Let's break down the analysis of the situation step by step:
Clarifying Questions:
Is the 15% decrease in Friends accept rate consistent across all user segments or are there specific groups affected more than others?
Were there any significant changes in the user interface or functionality of the notification system?
Did the decrease in Friends accept rate result in any observable impact on user engagement or other key metrics?
Are there any patterns in the timing of the notification system's launch and the decrease in Friends accept rate?
Have there been any user complaints or feedback regarding the new notification system?
Product and Objective:
Product: New Notification System
Objective/Goal: Increase Friends accept rate and maintain or improve user engagement.
Hypotheses:
Visibility Issue: The new notification system might not be as prominent, causing users to overlook friend requests.
User Experience Disruption: The new system might have introduced friction or confusion, leading to users avoiding or delaying accepting friend requests.
Notification Fatigue: Users might be receiving an increased number of notifications overall, causing them to ignore friend requests.
Algorithmic Mismatch: The new system might be recommending less relevant friend suggestions, leading to fewer acceptances.
Mobile vs. Desktop Discrepancy: The new system might be better suited for one platform (e.g., mobile) than the other, impacting accept rates.
Social Network Saturation: Users might be reaching a saturation point in their friend connections, reducing their willingness to accept new requests.
Privacy Concerns: Users might be hesitant to accept new friend requests due to concerns about privacy and sharing personal information.
Operationalizing Hypotheses:
Visibility Issue: Compare the click-through rates and impressions of friend request notifications before and after the new system's launch. Visualize with line charts.
User Experience Disruption: Conduct user surveys to gather feedback on the usability of the new system. Analyze completion rates and qualitative responses.
Notification Fatigue: Analyze user engagement with other types of notifications (e.g., likes, comments) before and after the new system's launch. Use stacked bar charts.
Algorithmic Mismatch: Compare the relevance scores of friend suggestions before and after the new system's launch. Utilize a scatter plot or heat map.
Mobile vs. Desktop Discrepancy: Segment user data based on platform and compare friend accept rates. Visualize with a grouped bar chart.
Social Network Saturation: Analyze the distribution of friend counts among users and correlate it with friend accept rates. Create a histogram.
Privacy Concerns: Survey users about their concerns regarding friend requests and privacy. Display results using a pie chart.
Conclusion and Recommendation:
Based on the analysis, it's evident that the new notification system has negatively impacted the Friends accept rate. To address this issue and improve the user experience, I recommend a two-fold approach:
Enhance Visibility: Make the friend request notifications more noticeable and distinguishable within the notification feed. Consider using bold text or a different color to attract attention.
Usability Optimization: Conduct a thorough usability review of the new notification system. Implement design changes and user interface enhancements to streamline the friend request acceptance process and minimize user confusion.
Regularly monitor and track the accept rate after implementing these changes to assess their effectiveness and iterate further if necessary.