PMTK Role Descriptions
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Marketing Engineering MGMT 49000
WALTON MBA ALUMNI RECONNECT DISRUPTION IN RETAIL Dinesh K. Gauri WHO AM I Dinesh Gauri . M.S. in Mathematics & Computer Applications . M.A. Economics . Ph.D. Marketing . Professor of Marketing (at Walton College since July 2016) . Executive Director of Retail Information . Associate Editor – Retailing Area, Journal of Business Research WATCH YOUR DAY IN FUTURE THE RETAILER’S ROLE IN A SUPPLY CHAIN 1-4 1-5 DISRUPTION IN INDUSTRY – OVER DECADE Retailer Market Value Market Value Change (2006) (Today) $28.4 B $15 B (47 %) $18.1 B $ 1.9 B (89 %) $24.2 B $ 6.9 B (71 %) $24.2 B $ 9.1 B (62 %) $12.4 B $ 7.7 B (37 %) $27.8 B $ 1.5 B (94 %) $51.3 B $ 29.5 B (42 %) $214 B $ 222.7 B 4 % $17.5 B $ 430.7 B 2361 % LEADING TO OVER $300B IN M&A OVER THE LAST 30 MONTHS IN CPG AND RETAIL ALONE E-COMMERCE RETAIL SALES AS % OF TOTAL SALES Ecommerce Retail Sales in 2016 - $398 billion BIGGEST U.S. E-COMMERCE RETAILERS Amazon.com $94.7 b* Apple $16.8 b Walmart $14.4 b Home Depot $5.6 b Best Buy $4.8 b Macy's $4.6 b Costco $4.2 b QVC $4.0 b *Excludes Media and Services Source: E-Marketer Inc. WHERE DO US CONSUMERS SHOP? Top 10 retailers and restaurants Penetration of US shoppers who made a purchase at one of these companies in 2016 Wal-Mart 95% McDonald's 89% Target 84% Walgreens 77% Dollar Tree 71% Subway 70% CVS 69% Home Depot 68% Taco Bell 62% Burger King 60% Source: NPD Group’s Checkout Tracking NON-FOOD RETAIL VS. -
Strategic Product Planning
Strategic Product Planning – The Enlightenment An explorative mapping of formal processes within Nordic-based industrial companies Master of Science Thesis in the Master’s Degree Programs Management and Economics of Innovation, and Supply Chain Management KRISTOFFER CLAESSON DANIEL LOVENBÄCK Department of Technology Management and Economics Division of Innovation Engineering and Management CHALMERS UNIVERSITY OF TECHNOLOGY Göteborg, Sweden, 2012 Report No. E 2012:075 MASTER’S THESIS E 2012:075 Strategic Product Planning – The Enlightenment An explorative mapping of formal processes within Nordic-based industrial companies KRISTOFFER CLEASSON DANIEL LOVENBÄCK Tutor, Chalmers: Magnus Holmén Tutor, Triathlon: Martin Karlsson & Peter Bengtsson Department of Technology Management and Economics Division of Innovation Engineering and Management CHALMERS UNIVERSITY OF TECHNOLOGY Göteborg, Sweden 2012 Strategic Product Planning – The Enlightenment – An explorative mapping of formal processes within Nordic-based industrial companies © Kristoffer Claesson, Daniel Lovenbäck, 2012 Master’s Thesis E 2012:075 Department of Technology Management and Economics Division of Management and Economics of Innovation Chalmers University of Technology SE-412 96 Gothenburg, Sweden Telephone: + 46 (0)31-772 1000 Chalmers Reproservice Gothenburg, Sweden, 2012 Acknowledgements Since this master’s thesis, carried out during the spring of 2012, has been one of the largest academic projects conducted by us up until this date it has been both challenging and inspiring. It has been a major step in finalizing our studies within the area of Industrial Engineering and Management at Chalmers University of Technology. During our work with the master’s thesis we have had the privilege to receive valuable input and guidance from multiple sources in our effort to finalize the report, and we are grateful for each and every one of them. -
Product Planning
Product Planning Product planning is the process of creating a product idea and following through on it until the product is introduced to the market. Additionally, a small company must have an exit strategy for its product in case the product does not sell. Product planning entails managing the product throughout its life using various marketing strategies, including product extensions or improvements, increased distribution, price changes and promotions. Developing the Product Concept The first phase of product planning is developing the product concept. Marketing managers usually create ideas for new products by identifying certain problems that consumers must solve or various customer needs. For example, a small computer retailer may see the need to create a computer repair division for the products it sells. After the product idea is conceived, managers will start planning the dimensions and features of the product. Some small companies will even develop a product mock-up or model. Studying the Market The next step in the product planning process is studying the competition. Most small companies will order secondary research information from vendors such as the NPD Group and Forrester Research. Secondary research usually provides details on key competitors and their market share, which is the percent of total sales that they hold in the marketplace. Some companies may also do a SWOT analysis (strengths, weaknesses, opportunities and threats), according to NetMBA.com, which will help them compare their strengths and weaknesses against those of key competitors. The business can then determine places in which it has an advantage over the competition to identify areas of opportunity. -
Marketing Engineering and Making Marketing Decisions
