663-665.Kuzensof, S., Tregar, A. and Moxey, A. (1999). Regional Foods: A consumer perspective. British Food Journal.William Hanrahan 5 Lautman, M., Percy, L. And Kordish, G. (1978). Campaigns from Multidimensional Scaling. Journal of Advertising Research, Vol.18, No.3, June, pp.35-40. Lonial, S., Menezes,D and Zaim, S. (2000). Journal of Economic and Social Research, Vol.2, No.2, pp.19-37.Mann, T., Reeve, W. And Creed, P. (2002). A Comparison of the acceptability to student consumers of three food products retailed at three ‘quality’ levels. Journal of Food Service Technology, Vol.2, pp.13-18.ME Porter. (1998) Competitive Advantage: Creating and Sustaining Superior Performance 1st Ed: Free Press.Mintel (2004). Ambient Ready Meals - UK, Mintel Marketing Intelligence, April.Mintel (2007). British Lifestyles, Mintel Marketing Intelligence, March.Mintel (2008). Chilled and Frozen Ready Meals - UK, Mintel Marketing Intelligence, May.Mintel (2008). Soup - UK, Mintel Marketing Intelligence, May.Mintel (1999). Student lifestyles, Mintel Marketing Intelligence, April.Moschis, G. And Churchill Jr, G. (1979). An Analysis of the Adolescent Consumer. Journal of Marketing, Summer, pp.40 – 48.Ness, M., Gorton, M. And Kuznesof, S. (2002). The student food shopper. British Food Journal, Vol.104, No.7, pp. 506 – 525.Nijssen, E. And Lieshout, K. (1995). Awareness, use and effectiveness of models and methods for new product development. European Journal of Marketing, Vol.29, No.10, pp.27-44.William Hanrahan 5 Reardon, D (2006) Doing your undergraduate project: first edition, Sage Publications LtdRoberts, M. And Wortzel, L. (1979). New Life-Style determinants of Women’s food shopping behaviour, Journal of Marketing, Summer, pp.28-39.Sethi, R. (2000). New Product Quality and Product Development Teams. Journal of Marketing, April, pp.1-14.Singston, R. (1975). Multidimensional Scaling Analysis of Store Image and Shopping Behaviour. Journal of Retailing, Vol.51, No. 2, pp. 38-52.Wandel, M. (1997). Food labelling from a consumer perspective. British Food Journal, pp.212-219.Warde, A. (1999). Convenience food: space and timing. British Food Journal, Vol.101, No.7, pp.518-527.Used Newcastle University dissertations for reference:Name Title You are what you eat. Students attitudes towards healthy Boffey, I. eating Own - brand carbonated soft drinks: To buy or not to buy. Pantazi, A-M. How Greek and UK students make the decision. Allen, P. Examination of the market potential for Brussels sprouts. An analysis of the attitudinal and behavioural characteristics of the student food shopper based on store image, Dillon, R. satisfaction and loyalty. Dobson, S. The student shopper: Attitudes to food shopping and time. Focus Group FG13NI – WHOLEHEART – 26th July 2007 - Sharon KuznesofWilliam Hanrahan 5 8.1 Websites Used Webster's New Millennium™ Dictionary of English, Preview Edition (v 0.9.7). Retrieved November 12, 2008, from Dictionary.com website: http://dictionary.reference.com/browse/ambient food ME Porter (no date) www.quickmba.com Definition of Porters Generic Strategies, Figure 1, Figure 2 - Date accessed – [11.11.08] Look What We Found Website - http://www.lookwhatwefound.co.uk/ Accessed on 25.10.08 http://www.1000ventures.com Accessed on 25.10.08 Learning curve definition and figure 4, taken from Phil Dawsons lecture notes http://www.1000ventures.com/business_guide/crosscuttings/customer_vp.html - Customer value proposition Fame database for most recent accounts of Baxter’s and The Tanfield Food Company (Look What We Found) http://www.sungard.com/fame Love Food, Hate Waste Campaign for facts on food waste. http://www.gateshead.gov.uk/Environment%20and %20Waste/Waste/food/facts.aspxWilliam Hanrahan 5 9.0 Appendix - Literature SummaryWilliam Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 William Hanrahan 5 9.2 Appendix 2 SPSS Output Descriptive Statistics Fig 1.0 Descriptive Statistics Descriptive