Using Data Mining to Increase Customer Life Time Value

Chu Chai Henry Chan Hsin-Chieh Wu

E-Business Research Lab Department of Industrial Engineering and Management,

Chaoyang University of Technology Wufeng, Taiwan, R.O.C.

Abstract: - In the recent years, customer relationship management (CRM) is an important issue for marketers. Most of marketing researchers intend to compute customer value and provide valuable activities when customers demand are occurring. Unfortunately, the linkage between customer value and campaign management is still missing. This research proposes lifetime value (LTV) model in analyzing customer lifetime value to construct new promotion plans. To condcut a case study, this investigation extracts more than ten thousand customer data from a Nissan dealer for finding the customer detecion. From evaluating the customer lifetime values, we found two interesting outcomes. The first one is that the activties of maintenance item is more valuable than those activies of car purchasing and car issurance. The second one is that a lot of new customers lost their loyalties on the second year. To slove the two problems, this research suggest the studied Nissan dealer shoutd take two corresponding promotion stratetgies. First, the dealer should provids five-years assurance for new car purchasing customers to increase their loyalty. Secondly, they need to decrease the price of maintenance and speed up the process of maintenance to attract customers. Key-Words: - Customer Relationship Management, Customer Lifetime Value, Data Mining

1. Introduction Customer Relationship Management (CRM) is one of the most important strategies for many corporations to retain customers and keep profits in the global competitive environment. The major tasks of CRM include customer acquisition, customer development and customer retention [4]. Most existing researches focus on using lifetime value to compute the value of customer. For example, Verhoef applied a regretion model to prodict the potential value of customers in the insurance industry[11]. Hwang used LTV model on the wireless telecommunication industry in year 2005 [6].. Unfortunately, most existing researches still stay in academic study. Most of private sectors did not know how to use customer value to increase their value and profitability. This paper is aiming to demonstrate the application of using the customer lifetime value model in finding the problems of customer detection and create new strategies for value creation. Based on the proposed procedure, most companies can find the customer detection and provide a better strategy for increasing customer value. By using the customer value evaluation processes, the potential customer value can be added. In this paper, the proposed concept is applied in a case study of automobile industry.

2. literature Review Two significant issues must be addressed in this study. First, the existing data mining researches would be reviewed. Secondly, the previous studies of custom life time value should be depicted shortly.

2.1 Customer Value Most companies dedicate all of their resources to attract customers, but not all of customers are valuable. Since 1980, many corporation and researches developed customer relationship management to sustain the profitable customer as longer as possible [5,9,12,13,14]. In previous study, CRM comprises the activities; customer acquisition, customer cultivation, and customer retention [6]. The customer value are classified into three categories; current value, potential value and loyalty [6,11]. The value creation process consists of three key elements: the value customer receives; the value organization receives; and, by successfully managing this value exchange, maximizing the lifetime value of desirable customer segments [10]..

Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications, Elounda, Greece, August 18-20, 2006 (pp13-17)

2.2 Data Mining Even CRM had employed in the real world for half of a decade. Still a lot companies face the painful problem in losing their most profitable customers daily. Some studies began to use data mining as a tool to dig out the hidden problems of missing customer loyalty [2,17]. The technology of data mining is defined as a sophisticated data search capability that uses statistical or intelligent algorithms to discover patterns and correlations in data [3,15]. Several studies use data mining to segment customers in bank, insurance, telecommunication industry, retailer, hospital [1,6,7,8,11,15] 3. Mining Customer Value Recognition of the importance of relationships in recent years has inspired marketers to focus on the maintenance of exchange relationships rather than on the accumulation of transient transactions[16]. IBM Corp. recommends four steps to employ relationship marketing with valuable customers (see Fig. 1). First, product information has to be prepared by marketers. Secondly, marketing and merchandising techniques need to deliver key information to customer through multiple mediums, such as webs, e-mail, POS and call. Thirdly, the merchandising results would be analyzed into the forms of business intelligence. Finally, the business intelligences would be utilized to construct the profile of customer for understanding the behaviors of customers. The purpose of CRM is to min customer value for finding a good successful promotion plan. Most of existing researches only focus on mining customer behavior and fail to link with any promotion plan. To cope with this problem, this research proposes a customer lifetime value model to conduct data mining in finding the changes of customer value. From the analyzed result, automobile dealer can figure out the trend of value creation processes. Then a valuable promotion plan would be generated to establish a good relationship with customers and increase profitability (see Fig. 2). 4. Customer Life Time Value Model

To analyze the lifetime value of customer, the core costs of customer in automobile industry incorporates three items; purchase, insurance and maintenance. The purchase information represents the cost of purchasing a new car. The insurance information denotes the cost of customer attending

an insurance policy. The maintenance cost is the expenditure on maintaining a car annually.

- Marketing and Merchandising Techniques

-Profile - Demographics - Behavioral - Business System's Data

- Data mining - User analysis- Usage analysis - Commerce analysis

- Product Information - Other Web Info.

