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Introduction
Defining success metrics for Instagram's Verified badge is crucial for ensuring the feature's effectiveness and alignment with broader business goals. To approach this product success metrics problem, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders.
Framework Overview
I'll follow a simple success metrics framework covering product context, success metrics hierarchy.
Step 1
Product Context
The Verified badge on Instagram is a blue checkmark that appears next to an account's name, indicating that Instagram has confirmed the account is the authentic presence of a notable public figure, celebrity, or global brand. This feature aims to combat impersonation and provide users with confidence in the authenticity of high-profile accounts.
Key stakeholders include:
- Users: Seeking reliable information and authentic interactions
- Verified account holders: Protecting their brand and reputation
- Instagram: Maintaining platform integrity and user trust
- Advertisers: Ensuring partnerships with genuine influencers
User flow:
- Account holder applies for verification
- Instagram reviews the application
- If approved, the badge appears on the account profile
- Users see the badge when interacting with verified accounts
The Verified badge fits into Instagram's broader strategy of fostering trust, authenticity, and safety on the platform. It also supports the company's monetization efforts by creating a more reliable environment for influencer marketing and advertising.
Compared to competitors like Twitter and Facebook, Instagram's verification process is relatively stringent, emphasizing notability and authenticity over mere identity confirmation.
Product Lifecycle Stage: The Verified badge is in the maturity stage, having been introduced several years ago and now widely recognized by users. However, there's ongoing refinement of the verification process and criteria.
Step 2
Goals
| Core Goals | User Goals | Technical Goals | Business Goals |
|---|---|---|---|
| Increase trust and authenticity on the platform | Easily identify genuine accounts of public figures and brands | Maintain a robust and scalable verification system | Enhance platform value for advertisers and partners |
| Reduce impersonation and fraud | Access reliable information from verified sources | Minimize false positives and negatives in the verification process | Increase user engagement and retention |
| Improve overall user experience | Build connections with authentic accounts | Ensure seamless integration of the badge across all Instagram features | Support growth of influencer marketing ecosystem |
Step 3
North Star Metric
Proposed North Star Metric (NSM): Verified Account Engagement Rate
Definition: The average engagement rate (likes, comments, shares) on posts from verified accounts compared to non-verified accounts with similar follower counts.
Calculation: (Total engagements on verified account posts / Total verified account followers) / (Total engagements on comparable non-verified account posts / Total comparable non-verified account followers)
This metric captures success because it demonstrates the value and impact of the Verified badge. A higher engagement rate for verified accounts indicates that users trust and interact more with these accounts, validating the badge's purpose.
All stakeholders derive value from this metric:
- Users benefit from more engaging, trustworthy content
- Verified account holders see increased engagement
- Instagram benefits from higher overall platform engagement
- Advertisers gain more valuable partnerships with verified accounts
Hypothetical data: If the Verified Account Engagement Rate is 1.5, it means verified accounts receive 50% more engagement than comparable non-verified accounts. An increasing trend would indicate growing trust and value in the verification system.
