Loyaltracker: Visualizing loyalty dynamics in search engines

Conglei Shi, Yingcai Wu, Shixia Liu, Hong Zhou and Huamin Qu

LoyalTracker illustrates loyalty dynamics of the users using search engine A. Top and bottom show the same flow view that highlights two different flowing patterns of the users (in orange) selected from a layer flow (top) and a branch flow (bottom) across multiple loyalty categories (layers) over time. The switching histogram on the top shows a visual summary of switching behavior.

Abstract

The huge amount of user log data collected by search engine providers creates new opportunities to understand user loyalty and defection behavior at an unprecedented scale. However, this also poses a great challenge to analyze the behavior and glean insights into the complex, large data. In this paper, we introduce LoyalTracker, a visual analytics system to track user loyalty and switching behavior towards multiple search engines from the vast amount of user log data. We propose a new interactive visualization technique (flow view) based on a flow metaphor, which conveys a proper visual summary of the dynamics of user loyalty of thousands of users over time. Two other visualization techniques, a density map and a word cloud, are integrated to enable analysts to gain further insights into the patterns identified by the flow view. Case studies and the interview with domain experts are conducted to demonstrate the usefulness of our technique in understanding user loyalty and switching behavior in search engines.

Materials

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