StatisticsN Mean Std. Deviation Food Features - Locally Sourced 111 2.55 1.068 Food Features - Quality of Food 111 4.16 .708 Food Features - Value for Money 111 4.27 .750 Food Features - Choice 111 3.78 .744 Food Features - Packaging 111 2.36 .951Food Features - Ease of Storage 111 3.39 .965 Food Features - Ease of Use 111 3.48 .862 Food Features - Cooking Time 111 3.50 .913 Food Features - Nutritional Value 111 4.04 .863 Brand Info - Look What We Found 111 1.36 .772 Brand Info - New Covent Garden 111 2.78 1.467 Brand Info - Seeds of Change 111 1.75 1.004 Purchase Likelihood - Meatballs 111 2.42 1.195 Purchase Likelihood - Fellside 111 1.97 1.013 Purchase Likelihood - Chilli 111 2.06 1.038Purchase Likelihood - Hotpot 111 2.07 1.158 Purchase Likelihood - Stew 111 1.85 1.020Purchase Likelihood - Old Spot Pork 111 2.01 1.083 Purchase Likelihood - Rabbit in Leek 111 1.96 1.159 Purchase Likelihood - Stroganoff 111 2.08 1.222 Purchase Likelihood - Casserole 111 2.41 1.194 Purchase Likelihood - Velvet Porter 111 2.36 1.313William Hanrahan 5 Soup Likelihood - Beef and Tomato 111 2.48 1.299 Soup Likelihood - Hum and Pea 111 2.55 1.340 Soup Likelihood - Parsnip 111 2.50 1.348 Soup Likelihood - Chicken 111 3.23 1.255 Soup Likelihood - Mushroom 111 2.27 1.279 Soup Likelihood - Tomato and Cheese 111 3.05 1.224 Valid N (listwise) 111 N Minimum Maximum Food Features - Locally Sourced 111 1 5 Food Features - Quality of Food 111 2 5 Food Features - Value for Money 111 1 5 Food Features - Choice 111 1 5 Food Features - Packaging 111 1 5 Food Features - Ease of Storage 111 1 5 Food Features - Ease of Use 111 1 5 Food Features - Cooking Time 111 1 5 Food Features - Nutritional Value 111 1 5 Brand Info - Look What We Found 111 1 4 Brand Info - New Covent Garden 111 1 5 Brand Info - Seeds of Change 111 1 4 Purchase Likelihood - Meatballs 111 1 5 Purchase Likelihood - Fellside 111 1 5 Purchase Likelihood - Chilli 111 1 4 Purchase Likelihood - Hotpot 111 1 5 Purchase Likelihood - Stew 111 1 4 Purchase Likelihood - Old Spot Pork 111 1 5 Purchase Likelihood - Rabbit in Leek 111 1 5 Purchase Likelihood - Stroganoff 111 1 5William Hanrahan 5 Purchase Likelihood - Casserole 111 1 5 Purchase Likelihood - Velvet Porter 111 1 5 Soup Likelihood - Beef and Tomato 111 1 5 Soup Likelihood - Hum and Pea 111 1 5 Soup Likelihood - Parsnip 111 1 5 Soup Likelihood - Chicken 111 1 5 Soup Likelihood - Mushroom 111 1 5 Soup Likelihood - Tomato and Cheese 111 1 5 Valid N (listwise) 111 Remaining DescriptivesDescriptive Analysis ResultsFull Time UndergradCumulative Frequency Percent Valid Percent Percent Valid Yes 111 100.0 100.0 100.0Own MealsCumulative Frequency Percent Valid Percent Percent Valid Yes 111 100.0 100.0 100.0FacultyCumulative Frequency Percent Valid Percent Percent Valid HaSS 65 58.6 58.6 58.6 Medical 18 16.2 16.2 74.8 SAgE 28 25.2 25.2 100.0 Total 111 100.0 100.0 Brand Info - New Covent Garden Cumulative Frequency Percent Valid Percent Percent Valid Never Heard of 36 32.4 32.4 32.4 Have heard, Not Sure Why 11 9.9 9.9 42.3 Have heard, know products 19 17.1 17.1 59.5 Have heard, tried products 31 27.9 27.9 87.4 have heard and 14 12.6 12.6 100.0 regularly buyWilliam Hanrahan 5 Total 111 100.0 100.0 The student sample had a little more knowledge about the ‘New Covent Garden’ range of chilled food, with 57.6% having at least heard of the Brand name.Brand Info - Seeds of ChangeCumulative Frequency Percent Valid Percent Percent Valid Never Heard of 64 57.7 57.7 57.7 Have heard, Not Sure Why 20 18.0 18.0 75.7 Have heard, know products 18 16.2 16.2 91.9 Have heard, tried products 9 8.1 8.1 100.0 Total 111 100.0 100.0 Seeds of change, a similar brand that also produce ambient soups are also relatively unknown, with almost 60% having never heard of the Seeds of Change brand.Usual Shop - AldiCumulative Frequency Percent Valid Percent Percent Valid Yes 10 9.0 9.0 9.0 No 101 91.0 91.0 100.0 Total 111 100.0 100.0 9% of