Widget Visual
Overview:
The "Monthly Active People" widget illustrates the percentage of users who have been active on the platform within a given month, as compared to the total number of users who have claimed their accounts.
Metrics Explained:
Monthly Active People
Definition: The count of users who have shown activity on the platform in the past month.
Significance: Represents the level of user engagement and activity over a monthly span.
Claimed Accounts
Definition: The cumulative number of users who have successfully claimed and set up their accounts on the platform.
Significance: Indicates the total potential user base, providing context to the monthly active users.
Metric Interplay:
The displayed percentage is calculated by comparing Monthly Active People to Claimed Accounts. If the percentage is high, it indicates that a majority of those who've claimed their accounts are consistently using the platform monthly. A lower percentage might point to a gap between account creation and active platform usage.
Use Cases:
Engagement Analysis: Enables an understanding of how many of the registered users are actively engaging with the platform on a monthly basis.
User Retention: A tool for tracking monthly retention and deducing patterns that might influence user activity.
FAQs:
Q: What activities count towards a user being deemed "active" monthly?
A: Activities such as logging in, viewing, posting, or interacting in any other way within the month are typically counted. However, specifics may vary based on the platform.
Q: Why is there a gap between claimed accounts and monthly active users?
A: Not all users who claim their accounts may remain active or use the platform regularly. The gap can provide insights into areas for user re-engagement.
Troubleshooting:
Issue: My "Monthly Active People" seems unusually low compared to "Claimed Accounts".
Solution: Ensure there haven't been any platform issues preventing user activity. If no apparent issues arise, consider strategies to re-engage dormant users or investigate further for potential data discrepancies.