Acquisition and retention · Structural model using exogenous churn data from a field setting
Exploring Peer Effects Associated with User Retention in a Socially Connected Business
Chen, Y., & Mehta, N. (2026). Marketing Science, 45(2), 449–471.
Plain-English take
Churn by a high-centrality member caused a stronger negative cascade in peers' usage and subscriptions than churn by a low- or medium-centrality member. For your marketing: Where product use is collaborative, consider whether a departing or inactive central user affects teammates.
How much weight to give this
2.5/5 Limited or context-dependent evidence
The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.
This is observational evidence; selection or unmeasured differences may affect the result.
A usable sample size is not stated in the profile's accessible source.
Statistical adjustment is not the same as random assignment; review the controls and assumptions.
This profile could be checked against an abstract or metadata, not the full paper.
Double-blind? Not applicable in the same way as a participant-treatment experiment.
Research question
What the authors investigated
How does one user's churn affect usage and retention among connected peers, and whom should firms target to prevent network cascades?
Design
The authors use data from an upscale gym, including exogenous customer churn, and estimate a structural model of plan choice, usage and dynamic peer effects.
Sample and setting
Members of one upscale gym with observed social-network ties, plan choices and usage.
Reported result
What the study found
Churn by a high-centrality member caused a stronger negative cascade in peers' usage and subscriptions than churn by a low- or medium-centrality member. Short-term targeting may prioritize lower-centrality churners, while longer-term retention can favor high-centrality users because of network spillovers.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
Scope and transfer
Limitations to keep in view
One gym and its observed social network; peer effects may differ in software teams, buyer organizations and products with less visible usage. The targeting tradeoff depends on campaign and relationship costs.
Possible founder application
Where product use is collaborative, consider whether a departing or inactive central user affects teammates. Validate network effects and choose retention targets using both direct and downstream value.
Evidence access
Publisher abstract
Marketing Science publisher abstract and issue metadata; setting, model and centrality results are reported by the journal.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.