students listed Aldi as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - AsdaCumulative Frequency Percent Valid Percent Percent Valid Yes 53 47.7 47.7 47.7 No 58 52.3 52.3 100.0 Total 111 100.0 100.0 This was nearly 50/50, 47.7% of students listed Asda as one of their 3 most common shopping destinations.Usual Shop - Co-OpCumulative Frequency Percent Valid Percent Percent Valid Yes 22 19.8 19.8 19.8 No 89 80.2 80.2 100.0 Total 111 100.0 100.0 20% of students listed Co-op as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.William Hanrahan 5 Usual Shop - CostcoCumulative Frequency Percent Valid Percent Percent Valid Yes 2 1.8 1.8 1.8 No 109 98.2 98.2 100.0 Total 111 100.0 100.0 1.8% of students listed Costco as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - FarmfoodsCumulative Frequency Percent Valid Percent Percent Valid Yes 2 1.8 1.8 1.8 No 109 98.2 98.2 100.0 Total 111 100.0 100.0 1.8% of students listed Farmfoods as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - IcelandCumulative Frequency Percent Valid Percent Percent Valid Yes 8 7.2 7.2 7.2 No 103 92.8 92.8 100.0 Total 111 100.0 100.0 7.2% of students listed Iceland as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - LidlCumulative Frequency Percent Valid Percent Percent Valid Yes 5 4.5 4.5 4.5 No 106 95.5 95.5 100.0 Total 111 100.0 100.0 4.5% of students listed Lidl as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - LondisWilliam Hanrahan 5 Cumulative Frequency Percent Valid Percent Percent Valid Yes 5 4.5 4.5 4.5 No 106 95.5 95.5 100.0 Total 111 100.0 100.0 4.5% of students listed Londis as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - NettoCumulative Frequency Percent Valid Percent Percent Valid No 111 100.0 100.0 100.00% of students listed Netto as one of their 3 most common shopping destinations. This suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - SomerfieldCumulative Frequency Percent Valid Percent Percent Valid Yes 3 2.7 2.7 2.7 No 108 97.3 97.3 100.0 Total 111 100.0 100.0 2.7% of students listed Somerfield as one of their 3 most common shopping destinations. This is quite low and suggests students in Newcastle don’t tend to shop here regularly.Usual Shop - SPARCumulative Frequency Percent Valid Percent Percent Valid Yes 1 .9 .9 .9 No 110 99.1 99.1 100.0 Total 111 100.0 100.0 0.9% of students listed SPAR as one of their 3 most common shopping destinations. This is low and suggests students in Newcastle don’t tend to shop here regularly.Appendix – 8 Remaining Cross-TabsWilliam Hanrahan 5 The hypotheses are:H0: Average Weekly spend and student cluster are independent H1: Average Weekly spend and student cluster are associatedThe value of 0.049 is less than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is rejected – Average weekly spend and student cluster are associatedThe hypotheses are:H0: Soup type purchased and student cluster are independent H1: Soup type purchased and student cluster are associatedThe value of 0.894 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – Soup type purchased and student cluster are independentThe hypotheses are:H0: Budget and student cluster are independent H1: Budget and student cluster are associatedThe value of 0.602 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – Budget and student cluster are independentThe hypotheses are:H0: Preparation time and student cluster are independent H1: Preparation time and student cluster are associatedThe value of 0.490 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – Preparation time and student cluster are independentWilliam Hanrahan 5 The hypotheses are:H0: Special offer attraction and student cluster are independent H1: Special offer attraction and student cluster are associatedThe value of 0.405 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – Special offer attraction and student cluster are independentThe hypotheses are:H0: Changing Spending habits and student cluster