EXPRESS: Consumer Interactions and Peer Effects in Socially-Connected Digital Products

The paper explores peer effects in user churn within a digital socially-connected platform and investigates how firms can leverage peer effects and network structure for customer relationship management (CRM). The data come from a massively-multiplayer online game, where gamer social ties are endogenous. We build a two-stage structural model to capture network formation and peer effects in churn. Unobserved gamer heterogeneity inferred from network formation corrects for endogeneity bias in peer effects. The main findings are: (i) Peer effects substantially amplify intervention effectiveness, with an average social multiplier of 2.48. Critically, the full model with unobserved gamer heterogeneity reveals substantial cross-network variation in social multipliers that the restricted model largely masks. (ii) Users vary far more in how they influence peers' retention than in their own likelihood of retention. (iii) User's network value is driven primarily by network centrality measures, unlike user's direct value which correlates more with individual characteristics.

Authors

Publication Details

Journal
Journal of Marketing Research
Published
2026-06-16
DOI
https://doi.org/10.1177/00222437261463518
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

EXPRESS: Consumer Interactions and Peer Effects in Socially-Connected Digital Products

Yulia Nevskaya, Yijun Chen
Journal of Marketing Research
Digital Marketing and Social Media
article

EXPRESS: Consumer Interactions and Peer Effects in Socially-Connected Digital Products

Yulia Nevskaya, Yijun Chen
article en

Abstract

The paper explores peer effects in user churn within a digital socially-connected platform and investigates how firms can leverage peer effects and network structure for customer relationship management (CRM). The data come from a massively-multiplayer online game, where gamer social ties are endogenous. We build a two-stage structural model to capture network formation and peer effects in churn. Unobserved gamer heterogeneity inferred from network formation corrects for endogeneity bias in peer effects. The main findings are: (i) Peer effects substantially amplify intervention effectiveness, with an average social multiplier of 2.48. Critically, the full model with unobserved gamer heterogeneity reveals substantial cross-network variation in social multipliers that the restricted model largely masks. (ii) Users vary far more in how they influence peers' retention than in their own likelihood of retention. (iii) User's network value is driven primarily by network centrality measures, unlike user's direct value which correlates more with individual characteristics.

Journal of Marketing Research
Openalex Percentile: Top 2%
Digital Marketing and Social Media
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