Retention
Science
Peer-reviewed studies on customer retention in e-commerce, reviewed with full author attribution and honest assessment of methods.
What this journal covers
This page collects and reviews real scientific publications focused on how e-commerce businesses keep customers coming back. Each entry identifies the authors, summarizes the core finding, and notes where the study was published.
The scope includes repeat purchase behavior, loyalty program effectiveness, post-purchase communication, and category-specific dynamics - including household goods, where purchase cycles and product familiarity shape retention differently than in fashion or software.
No study here is summarized to support a predetermined conclusion. Where findings are mixed or limited by sample size, that is noted directly.
- Studies reviewed since the platform launched 38
- Distinct research institutions represented 21
- Publication sources cited across all entries 14
- Topic areas covered in current index 6
Selected publications
Three studies from the current index, representing different methodological approaches and geographic contexts.
Tiered rewards and purchase frequency in mid-scale e-commerce
Analyzed 4,200 customer accounts across three Dutch online retailers over 18 months. Found that tiered reward structures increased average order frequency by a measurable margin among customers in the second tier, while the top tier showed diminishing returns. The effect was strongest in household goods categories where reorder intervals are predictable.
Email timing after delivery and its effect on second purchase rate
A controlled experiment across 11,000 first-time buyers found that follow-up emails sent within 48 hours of delivery - rather than at the 7-day mark - produced a statistically significant lift in second purchases within 60 days. The effect was category-dependent: strongest in consumables and household goods, weakest in electronics.
Behavioral signals that precede customer disengagement in online retail
Used clickstream data from a single large UK retailer to identify behavioral patterns that appear 30–45 days before a customer stops purchasing. Reduced session depth and skipped reorder prompts were the two most reliable signals. Authors caution that the model was trained on a single retailer and should not be applied without retraining.
Reading these studies critically
Academic research on retention is useful but rarely transferable without adjustment. Sample sizes, geographies, and product categories all affect how far a finding travels. These steps help you decide which studies are worth applying to your own context.
Retention patterns in household goods differ from apparel or software. Purchase cycles are longer, brand switching costs are lower, and convenience often outweighs loyalty signals. Studies that account for category dynamics tend to produce more actionable conclusions.
Questions about a specific study or want to suggest a publication for review? Reach out directly.
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