is Independent H1: Changing Spending habits and student cluster are associatedThe value of 0.129 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – changing spending habits and student cluster are independentThe hypotheses are:H0: How often eating out and student cluster are independent H1: How often eating out and student cluster are associatedThe value of 0.867 is more than the Significance Level of 0.050 or 5 per cent.Null Hypothesis is accepted – How often eating out and student cluster are independentThe hypotheses are:H0: Most likely meal and student cluster are independent H1: Most likely meal and student cluster are associatedThe value of 0.888 is more than the Significance Level of 0.050 or 5 per cent.William Hanrahan 5 Null Hypothesis is accepted – Most likely meal and student cluster are independent9.3 Appendix 3 SPSS Cluster OutputIteration History(a)Change in Cluster Centers Iteration 1 2 3 4 1 4.236 6.011 5.927 5.130 2 .453 .805 .916 1.092 3 .320 .535 .357 1.055 4 .241 .381 .000 .416 5 .309 .000 .000 .515 6 .250 .000 .000 .360 7 .000 .000 .000 .000 A Convergence achieved due to no or small change in cluster centres. The maximum absolute coordinate change for any centre is .000. The current iteration is 7. The minimum distance between initial centres is 10.770.Cluster MembershipCase Number Cluster Distance 1 4 5.204 2 3 4.997 3 4 4.047 4 4 6.404 5 4 5.995 6 4 7.296 7 2 3.975 8 3 2.804 9 4 6.840 10 2 5.510 11 2 3.950 12 4 5.742 13 4 5.282 14 1 4.556 15 1 3.280 16 4 5.873 17 4 3.518 18 4 5.809 19 2 3.758 20 1 6.273 21 2 3.661 22 1 6.149 23 2 4.015 24 1 3.982William Hanrahan 5 25 1 4.220 26 3 4.550 27 2 3.388 28 4 5.575 29 4 3.571 30 3 4.693 31 1 5.105 32 2 4.395 33 1 3.742 34 1 5.021 35 1 4.539 36 1 4.490 37 1 3.906 38 1 4.696 39 1 5.984 40 1 3.736 41 3 4.288 42 3 3.565 43 4 6.319 44 2 6.896 45 3 4.608 46 1 4.118 47 4 4.226 48 1 4.905 49 1 4.450 50 3 5.075 51 4 5.444 52 4 7.056 53 2 4.907 54 2 4.874 55 2 6.502 56 2 4.512 57 1 5.649 58 3 6.454 59 3 5.188 60 1 3.815 61 1 3.668 62 2 5.393 63 2 4.783 64 3 3.821 65 4 4.368 66 2 6.603 67 1 4.853 68 3 4.614 69 2 5.192 70 1 5.320 71 3 4.726 72 1 4.843 73 2 5.657 74 1 3.988William Hanrahan 5 75 2 5.340 76 1 3.179 77 1 3.465 78 2 3.784 79 3 3.320 80 1 6.189 81 1 3.179 82 1 4.290 83 1 3.572 84 2 6.381 85 1 4.013 86 2 4.386 87 1 3.689 88 4 5.464 89 4 4.398 90 1 5.182 91 1 3.982 92 1 4.081 93 1 5.259 94 3 5.244 95 4 5.911 96 3 6.647 97 3 3.780 98 4 6.219 99 4 5.067 100 1 4.296 101 2 6.437 102 3 5.484 103 1 4.100 104 4 6.135 105 3 3.475 106 2 4.391 107 4 5.243 108 1 4.966 109 4 6.004 110 4 4.907 111 2 5.265Number of Cases in each ClusterCluster 1 40.000 2 25.000 3 19.000 4 27.000 Valid 111.000 Missing .000William Hanrahan 5 ANOVA Cluster Error Mean Square df Mean Square df F Sig. Food Features - Locally Sourced 7.556 3 .961 107 7.863 .000 Food Features - Quality of Food .495 3 .501 107 .989 .401 Food Features - Value for Money .588 3 .562 107 1.047 .375Food Features - Choice .714 3 .548 107 1.303 .277 Food Features - Packaging .647 3 .913 107 .709 .548Food Features - Ease of Storage 1.501 3 .914 107 1.642 .184 Food Features - Ease of Use .897 3 .738 107 1.215 .308Food Features - Cooking Time .682 3 .838 107 .813 .489Food Features - Nutritional Value .267 3 .758 107 .352 .788 Purchase Likelihood - Meatballs 13.680 3 1.085 107 12.612 .000 Purchase Likelihood - Fellside 13.345 3 .681 107 19.591 .000Purchase Likelihood - Chilli 10.012 3 .827 107 12.101 .000Purchase Likelihood - Hotpot 15.237 3 .951 107 16.030 .000Purchase Likelihood - Stew 15.570 3 .633 107 24.614 .000Purchase Likelihood - Old Spot Pork 15.643 3 .767 107 20.397 .000 Purchase Likelihood - Rabbit in Leek 21.003 3 .793 107 26.486 .000 Purchase Likelihood - Stroganoff 13.582 3 1.154 107 11.765 .000 Purchase Likelihood - Casserole 20.164 3 .901 107 22.371 .000 Purchase Likelihood - Velvet Porter 32.298 3 .866 107 37.283 .000 Soup Likelihood - Beef and Tomato 24.771 