Title page for etd-0110117-143921


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URN etd-0110117-143921
Author Hao-yu Chung
Author's Email Address No Public.
Statistics This thesis had been viewed 5341 times. Download 631 times.
Department Business Management
Year 2016
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title The Study of Marketing Strategy and Customer Management in the Age of Data-A Case of Company O
Date of Defense 2016-06-29
Page Count 79
Keyword
  • Data analysis
  • Customer lifetime value
  • Prediction
  • Marketing strategy
  • Customer management
  • Abstract It is well-known that a company makes revenues from customers. In other words, customers can dominate and dictate the prospect of a company. Consequently, importance of customers for the survival of a company has attracted increasing attention in the trend of marketing. In current scenario, marketing is no longer a one-way strategy which regards satisfying customers’ needs as the only object. Instead, it should be a two-way approach by which co-values for both companies and customers can be created.
    How do customers offer values to a company? The answer is DATA! For instance, since transaction data between customers and a company is usually available, the latter can acquire the implied information easily. This includes the starting point of the relationships between customers and companies, negotiation and coordination in the transaction process, as well as completion time of the transaction. Unfortunately, only few companies can realize how these data can be applied to the co-value creation process.
    In the past, companies set the STP and then attracted customers through 4P actions. Nevertheless, there are several blind spots in this approach, e.g., if these customers are really suitable for the company, and how long they will stay in the company. Fortunately, these shortcomings can be overcome through the transaction data analysis. Based on the analyzed data, a company can scientifically predict each customer’s whole life contribution, which is called Customer Lifetime Value (CLV/CLTV), and can estimate potential revenues that can be produced by each customer. Moreover, based on the analyzed data, a company can find out its "true friends", then uses an appropriate approach at the right time to retain them, and even develop potential customers. In this way, a company can keep its regular customers, develop new customers, evaluate individual cost limit of maintaining every single customer, make optimum resources allocation, automatize the customer management process, and finally make more profits.
    Nowadays, restaurant industry is one of the fast-growing industries in Taiwan. It is reported that the number of restaurants nearly increased over 18% from 2008 to 2012, which was much higher than the average increasing rate of 5.5% in other industries. Based on an official document made by Ministry of Economic Affairs and Statistics Department, the turnover produced by restaurant industry nearly has increased by 200% from February 2006 to February 2016. In addition, the number of employees engaged in restaurant related industries has increased by 26% from 2003 to 2012. This drives the number of students studying in food and beverage departments has increased over 300% from 2005 to 2011 (Ming-Ling Xie, 2012). Therefore, this thesis will focus on restaurant industries by investigating the Marketing Strategy and Customer Management of a restaurant. We will choose a restaurant for our case study. The selected restaurant satisfies the following three criteria: (1) It is a benchmark in restaurant industry with rapid growth rate; (2) It has kept customers’ transaction data already; (3) The customers’ transaction data have not being employed to the marketing strategies yet. This research will use case interview method to analyze suitability of the company 's environmental background, as well as STP and 4P actions. Thereafter, we will use the data obtained from actual customer behaviors to set up a regression model. By using this model, we can predict each customer’s future contribution and value, classify them, and finally make recommendations to the company. In conclusion, we expect that this research can provide a useful guidance for those restaurant operators in Taiwan who want to use data marketing.
    Advisory Committee
  • Hsuan-yi,Chou - chair
  • Chien-yuan,Sher - co-chair
  • Wei-ning,Wu - co-chair
  • Chi-cheng,Wu - advisor
  • Files
  • etd-0110117-143921.pdf
  • Indicate in-campus at 1 year and off-campus access at 1 year.
    Date of Submission 2017-02-10

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