From User Behavior to Subscription Sales: An Insight Into E-Book Platform Leveraging Customer Segmentation and A/B Testing

Abstract

E-book platforms have gained popularity due to their affordability, portability, and extensive title selection. This study analyzes customer behavior based on their platform activities before the launch of a subscription service and investigates strategies to boost subscription plan adoption. To achieve this, we employ customer segmentation through a clustering algorithm to examine customer behavior. Subsequently, we track customer behavior in two distinct groups: RFM and proposed features, regarding their engagement with purchased plans via A/B testing. The results indicate that the conversion rates for the proposed features outperform the RFM model in experiments by 0.42% (2072 customers) and 0.54% (27 customers).

Keywords:

• Customer behavior
• customer segmentation
• eBook subscription
• RFM
• machine learning

Disclosure statement

No potential conflict of interest was reported by the author(s).