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 8, ISSUE 12, DECEMBER 2019 ISSN 2277-8616 Marketing Engineering And Making Marketing Decisions Mahmood Jasim Alsamydai Absract : The concept of marketing engineering has become, today, an issue of great importance because it has helped in enabling marketing management to gain information and analyze it by using computer devices, communication networks, software and marketing decisions support systems, thus helping marketing management to take marketing decisions. The term marketing engineering can be traced back to Lilien et al. in "The Age of Marketing Engineering" published in 1998. In this article the authors defined marketing engineering as the use of computer decision models in making marketing decisions. The definition of marketing engineering was also developed by Lilien et al. 2002, who defined marketing engineering as "the systematic process of putting marketing data and knowledge to practical use through the planning, design, and construction of decision aids and marketing management support systems (MMSSs)". Among the driving factors toward the development of marketing engineering are the use of high- powered personal computers connected to LANs and WANs, the exponential growth in the volume of data, and the reengineering of marketing functions. other researcher also called marketing engineering "the systematic process of putting marketing data and knowledge to practical use through the planning, design, and construction of decision aids and marketing management support systems." Marketing management works in a variable and unstable environment, where it is requested to be flexible and interactive with these changes in the internal and external environment of the organization. There is a tremendous flow of information, where marketing engineering has to collect and analyze, by adopting information systems, information technology management decision support systems. -
The Impact of Product Planning and Development to Management Efficiency: a Case Study of Seven up Bottling Company, Aba, Abia - State, Nigeria
COMMERCE ECONOMICS AND BUSINESS MANAGEMENT Journal homepage: www.jakraya.com/journal/cebm ORIGINAL ARTICLE The Impact of Product Planning and Development to Management Efficiency: A Case Study of Seven Up Bottling Company, Aba, Abia - State, Nigeria Iwunze FC1 1Department of Marketing, Imo State Polytechnic Umuagwo, Nigeria. Abstract This study concentrated on the impact of product planning and development to management efficiency. The main objective is to determine *Corresponding Author: how product planning and development can prevent product failure in the Iwunze FC market place. The study adopted the quasi - experimental design which made use of questionnaire and interview to gather information. Customers’ Email: [email protected] needs and wants were determined when the organization applied on product planning which leads to the success. However, findings revealed that product planning and development created distinctive advantages in both Received: 03/06/2018 product and customer performance. The study recommends that planning Accepted: 01/07/2018 should always be made before development to ensure that product developed is what the customers need and required. Keywords: Product planning, Development, Management Efficiency, Seven Up Bottling Company, Organization. 1. Introduction develop new products usually have limited study in the The life cycle of a product and the life cycle of organisation, hence, there is need for product planning the respective production equipment intersect in the and development. Azu (2014) referred product production phase of the product, which at the same planning and development as characterized by risk and time represents the use phase of the production uncertainties. The dangers may be in wasting financial equipment (Steffens, 2002). -
Determinants of Competitor's Response Time to the New Product
The Journal of Nepalese Business StudiesDeterminants Vol. of Competitor’sII No. 1 Response Dec. Time2005 Determinants of Competitor’s Response Time to the New Product in the Market of Nepal Bed Nath Sharma ABSTRACT This study is concerned with competitor’s response time determinants to a new consumer prod- uct in Nepalese market. Products are in high competitive situation. New–to-the-world product is facing more competition complexities. Channels, market research, sales force and public opin- ions are the main source to get the market information of new products. Consultant’s service is main helping hand to increase competitive strength. Financial and non-financial measures are applied to increase the competitive ability. Both qualitative and quantitative methods are in use to measure competitiveness of new products. The competitor’s response time to most of the new products is less than six months after commercialization. Types of users are also in focus while developing the new products. Cut-throat competition is emerging in the market and firms are not able to defend fairly. IN TODAY’S GLOBALLY COMPETITIVE world, successful new product planning and development is a challenge to the industry. It is a creative function within a business organi- zation. Modern concept of new product planning and development is the involvement of multi-disciplinary team from idea generation to commercialization. In Nepal, competition is increasing day by day. Many products of same use are available in the market. Product failure rate is also increasing. Many products are in sick situation. So the study is focused to know that “what are the determinants of competitor’s response time to a new product in Nepalese market?” 1. -
