What retention metrics would you use if you were the PM for Instagram Stories?

Introduction

Retention metrics for Instagram Stories are crucial for measuring user engagement and the feature's overall success. To approach this product success metrics problem effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Step 1

Product Context

Instagram Stories is a feature within the Instagram app that allows users to share photos and videos that disappear after 24 hours. Key stakeholders include users (content creators and viewers), advertisers, and Instagram/Meta leadership.

User flow:

1. Creation: Users capture or upload content, add filters/stickers/text
2. Publishing: Content is shared to user's Story
3. Consumption: Followers view Stories in a tappable, chronological format
4. Interaction: Viewers can react, reply, or share Stories

Instagram Stories fits into Meta's broader strategy of increasing user engagement and time spent in-app, while also providing new advertising opportunities. It competes directly with Snapchat's core functionality and TikTok's short-form video content.

Product Lifecycle Stage: Mature - Stories has been widely adopted but continues to evolve with new features and integrations.

Step 2

Goals

Step 3

North Star Metric

Proposed North Star Metric (NSM): Daily Active Story Users (DASU)

Definition: The number of unique users who either create or view at least one Story in a 24-hour period.

Calculation: Count of unique users who interact with Stories (create or view) within a rolling 24-hour window.

This metric captures both content creation and consumption, reflecting overall engagement with the Stories feature. It aligns with user goals (expression and connection), business goals (engagement and retention), and technical goals (reliable content delivery).

Hypothetical data: If DASU is trending upwards week-over-week, it indicates growing adoption and engagement. A plateau might suggest market saturation or the need for feature enhancements.

Breakdown of North Star Metric

DASU can be broken down into its component parts:

Formula: DASU = f(SC, SV) Where: SC (Story Creators) = f(NSC, RSC) SV (Story Viewers) = f(NSV, RSV)

NSC = New Story Creators RSC = Returning Story Creators NSV = New Story Viewers RSV = Returning Story Viewers

Step 4

Supporting Metrics

Step 5

Guardrail Metrics

Story Load Time is critical because slow-loading Stories can frustrate users and decrease engagement. If this metric exceeds the threshold, it could negatively impact the DASU by discouraging Story viewing.

Ad Viewability ensures that advertisers get value from the platform. A low viewability rate could lead to reduced ad spend, indirectly affecting resources available for Stories feature development.

App Crash Rate, if too high, could deter users from engaging with Stories altogether, directly impacting the DASU.

Story Upload Success Rate is essential for content creators. A low success rate could discourage Story creation, reducing the content available for viewers and negatively impacting the DASU.

Step 6

Trade-off Metrics

1. Ad Frequency vs. User Satisfaction

   • Trade-off: Increasing ad frequency boosts revenue but may decrease user satisfaction
   • Balance: Monitor user engagement metrics alongside ad revenue, adjusting frequency based on user behavior

2. Content Ephemerality vs. Engagement Duration

   • Trade-off: Longer Story availability might increase views but reduce urgency to check daily
   • Balance: Experiment with Story duration options, measuring impact on daily and weekly active users

3. Feature Complexity vs. User Adoption

   • Trade-off: Adding new Story features can drive engagement but may overwhelm some users
   • Balance: Implement progressive feature rollouts, tracking adoption rates and user feedback

Step 7

Counter Metrics

1. Story Abandonment Rate

   • Purpose: Identify potential issues with content quality or relevance
   • Calculation: (Stories started - Stories completed) / Stories started
   • Action if high: Improve content recommendation algorithms or creator tools

2. Daily Time Limit Reached

   • Purpose: Ensure healthy app usage and prevent burnout
   • Calculation: Users reaching self-set daily time limits / DAU
   • Action if increasing: Promote digital wellbeing features and balanced app use

3. Story Creation Churn

   • Purpose: Monitor creator retention
   • Calculation: (Previous month's creators - This month's returning creators) / Previous month's creators
   • Action if high: Analyze drop-off points in creation flow, enhance creator incentives

Strategic Initiatives

1. AI-Powered Content Recommendations

   • Rationale: Improve content relevance and increase engagement
   • Impact: Could boost Story Completion Rate and Time Spent Viewing Stories
   • Challenges: Balancing personalization with content diversity, data privacy concerns

2. Collaborative Stories

   • Rationale: Encourage more user-generated content and social interaction
   • Impact: Potential increase in Stories Created per User and Story Replies per View
   • Challenges: Moderation of multi-user content, ensuring seamless user experience

3. Integrated AR Creation Tools

   • Rationale: Enhance creativity options for Story creators
   • Impact: Could increase Stories Created per User and attract new creators
   • Challenges: Technical implementation, ensuring tools are intuitive for all user skill levels

Conclusion

Emerging technologies like AI and AR will likely play a significant role in the future of Instagram Stories, potentially impacting content creation, consumption, and advertising. Success metrics may need to evolve to capture new forms of engagement, such as AR interactions or AI-assisted content creation.

As the social media landscape continues to change, Instagram Stories' metrics should adapt to measure not just quantity of engagement, but quality and impact of interactions. This might include metrics around meaningful connections made through Stories or the platform's role in users' creative expression and personal branding.

Expand Your Perspective

• How might cultural differences impact the relevance of these metrics in various global markets?

• What ethical considerations should be taken into account when optimizing for these metrics?

• How could Instagram Stories metrics be integrated with broader Instagram and Meta ecosystem metrics for a more holistic view of user engagement?

Related Topics

• Cross-platform content strategy

• Machine learning in content recommendation systems

• Balancing user privacy with personalization in social media

• Monetization strategies for ephemeral content

• User retention in highly competitive social media landscapes