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Area of Science:

  • Marketing
  • Data Science
  • Sociology

Background:

  • Customer engagement in online brand communities is rising.
  • Identifying user segments and reducing churn are critical marketing challenges.
  • User activity varies significantly across different segments.

Purpose of the Study:

  • To segment online brand community users based on user-generated content (UGC).
  • To identify characteristics of each user segment.
  • To provide strategies for reducing user churn in online brand communities.

Main Methods:

  • Collected user post data from a Chinese online brand community (July 2012 - Dec 2019).
  • Employed text mining and clustering techniques for user segmentation.
  • Analyzed segment differences and churn rates.

Main Results:

  • Identified three user segments: information-oriented, entertainment-oriented, and multi-motivation.
  • Entertainment-oriented users exhibited the highest activity levels.
  • Multi-motivation users demonstrated the lowest churn probability (0.607 times that of information or entertainment-focused users).

Conclusions:

  • User-generated content (UGC) provides a basis for effective online community segmentation.
  • Targeting multi-motivation users can significantly reduce churn rates.
  • Findings offer actionable insights for marketers to enhance customer retention in online brand communities.