Marketing Engineering for Excel • Tutorial •
MARKETING ENGINEERING FOR EXCEL TUTORIAL VERSION 160804 Tutorial Positioning Marketing Engineering for Excel is a Microsoft Excel add-in. The software runs from within Microsoft Excel and only with data contained in an Excel spreadsheet. After installing the software, simply open Microsoft Excel. A new menu appears, called “MEXL.” This tutorial refers to the “MEXL/Positioning” submenu. Overview Positioning analysis software incorporates several mapping techniques that enable firms to develop differentiation and positioning strategies for their products. By using this tool, managers can visualize the competitive structure of their markets, as perceived by their customers. Typically, data for mapping include customer perceptions of existing products (and new concepts) along various attributes, customer preferences for products, and measures of the behavioral responses of customers toward the products (e.g., current market shares). Positioning analysis uses perceptual mapping and preference mapping techniques. Perceptual mapping helps firms understand how customers view their product(s) relative to competitive products. The preference map plots preference vectors or ideal points for each respondent on a perceptual map. The ideal point represents the location of the (hypothetical) product that most appeals to a specific respondent. The preference vector indicates the direction in which a respondent’s preference increases. In other words, a respondent’s ideal product lies as far up the preference vector as possible. POSITIONING TUTORIAL -
B2b Segmentation As a Tool for Marketing and Logistic Strategy Formulation
ISSN 1822-8011 (print) VE IVS ISSN 1822-8038 (online) RI TI TAS TIA INTELEKTINĖ EKONOMIKA INTELLECTUAL ECONOMICS 2011, No. 1(9), p. 54–64 B2B SEGMENTATION AS A TOOL FOR MARKETING AND LOGISTIC STRATEGY FORMULATION Stanislava GROSOVA Institute of Chemical Technology Prague, Technická 5, Praha 6 E-mail:[email protected] Ivan GROS Institute of Chemical Technology Prague, Technická 5, Praha 6 E-mail: [email protected] Magda CISAROVA Institute of Chemical Technology Prague, Technická 5, Praha 6 E-mail: [email protected] Abstract. This article deals with the B2B market segmentation as the tool for formula- tion of the marketing and logistical strategy. An empirical study on the market of secondary cardboard packaging represents the research approach carried out by personal and electronic questioning in order to determine customers´ expectations, demands, preferences and charac- teristics, results in the processing by the factor and cluster analysis, discovered and designed segments and their profiles. The research focused on existing and potential customers was primarily motivated by finding ways to discover new opportunities in value creation for spe- cific segments on stagnant market. The important part of the study is the confirmation or re- fusing of hypotheses concerning the behavior of created B2B segments. JEL Clasification: M31, M21. Keywords: market segmentation, B2B market, corrugated cardboard, marketing strat- egy, logistic strategy Reikšminiai žodžiai: rinkos segmentavimas, verslas verslui rinka, rinkodaros strategija, logistikos strategija. B2B Segmentation as a Tool for Marketing and Logistic Strategy Formulation 55 1. Introduction Significant position on secondary manipulation and transport packaging is held by cardboard packages. -
Application of Neural Network in the Cost Estimation of Highway Engineering
1762 JOURNAL OF COMPUTERS, VOL. 5, NO. 11, NOVEMBER 2010 Application of Neural Network in the Cost Estimation of Highway Engineering WANG Xin-Zheng School of Civil Engineering,Nanyang Normal University ,Nanyang city P.R.China, 473061 [email protected] DUAN Xiao-chen and LIU Jing-yan School of Economics and Management,Shijiazhuang Railway InstituteShijiazhuang city,P.R.China,050043 [email protected] Abstract—Based on the BP neural network, this paper sets up the model of cost estimation of highway engineering. The BP neural network model is trained by a sample data II. METHODOLOGY OF NEURAL NETWORK obtained from some performed typical engineering to come The neural network is a new method of information true quick cost-estimating.It is sure that the method is practical and the estimating results are reliable according processing[3]. It is the complex network system that is . formed by many plentiful and simple processing units to lots of examples It shows the promising perspective of [4] BP Neural Network in cost estimate of construction (neurons) . The neural network is one kind of engineering. large-scale parallel connection mechanism with adaptive modeling function, which simulates the structure of Index Terms -neural network, highway engineering, cost human brain[5]. Its establishment is on the basis of estimation modern neuroscience research. In many kinds of neural network models, the back-propagation neural network I. INTRODUCTION model (i.e. BP network model) is the most popular The cost estimation of the project is an important network because of its better functions of self-study and content of the feasibility Study. -
