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1NH18MBA03.Pdf \ Adhesh_Dheeraj_report.pdf by Submission date: 28-Apr-2020 06:11AM (UTC+0530) Submission ID: 1309691549 File name: Adhesh_Dheeraj_report.pdf (2.18M) Word count: 9211 Character count: 59396 PROJECT REPORT ON Consumer Behavior through Website Analysis of Lenovo BY Adhesh Dheeraj 1NH18MBA03 Submitted to DEPARTMENT OF MANAGEMENT STUDIES NEW HORIZON COLLEGE OF ENGINEERING, OUTER RING ROAD, MARATHALLI, BANGALORE In partial fulfillment of the requirements for the award of the degree of MASTER OF BUSINESS ADMINISTRATION Under the guidance of Prof. Dr. Smita Harwani 2018-2020 CERTIFICATE This is to certify that ADHESH DHEERAJ bearing USN 1NH18MBA03, is a bonafide student of Master of Business Administration course of the Institute 2018-2020, autonomous program, affiliated to Visvesvaraya Technological University, Belgaum. Project report on “Consumer Behavior through website Analysis of Lenovo” is prepared by him/her under the guidance of Dr. Smita Harwani, in partial fulfillment of requirements for the award of the degree of Master of Business Administration of Visvesvaraya Technological University, Belgaum Karnataka. Signature of Internal Guide Signature of HOD Principal Name of the Examiners with affiliation Signature with date 1. External Examiner 2. Internal Examiner DECLARATION I, Adhesh Dheeraj, hereby declare that the Project report entitled Consumer Behavior through Website Analysis of Lenovo prepared by me under the guidance of DR. SMITA HARWANI, of M.B.A Department, New Horizon College of Engineering. I also declare that this Project is towards the partial fulfillment of the university regulations for the award of the degree of Master of Business Administration by Visvesvaraya Technological University, Belgaum. I have undergone an industry Project for a period of Eight weeks. I further declare that this report is based on the original study undertaken by me and has not been submitted for the award of a degree/diploma from any other University / Institution. Signature of Student Place: Date ACKNOWLEDGEMENT The successful completion of the project would not have been possible without the guidance and support of many people. I express my sincere gratitude to Mr.Santhosh Nair, Director of Global Analytics, Lenovo, Bengaluru, for allowing to do my project at Lenovo. I thank the staff of Lenovo, Bengaluru for their support and guidance and helping me in completion of the report. I am thankful to my internal guide Dr. Smita Harwani , for his constant support and inspiration throughout the project and invaluable suggestions, guidance and also for providing valuable information. Finally, I express my gratitude towards my parents and family for their continuous support during the study. ADHESH DHEERAJ 1NH18MBA03 TABLE OF CONTENTS SL no Chapters Page no Chapter 1 Executive Summary 8-8 Chapter 2 Theoretical Background of 9- 15 the study Chapter 3 Industry and company profile 16 – 30 Chapter 4 Application of theoretical framework 31 - 43 Chapter 5 Analysis and interpretation 44– 54 of financial statement Chapter 6 Learning experience 55 - 58 conclusion Chapter 7 Bibliography 59 CHAPTER-1 EXECUTIVE SUMMARY Executive summary Lenovo, the largest PC business in China faced the intensified competition of its own market by global level companies such as HP and Dell. In attempt to expand the market internationally, Lenovo made the acquisition of IBM’s PC division. Since two organizational cultures were different, the synergy of the merged Lenovo-IBM was required. Lenovo entitled to IBM landmark and “Think” products to move to international market and enabled to increase the market power by over night after the acquisition. Together with IBM sales forces and distribution expertise, Lenovo employed it cost-efficiency and technology expertise in respond to the global demand. Moreover, it allows Lenovo to gain market power and rapid growth in the global level by the acquisition. Essentially, sale activities, distribution network and services and solutions which IBM focuses in global level could benefit Lenovo in the future prospect. From IBM’s PC division point of view, acquisition also required large amount of funds which could quickly boost the losses of IBM’s PC division of nearly $ 1 billion since 2001. Furthermore, it also provided the opportunity for IBM to enter Chinese market and focused more on services while manufacturing function Lenovo could cope with very well. Although two different companies have the similar focus and vision in terms of consumers-oriented and full range of services, they are quite different in internal level and their business. Problems identification after acquisition , one of the problems that Lenovo - IBM faces is the organizational culture. Essentially, when two culture - different firms are formed, this could lead to the difficulty after integration. Potential reasons are firstly the differences in target market where Lenovo focuses on Low-end market trying to achieve the cost leadership, while IBM targets High-end market offering the innovation, good quality products and service. CHAPTER-2 THEORITICAL BACKGROUND Analytics Analytics is the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision making. In other words, analytics can be understood as the connection between data and effective decision making within an organization. