Challenge
An online sales portal wanted to understand how visitors moved through its public sales pages, where they disengaged, and which patterns might explain a high bounce rate. The volume of analytics data made manual review impractical.
Approach
Batoi reviewed the available Google Analytics information, retrieved the relevant data into MySQL, and evaluated it using time-series and statistical techniques. A Naive Bayes classifier helped group behavior patterns, while JPGraph visualizations made the findings easier to review.
This historical analysis aligns with the Intelligence and Integrations responsibilities of today’s Batoi Platform; it does not imply that current Batoi Intelligence was used in the original engagement.
Outcome
The customer gained an evidence-based view of user behavior and used the findings to reorganize its online sales interface. The analysis provided a clearer basis for decisions intended to improve the sales journey.