3 1.041 107 23.796 .000 Soup Likelihood - Hum and Pea 26.175 3 1.112 107 23.545 .000Soup Likelihood - Parsnip 3.795 3 1.760 107 2.156 .098William Hanrahan 5 Soup Likelihood - Chicken 13.555 3 1.240 107 10.930 .000 Soup Likelihood - Mushroom 11.047 3 1.371 107 8.055 .000Soup Likelihood - Tomato and 6.328 3 1.363 107 4.644 .004 Cheese Regularly Buy Soup .070 3 .257 107 .271 .846 Regular Buy Meal .290 3 .222 107 1.302 .278 New Product Marketing 174.339 3 1.672 107 104.244 .000 9.5 Appendix 5: Executive Summary William Hanrahan 17 Coniston Avenue Jesmond Newcastle Upon Tyne NE2 3EY [email protected] Tuesday, 14 April 2009Dear Keith,Please find enclosed recommendations from my final year dissertation summarised for you in relation to the Look What We Found brand with a focus on the student market. The research I have employed in this study has used related literature in the field, questionnaires and cluster analysis. Please could you send me a response by email to this letter as I intend to include it as part of the dissertation summary, I would be delighted to receive your feedback to this report’s findings.Once my dissertation is ready, I will send you a printed copy of the complete dissertation. Thank you for the help and support you have provided in allowing me to study your company for my dissertation project,Yours Sincerely,William HanrahanWilliam Hanrahan 5 This study looked into the current situation of Look What we found brand and identified the need to find new markets, the Student market was identified as a potential target so this became the focus of the research. A Literature review was completed looking into Student food shoppers, new product marketing, British and regional foods and the recommended analytical techniques. Questionnaires were completed by 111 Newcastle University students responsible for providing their own food. When students were asked about the following brands – Look What We Found, New Covent Garden, Seeds of Change, students demonstrated the lack of impact that some of these brands have made on them. 80% of students had never heard of Look What We Found, however with the Chilled soup brand ‘New Covent Garden’, 63% of students had heard of the brand, with 40% having purchased the brand, showing that students were willing to pay for premium soups. Half of the student sample regularly buys soup, and 67% of the sample regularly purchases convenience food. When asked for their usual soup purchase the majority responded canned soup at 50% followed by Chilled fresh soup at 27.7%, this identifies that students are open to both types of soup and if correctly targeted it’s likely that The Tanfield Food Group soups can become a popular choice. Similar results followed for ready meals, 48% responding with Chilled foods, but just over 11% responding ambient foods. Suggesting there’s a long way to go in informing customers about this particular food type. Tesco was the clear favourite in terms of students’ usual supermarket with 82% shopping at Tesco, followed by Asda then Marks and Spencer. Most students spend between £16 – 30 per week on food shopping and 16 – 30 minutes preparing evening meals, just 10% spent less than 15 minutes on preparing their evening meal, suggesting they care about cooking and meal preparation, Importantly 55% of students usually buy food alone, from this I imagine that many students will cook alone, which suits the portion size of The Tanfield Food Group, suggesting a good fit for the student market as opposed to other consumer groups who usually cook with families. Less than 5% of the sample spent longer than 45 minutes preparing meals which is usually less than the time it takes prepare the cooked meal choices offered by The Tanfield Food Group, this suggests students may be missing out on some proper home cooked meals due to time restraints. 