Breakdown of North Star Metric
Components of the NSM:
- Verified Account Engagement
- Non-Verified Account Engagement
- Follower Count Normalization
Formula breakdown: NSM = f(VE, NVE, FCN) VE = f(L_v, C_v, S_v) NVE = f(L_nv, C_nv, S_nv) FCN = f(F_v, F_nv)
Where: VE = Verified Engagement NVE = Non-Verified Engagement FCN = Follower Count Normalization L = Likes, C = Comments, S = Shares F = Followers _v = verified, _nv = non-verified
Step 4
Supporting Metrics
| Metric | Importance | Calculation | Actions |
|---|---|---|---|
| Verification Application Success Rate | Measures the quality and clarity of the verification process | (Approved applications / Total applications) * 100 | Improve guidelines or adjust criteria if too low/high |
| Time to Verification | Indicates efficiency of the verification process | Average time from application submission to decision | Optimize review process if consistently high |
| Verified Account Growth Rate | Shows the expansion of verified presence on the platform | (New verified accounts / Total verified accounts) per month | Adjust outreach or criteria if growth stagnates |
| Impersonation Report Rate | Measures the effectiveness in reducing fraud | (Impersonation reports for verified accounts / Total impersonation reports) * 100 | Strengthen verification process if rate increases |
| Verified Account Retention Rate | Indicates the ongoing value of verification | (Verified accounts active after 1 year / Total verified accounts) * 100 | Investigate churn reasons if rate decreases |
Step 5
Guardrail Metrics
| Key Stakeholder | Metric | Why It Matters | Threshold |
|---|---|---|---|
| Users | User Trust Score | Ensures overall platform integrity | >80% positive |
| Verified Account Holders | Account Health Score | Maintains quality of verified accounts | >90% compliance |
| False Positive Rate | Protects against mistaken verifications | <1% of approvals | |
| Advertisers | Brand Safety Score | Ensures advertiser confidence | >95% safe interactions |
User Trust Score matters because it reflects the overall perception of the platform's authenticity. If it drops below 80%, it could indicate that the Verified badge is losing its meaning or that there are too many unverified but notable accounts.
Account Health Score is crucial because it ensures that verified accounts continue to meet high standards. A score below 90% might suggest that some verified accounts are engaging in behavior that could undermine the badge's credibility.
False Positive Rate is critical to maintain the exclusivity and trustworthiness of the Verified badge. A rate above 1% could lead to a flood of undeserving verified accounts, diluting the badge's value.
Brand Safety Score is vital for advertisers' confidence in partnering with verified accounts. A score below 95% might indicate increased risk for brands, potentially leading to reduced ad spend on the platform.
Step 6
Trade-off Metrics
-
Verification Approval Rate vs. Badge Exclusivity
- Trade-off: Increasing approvals may dilute the badge's value
- Balance: Maintain strict criteria while expanding education on eligibility
-
User Engagement vs. Content Authenticity
- Trade-off: Highly engaging content may not always be the most authentic
- Balance: Promote verified accounts that maintain high engagement and authenticity scores
-
Verification Speed vs. Accuracy
- Trade-off: Faster verification may lead to more errors
- Balance: Implement a tiered review system with quick initial checks and thorough secondary reviews
Step 7
Counter Metrics
-
Verified Account Complaint Rate
- Purpose: Identify misuse of verified status
- Helps avoid: Erosion of trust in the verification system
- Action if high: Review and potentially revoke verification for problematic accounts
-
Non-Verified Notable Account Satisfaction
- Purpose: Ensure the verification system isn't alienating worthy accounts
- Helps avoid: Platform abandonment by influential but unverified users
- Action if low: Review verification criteria and provide clearer guidance
-
Verified Badge Click-through Rate
- Purpose: Measure user interest and understanding of the badge
- Helps avoid: The badge becoming ignorable or misunderstood
- Action if low: Improve badge design or educate users on its significance
Strategic Initiatives
-
AI-Assisted Verification Process
- Rationale: Improve efficiency and accuracy of verifications
- Potential impact: Increase in Verification Application Success Rate and decrease in Time to Verification
- Challenges: Ensuring AI decisions are unbiased and accurate
-
Tiered Verification System
- Rationale: Provide more nuanced recognition of account notability
- Potential impact: Increase in Verified Account Growth Rate and Non-Verified Notable Account Satisfaction
- Challenges: Communicating the differences between tiers to users
-
Verified Account Mentorship Program
- Rationale: Improve quality of content from verified accounts
- Potential impact: Increase in Verified Account Engagement Rate and Account Health Score
- Challenges: Scaling the program effectively
Conclusion
Emerging technologies like blockchain could potentially impact verification by providing decentralized identity solutions. AI advancements may also allow for more sophisticated impersonation detection.
In the future, success metrics might need to evolve to include measures of cross-platform verification integration or real-world impact of verified accounts.