Modeling Concentration Degree on the Most Valuable Customers for E-Commerce Sites

While examining the most valuable customers for an e-commerce site, should one focus on the customers who visit the site frequently but spend less, or those who visit the site infrequently but spend more on each visit? In terms of the consumer search propensity, should we focus on the customers who visit the web site frequently or those who make in-depth search for each visit by having a larger number of page views? To answer these questions, this dissertation take a perspective of customer concentration which can serve as a measuring metric to develop diagnostic strategies from the comparisons of different concentration degree ratios counted by means of customer’s search propensity, i.e., the number of repeat visits and the number of page views on each site visit. We also provide a framework to measure the concentration degree from two dimension, they are the aspects of customer value (purchase frequency and monetary value) as well as the customer’s search propensity, respectively. Therefore, our proposed model can identify the behavior patterns of the most valuable customers for an e-commerce site.
We apply the modeling approach to the comScore database with a focus on frequently purchased product categories such as books, music, and health & beauty.
From the empirical results, we have three main findings. First, some of the concentration degree ratios are different when calculated by including zero class versus by excluding zero class, which means there are different behaviors of search propensity for top percentile of customers while we calculate the concentration degree from different bases. These results occur at both amazon.com and barnesandnoble.com in the category of books & magazines, but just occur at columbiahouse.com in the category of music. They might be taken as product-specific feature, or website-specific feature, respectively. Second, from the comparisons of concentration degree curve, marketers can choose which extent of concentration degree is their targeting top percentile of customers in the future by comparing with its main competitor. Third, from the comparisons of concentration degree ratios, marketers also can decide which search propensity of their top percentile of customers is their focus by comparing with its main competitor. For example, in health & beauty category, both of the deviations of two concentration degree ratios in avon.com are manifestly greater than those of concentration degree ratios in melaleuca.com, no matter purchase frequency or monetary value, which reveals that the marketing strategy based on customer’s search pattern should clearly focus attention more on one of the search propensities.
In sum, even though there might be no significant difference among concentration degrees no matter on purchase frequency or monetary value in observed time period, it is useful for strategy development to keep on tracking the changes of concentration degree for itself and the whole product category, and monitoring the comparisons of concentration degree ratio with the target competitors.