Optimizing Web Sites for Customer Retention

TL;DR

This paper introduces an extended Logarithmic Series Distribution model to analyze and optimize customer retention on websites by understanding repeat usage patterns, demonstrated through a university's learning portal.

Contribution

It proposes a novel extension of the LSD model for web usage analysis, integrating marketing research models into CRM strategies for website optimization.

Findings

Model effectively evaluates website's ability to retain customers

Application to university portal shows improved resource engagement

Provides a quantitative basis for website optimization strategies

Abstract

With customer relationship management (CRM) companies move away from a mainly product-centered view to a customer-centered view. Resulting from this change, the effective management of how to keep contact with customers throughout different channels is one of the key success factors in today's business world. Company Web sites have evolved in many industries into an extremely important channel through which customers can be attracted and retained. To analyze and optimize this channel, accurate models of how customers browse through the Web site and what information within the site they repeatedly view are crucial. Typically, data mining techniques are used for this purpose. However, there already exist numerous models developed in marketing research for traditional channels which could also prove valuable to understanding this new channel. In this paper we propose the application of an extension of the Logarithmic Series Distribution (LSD) model repeat-usage of Web-based information and thus to analyze and optimize a Web Site's capability to support one goal of CRM, to retain customers. As an example, we use the university's blended learning web portal with over a thousand learning resources to demonstrate how the model can be used to evaluate and improve the Web site's effectiveness.