2018年-Talkingdata_移动游戏数据分析指标白皮书英文版_22页_598kb

Mobile Game Data Analysis White Paper Summary

Core Content

This document provides a comprehensive overview of key data metrics used in the analysis of mobile game performance. It focuses on user acquisition, activation, revenue, retention, and churn, offering definitions, purposes, and analysis methods for each metric. The metrics are intended to be used by developers, analysts, and management to assess game health, optimize strategies, and improve user engagement and monetization.

Main Metrics and Definitions

Key Questions Addressed

• Acquisition:

  • How well are new users adapting to the game mechanism?
  • How do promotion channels affect new user acquisition?
  • Are promotion channels cheating?
  • What is the cost to acquire new users through different channels?

• Activation:

  • What is the size and stability of our user base?
  • How "sticky" are our games?
  • How do changes in the game affect user engagement and retention?

• Revenue:

  • What are user payment habits and intentions?
  • How do we convert normal users to paying users?
  • What is the relationship between active users and revenue contribution?
  • How can we analyze the impact of revenue-producing events and version updates on user churn?

• Retention & Churn:

  • How can we assess the effectiveness of promotion channels?
  • At what point do we see the most churn among new users?
  • How can we determine the effect of user engagement on churn?
  • How can we analyze the behavior of different user segments (e.g., whales, dolphins, fish)?

Notes and Recommendations

• User Acquisition:

  • DNU and DOSU help identify traffic quality and potential cheating.
  • CAC is calculated per promotion channel to evaluate ROI.
  • Weekly and monthly fake user counts are used to detect anomalies in user acquisition.

• User Activation:

  • DAU, WAU, and MAU are used to assess user engagement and stability.
  • DAU/MAU ratio should not drop below 0.2 to ensure acceptable user retention.

• User Engagement:

  • DEC and DAOT/AT help understand how often and how long users engage with the game.
  • Changes in engagement levels can indicate the impact of updates or promotions.

• Revenue Analysis:

  • MPR and APA are used to assess payment behavior and user base stability.
  • ARPU and ARPPU help estimate revenue per user and evaluate monetization strategies.
  • LTV is a long-term metric that reflects the value of a user over their lifetime in the game.

• Retention & Churn:

  • Retention rates (Day 1, Day 3, Day 7, Day 30) are used to measure user satisfaction and "stickiness".
  • Churn rates help identify problematic periods and user segments.
  • Churn analysis should be combined with retention and engagement data for deeper insights.

• Reporting and Analysis:

  • Daily, weekly, monthly, quarterly, and annual reports are recommended for tracking performance over different time frames.
  • Data metrics should follow "Occam's Razor" to avoid overcomplication.
  • Cross-analysis of metrics with promotion channel data is essential for strategic decision-making.

Additional Metrics

• PCU [Peak Concurrent Users]: The highest number of users online at any given time.
• ACU [Average Concurrent Users]: The average number of users online during a period.
• New Users Conversion Rate: Measures the effectiveness of promotion channels.
• K-Factor: Indicates whether the game's user base is growing or shrinking based on invitation and conversion rates.

Conclusion

This white paper outlines essential data metrics for mobile game performance analysis, emphasizing the importance of user acquisition, activation, engagement, and monetization. It encourages a focused and strategic approach to data analysis, highlighting the need for cross-metric evaluation and regular reporting to maintain and improve game performance.