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Company focus

Meetup
Product Improvement Hard Member-only

How can Meetup enhance its event recommendation algorithm to better match users with relevant groups and activities?

Prepared by NextSprints

15 mins
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Data Analysis Product Strategy User Segmentation Social Media Event Management Community Building User Engagement Personalization Social Networking Algorithm Optimization Event Discovery
Product Management Improvement Question: Enhancing Meetup's event recommendation algorithm for better user-group matching

Introduction

To enhance Meetup's event recommendation algorithm for better user-group matching, we need to dive deep into user behavior, preferences, and the current system's limitations. I'll outline a comprehensive approach to improve the algorithm, focusing on user segmentation, pain point analysis, and innovative solutions.

Step 1

Clarifying Questions (5 mins)

  • Looking at Meetup's position in the market, I'm curious about the current user engagement metrics. Could you share some insights on the average user's monthly active days and the percentage of users who attend events they've RSVP'd to?

Why it matters: This helps us understand the baseline engagement and identify areas for improvement. Expected answer: 5-7 active days per month, with a 60-70% attendance rate for RSVP'd events. Impact on approach: Lower engagement would shift focus to activation, while higher engagement might prioritize retention and diversification.

  • Considering the evolving landscape of social networking and event discovery, how does Meetup currently differentiate itself from competitors like Facebook Events or Eventbrite?

Why it matters: Helps identify unique selling points to leverage in the recommendation algorithm. Expected answer: Meetup focuses on community-building and recurring interest-based gatherings. Impact on approach: Would emphasize recommending consistent group participation over one-off events.

  • Given the importance of data in recommendation systems, what types of user data does Meetup currently collect and utilize in its algorithm?

Why it matters: Determines the scope of available data and potential areas for expansion. Expected answer: User interests, past event attendance, location data, and group interactions. Impact on approach: Limited data would require focus on improving data collection, while rich data would allow for more sophisticated algorithmic improvements.

  • In terms of business objectives, is the primary goal of this improvement to increase overall user engagement, or are there specific metrics like new user activation or group creation that we're targeting?

Why it matters: Aligns our solution with broader company goals and KPIs. Expected answer: Balanced approach, with a slight emphasis on increasing repeat attendance. Impact on approach: Would tailor recommendations to encourage consistent participation in groups.

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Updated Jan 22, 2025