96.4% of students responded yes to being attracted by special offers in the supermarket, a resounding signal that students are very much interested by deals.Student Questionnaire Responses  Beef and Basil Meatballs in tomato sauce, Cumbrian Lamb Hotpot, Traditional Pork and Herb Sausage casserole, Home Reared beef in black velvet porter with Maris piper potatoes were the most popular meals in the student group, they were suggested as the meals that students were most likely to purchase. For the mass student market William Hanrahan 5 the two most popular meals were Beef and Basil Meatballs in tomato sauce and Traditional Pork and Herb Sausage casserole. For soups, two options strongly stood out, they were both mostly ‘Likely’ and ‘Very Likely’ to be purchased they were free range Chicken soup with lemon thyme and English Tomato Soup with Cheviot Cheese Pesto.  When asked how often they eat out per month, 66.6% of the sample responded over 3 times per month, demonstrating that students do have a disposable income to spend on food. Importantly students seem to have been relatively unaffected by the credit crunch, the student group responded 83% weren’t affected showing that the student group are a good target during these economic difficulties compares with other consumers who have been more effected and possibly less likely to continue purchasing what is a niche product as The Tanfield Food Group. Most Consumers chose in store promotion as the most effective medium to be informed about new products. Most of the students who asked in the survey lived in Jesmond, and Tesco was the supermarket most frequented.If students are usually spending quite long time cooking then when they have a night off cooking, and go for their weekly fast food option, students could consider The Tanfield Food Group foods, through the benefits of ease of use, its ease of storage, and the fact there’s no rush to eat it, but that it’s a nutritious option, for those days you want your mums cooking, but can’t be bothered to spend hours in the kitchen, or feel good food on a lazy Saturday after a big night out! As ease of storage was seen as in important factor and is something unique about this compared to fresh meals it could be highlighted in future communications. My research identified 4 equal student cluster groups, below is a summary of the following. The study suggests that student clusters do exist; four equally sized segments emerged from the sample: ‘ Male Foodies’, ‘Delia Smith and Jamie Oliver wannabes’, ‘Pot Noodle Students’ and ‘21st Century Women’. These are the researchers personal interpretations of the clusters identified. In terms of suitability for The Tanfield Food Group meals and soups, the market review identified the need for niche food consumers and (Clusters 3 & 4) Male Foodies, Delia Smith & Jamie Oliver wannabe’s seem to be the ideal student food groups that fit into this niche.Cluster 1- (21ST Century Women) are obviously a very female dominated group and they don’t seem to be a likely target segment, they didn’t respond strongly to the current meal choice, giving a ‘very unlikely’ response to most of The Tanfield Food Group’s current Soup and Meal options. This group was most interested in the ‘Ease of storage’; they rated this as important, demonstrating how females care more about the shape of product and their aesthetics than what most males do. They spend less money on food at the home and choose to go out more and spend their budgets on meals out. Although quality, value for money was seen as important factors the recommendation from looking at Cluster 1, is to avoid thisWilliam Hanrahan 5 group. This group seem to be the new generation of Females preferring going out and spending money on what there perceive to be more important, living the ‘Sex and the City’ lifestyle. Cluster 2 (Pot Noodle Students) are a mixed sex group of students, , with seemingly lower standards of taste preferring Canned soups and Frozen meals, ‘the typical student’ , they responded that