S-Space College of Business Administration/Business School (경영대학/대학원) Institute of Management Research (경영연구소) 경영논집 경영논집 vol.37 (2003)
고객 정보의 종류와 양이 구매모형 예측력에 미치는 영향에 관한 연구
How do types and number of the customer data affect the goodness-of-fit of the customer purchase models?
- 오윤경; 김지경; 김상훈
- Issue Date
- 서울대학교 경영대학 경영연구소
- 경영논집, Vol.37 No.2∙3, pp. 91-121
- The advancement of computer and telecommunicaton technology is providing numerous
ways for the marketing managers to collect and utilize consumer contact data. In other
words, marketers can now escape the limited boundaries of mass marketing channels and
begin to address individual needs of each customer, thereby realizing one-to-one marketing.
Those in academic fields have worked hard to develop models that predict the purchase
pattern and identify the causal factors. These efforts can be put into one word that has
become quite a sensation: the CRM(customer relationship marketing).
In this study, We have tried to quantitatively measure the value of customer information,
which has increasingly become important with the growing use of one-to-one marketing.
The customer information has been categorized into two, namely demographic information
and purchase history information. Different number and type covariates have been
incorporated into several models to see how they contribute to improving the goodness-of-fit of the models.
The results of the study are as follows.
First, even limited amount of demographic information about the customer can drastically
improve the goodness of fit of the models for target marketing.
Second, consumer purchase history data is more effective and better serve the purpose than
the demographic data when predicting purchase behavior.
Third, as more purchase history data are added, more accurate the model becomes.
Lastly, the marginal improvement of predictive capability of the model tends to decline as
more information is added. Therefore it can be deduced that there exists an ideal point in the
projectile of marketing budget that compromises cost and benefit.