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Organizations may apply analytics to business data to describe, predict, and improve business performance. Specifically, areas within analytics include predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, Big Data Analytics, retail analytics, supply chain analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics. Since analytics can require extensive computation (see big data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics. ON-SITE ANALYTICS There are no globally agreed definitions within web analytics as the industry bodies have been trying to agree on definitions that are useful and definitive for some time. The main bodies who have had input in this area have been the IAB (Interactive Advertising Bureau), JICWEBS (The Joint Industry Committee for Web Standards in the UK and Ireland), and The DAA (Digital Analytics Association), formally known as the WAA (Web Analytics Association, US). However, many terms are used in consistent ways from one major analytics tool to another, so the following list, based on those conventions, can be a useful starting point: Bounce Rate - The percentage of visits that are single-page visits and without any other interactions (clicks) on that page. In other words, a single click in a particular session is called a bounce. Click path - the chronological sequence of page views within a visit or session. Hit - A request for a file from the webserver. Available only in log analysis. The number of hits received by a website is frequently cited to assert its popularity, but this number is extremely misleading and dramatically overestimates popularity. A single web-page typically consists of multiple (often dozens) of discrete files, each of which is counted as a hit as the page is downloaded, so the number of hits is really an arbitrary number more reflective of the complexity of individual pages on the website than the website's actual popularity. The total number of visits or page views provides a more realistic and accurate assessment of popularity. Page view - A request for a file, or sometimes an event such as a mouse click, that is defined as a page in the setup of the web analytics tool. An occurrence of the script being run in page tagging. In log analysis, a single page view may generate multiple hits as all the resources required to view the page (images, .js and .css files) are also requested from the webserver. Visitor / Unique Visitor / Unique User - The uniquely identified client that is generating page views or hits within a defined time period (e.g. day, week or month). A uniquely identified client is usually a combination of a machine (one's desktop computer at work for example) and a browser (Firefox on that machine). The identification is usually via a persistent cookie that has been placed on the computer by the site page code. An older method, used in log file analysis, is the unique combination of the computer's IP address and the User-Agent (browser) information provided to the web server by the browser. It is important to understand that the "Visitor" is not the same as the human being sitting at the computer at the time of the visit, since an individual human can use different computers or, on the same computer, can use different browsers, and will be seen as a different visitor in each circumstance. Increasingly, but still, somewhat rarely, visitors are uniquely identified by Flash LSO's (Local Shared Object), which are less susceptible to privacy enforcement. Visit / Session - A visit or session is defined as a series of page requests or, in the case of tags, image requests from the same uniquely identified client. A unique client is commonly identified by an IP address or a unique ID that is placed in the browser cookie. A visit is considered ended when no requests have been recorded in some number of elapsed minutes. A 30-minute limit ("time out") is used by many analytics tools but can, in some tools (such as Google Analytics), be changed to another number of minutes. Analytics data collectors and analysis tools have no reliable way of knowing if a visitor has looked at other sites between page views; a visit is considered one visit as long as the events (page views, clicks, whatever is being recorded) are 30 minutes or less closer together.
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