Locally sourced food was unimportant to them and responded ‘Unlikely’ to most of the food offered, expect Ham and Pea which they were responded as a ‘likely purchase’. I don’t see this group as a likely target, they go out for meals occasionally and spend the average time cooking and monthly spend between £16 – 30 pounds.Cluster 3 (Male Foodies) are a very male dominated group, spending longer on preparing meals than clusters 1 and 2 demonstrating more interest in cooking, they seem not to be affected at all by the credit crunch, with only 5% saying they had changed spending habits, and they were attracted by special offers. Quality of Food, Value for money and choice were all important factors to this group, they were impressed with the meals on offer by The Tanfield Food Group, and in particular the Velvet Porter meal. They felt the same about Soups, as regular purchasers they favoured the Chicken soup. After looking at this group in depth, this group seems like an ideal target, they were the most likely group to purchase Ambient meals, but still don’t seem to have much knowledge about the products offered by The Tanfield Food Group. As the minority group of 17% of students this segment is still large enough to be viable as part of the 1.9 million students (Ness, 2002) in the UK. This small segment I have identified as ‘Aspiring males’ – those males who enjoy good wholesome food, likely to play sports and are taking a keener interest in food, thanks to a revival in cooking from some strong males figures as Hugh Fernley Whittingstall and Gordon Ramsey.Cluster 4 (Jamie Oliver & Delia Wanabees’) contain 24% of the student sample, and is of equal distribution of males and females, they have the highest average spend at over £30 a month, suggesting they like to purchase quality food, although 30% of its students have been affected by the credit crunch, suggesting that they may need to alter their higher levels of spending, as a result they are very influenced by promotions, with 100% of the segment admitting to be influenced by special offers. To them Quality of food, value for money, nutritional value and choice are all important, while they may be quite a busy set of consumers who still choose to allocate a lot of time to cooking, spending an average time cooking of 31 – 45 minutes, suggesting they really enjoy cooking and enjoy good food, however when looking at convenience foods they placed the highest importance of all the groups on ease of use and cooking time, suggesting they when they want to take a break from the toil of their usual meals with long preparation times, they want something as easyWilliam Hanrahan 5 as possible. They eat out least, probably due to the fact that they realise they can cook better meals in their homes, and for that reason choose to spend the money they save on other social activities, or simply on better ingredients in their own cooking. However it shows that on the occasion that they do want a night off, The Tanfield Food Group could be the ideal option. When purchasing convenience food they usually go for Chilled foods, but placed a ‘likely’ preference to purchasing meals offered by ‘The Tanfield Food Group’. For the meals they chose Velvet Porter, Casserole, Beef Chilli C.C, and soup Chicken. I would class this group as ‘True Foodies’ probably from higher social class families.Previous to this study little was known about student groups and although segmentation had occurred this had only been done on financial methods, but not relating to their preferences and attitudes towards convenience food, in particular the ambient food market. I am very happy that through statistical analysis I was able to cluster the student sample effectively, while using the focus of a food brand as a key factor for differentiation. 9.6 Appendix 6: Use of Social networkingWilliam Hanrahan 5 William Hanrahan 5

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