Technology Marketing Using PCA, SOM, and STP Strategy Modeling
IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 1, January 2011 87 ISSN (Online): 1694-0814 www.IJCSI.org Technology Marketing using PCA , SOM, and STP Strategy Modeling Sunghae Jun Department of Bioinformactics and Statistics, Cheongju University Cheongju, Chungbuk 360-764, Korea Abstract modeling. To verify improved performance of our study, Technology marketing is a total processing about identifying and we make experiments using patent data from United States meeting the technological needs of human society. Most Patent and Trademark Office (USPTO) [15]. technology results exist in intellectual properties like patents. In our research, we consider patent document as a technology. So patent data are analyzed by Principal Component Analysis (PCA) 2. Related Works and Self Organizing Map (SOM) for STP(Segmentation, Targeting, and Positioning) strategy modeling. STP is a popular approach for developing marketing strategies. We use STP strategy modeling for technology marketing. Also PCA and SOM 2.1 Technology Marketing are used to analyze patent data in STP modeling. To verify improved performance of our study, we make experiments using Technology marketing (TM) is at variance with general patent data from USPTO. business marketing. TM is defined as total behavior of technology transfer for planning, selling, and sales Keywords: Technology Marketing, Principal Component promotion from technology developer to technology Analysis, Self Organizing Map, Segmentation, Targeting, demander. According to development of industrial Positioning. structure, the importance of technology marketing has been increased. We have to consider the following issues for technology marketing. They are organization of TM, 1. Introduction selection of selling techniques, technology packaging, planning of TM, technology contract, post evaluation, and This paper proposes a technology marketing method using feedback. -
SPRINTER: a Tool for New Product Decision Making
LIBRARY OF THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY m 8 'ef Hue t3-69 <;t^r \D WORKING PAPER ALFRED P. SLOAN SCHOOL OF MANAGEMENT SPRINTER: A Tool for New Product Decision Making 214-66^ Glen L. Urban -.l'^^' ..^;- -_ >*•• .'^.-*,^»*->:^ i^ MASSACHUSETTS INSTITUTE OF TECHNOLOGY I 50 MEMORIAL DRIVE CAMBRIDGE, MASSACHUSETTS 02139 SPRINTER: A Tool for New Product Decision Making 214-66^ Glen L. Urban c RFXEIVED NOV 4 1965 The necessity of introducing new products has become widely recog- nized by today's business executives. Firms which do not innovate and produce new product offerings soon find their profitability impared. But those who do attempt to introduce new products are plagued by a; high failure rate in their new products. This large proportion of failures does not reflect the incompetence of decision makers, as much as it indicates the complexity and difficulty associated with the decision to market a new product. This article indicates an effective approach to the new product problem and describes how today's computer and management science technology can be used to implement this approach. The analysis is based upon a computer program called SPRINTER which is designed to be 2 used by executives to aid them in making the new product decision. SPRINTER does not completely relieve the executive of the burden of the new product decision, but it is a tool that he can use to reduce the failure rate of new products and to improve the quality of new product decisions. The model integrates the large number of complex factors affecting the decision and uses the computer to supply the muscle power necessary to optimize within this integrated framework. -
Implementing Marketing Analytics Implementing Marketing Analytics
Implementing Marketing Analytics Implementing Marketing Analytics Outline ▪ Potential benefits of vs. skepticism toward marketing analytics ▪ Empirical evidence about the per- formance implications of deploying marketing analytics ▪ Putting it all together Implementing Marketing Analytics Challenges faced by today’s marketing decision makers ▪ Global, hypercompetitive business environment. More demanding customers served by a greater number of competitors on a global scale. ▪ Exploding volume of data “We’re drowning in data. What we lack are true insights.” ▪ Need for faster decision making Information overload and lack of time, yet decisions have to be made all the time. ▪ Higher standards of accountability Marketing expenditures have to be justified in the same way as other investments. Implementing Marketing Analytics Need for better marketing decision making ▪ Intuitive decision making □ In a world characterized by rapid change, information overload, greater accountability, etc. intuition is unlikely to generate superior results; ▪ Data- and model-based decision making □ Marketing Engineering: “A systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported interactive decision process” (LRB, p. 2) ▪ Yet, “paralysis through analysis” and other criticisms of marketing analytics Implementing Marketing Analytics Marketing Engineering Marketing Environment Automatic scanning, data entry, subjective interpretation Data Database management,