Business Intelligence

Customer information

Content

Business Manager – Flexible Rules Builder – Merchandising Center

What's delivered

Callcenter

Print

e-mail

POS

Web

Personalization Capabilities

Fig. 1 Relationship Marketing Cycle

Enhanchements By IBM [4]

Furthermore, the revenue for each customer and items are different. For example, the average revenue of purchasing a new car is close to seven percentages. The average revenue of inviting a customer attending an issuance is fifty percentages. Based on this notation, the average revenue for each items are different. In this paper, the LTV model is defined as following:

Fig. 2 The Framework of Mining Customer Lifetime Value

Customer Data Collection

Built Customer Lifetime Value

Model

Data Mining for Customer Retention

Customer Value Creation

New Promotion Plan

Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications, Elounda, Greece, August 18-20, 2006 (pp13-17)

Current Value = ...(1)

Where:

t-1

0 1 1( )(1+r)

i

i

C n n

i ic x cxt y cytC t t

V m V I V M= = =

+ +∑ ∑ ∑

Vi= The Average Revenue of Car Purchasing Profit

Mic= Car Purchasing Profit Contribution of Customer i At Period c

Vx= Insurance Profit contribution of Customer i

Icxt= The average revenue of Insurance Profit

Vy= Maintenance Profit contribution of Customer i at period t

Mcyt= The average revenue of Maintenance Profit

r= Interest Rate t= The length of years which cars

are purchased

5. Case Study To conduct an empirical study, this study collect 12598 historic data of 10456 customers from a Nissan automobile dealer in Central Taiwan (see figure 1). From the aspect of customer data in table 1, we found that 86.97% of customers purchase only one car and 13.03% of customers own two cars or more. Under the investigation, the most popular models are Sentra, Cefiro and March (see Table 2). Based on the analysis of our study, the customer lifetime value is gradually increasing annually (see Fig. 3), but not all value item are increasing. From Fig. 4, we found that only the value of maintenance item is increasing annually. Car purchase and insurance would not the most value-added processes. Fig. 5 shows that the numbers of customer are decreased gradually after the second year. It means that most customers lost their loyalties on the second year. After data mining, we suggested that the studied Nissan dealer need to launch a new promotion plan to retain customer on the second year and increase customer value on maintenance.

Table 1 the Basic Customer Information based on the Length of Year

Year 1 2 3 4

Number 9172 1102 168 37

Percentage 86.97% 10.45% 1.59% 0.35%

Year 5 6~12 Over12

Number 22 39 6

Percentage 0.21% 0.37% 0.06%

Table 2 The Distribution of Car Model

Model March Sentra Cefiro X-Trail Serina

Number 2070 4662 2797 874 252

Percentage 16.43% 37.01% 22.20% 6.94% 2.00%

Model Teana Primera AD Resort Cabstar Others

Number 150 262 113 141 1277 Percentage 1.19% 2.08% 0.90% 1.12% 10.14%

After several creation meetings, a credited-based program is designed by the Nissan deal. In this program, the dealer would provide five-years assurance for all of new car purchasing customers to increase their loyalty. From the marketing surveys, we also found that prices and time consuming on maintenance are two key factors of affecting customer’s maintenance. To improve such problems, the dealers began to decrease the price of maintenance and speed up the process of maintenance to lure customers. The details of two proposed strategies are shown in table 3.

0

20,000,000

80,000,000

100,000,000

120,000,000

140,000,000 160,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Current Value Potential Value Life Time ValueAverage Average Average

60,000,000

40,000,000

Fig.3 the Customer Life Time Value Distribution

Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications, Elounda, Greece, August 18-20, 2006 (pp13-17)

Fig. 4 the Customer Value Distribution for each

Purchasing Items

Fig. 5 the Customer Number Distribution

Table 3 Value Creation Strategy

Problems Value Creation Process

Strategy

1. Only the value of maintenance item is increasing annually.

Provide a good offer on maintenance to attract customers and retain loyal customers.

Decrease the price of maintenance and speed up the process of maintenance to attract customers.

2. Customers lost their loyalty on the second year.

Implement a promotion plan to retain customer

A five-years assurance program are launched

lied in several industries by

odel in

tomer value and promotion d

the customer value of 10456

odel to find the

o thank the EMPower

eferences: O¨ztu¨rk, Sinan Kayalıgil,

6. Conclusion Even CRM had app

0

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

60,000,000

70,000,000

80,000,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Car Purchase Maintenance Average Average

Average Insurance

many well-known companies such as IBM, Cisco. At the mean time, a lot of previous researches proposed data mining to find the patterns of customer behavior [3,15]. For instance, Hwang and Verhoef applied differnt models to compute the customer value[4,11]. The link between customer value and promotion plans is still msssing. To deal with the obstacle, this paper proposes a mechanism to mine the value of customer lifetime value for support a valuable promotion plan. The major contributions for this paper as follows:

Propose a customer value mautomobile industry

Connect the cusby ata mining This study computedata. From evaluating the customer lifetime values, we found two interesting outcomes. The first one is that the activties of maintenance item is more valuable than those activies of car purchasing and car issurance. The second one is that a lot of new customers lost their loyalties on the second year. To slove the two problems, this research suggest the studied Nissan dealer shoutd take two corresponding promotion stratetgies. First, the dealer should provids five-years assurance for new car purchasing customers to increase their loyalty. Secondly, they need to decrease the price of maintenance and speed up the process of maintenance to attract customers. After this study presents a LTV m

0

500

1,000

1,500

2,000

2,500

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Car Purchase Maintenance Insurance

problems of customer detection and provide value creation strategies, one of major problems for promotion is to search the right and profitable customers. In the future, more researches should be conducted in the ares of targeting customers to assist automobile retailers implementing effecitve promotion plans. Acknowledgments The authors would like tCorporation and National Science Council of the Republic of China, Taiwan for financially supporting this research. R [1] Atakan

Nur E. O¨zdemirel, “Manufacturing lead time estimation using data mining,” European Journal of

Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications, Elounda, Greece, August 18-20, 2006 (pp13-17)

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Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications, Elounda, Greece, August 18-20, 2006 (pp13-17)