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Stable Money Onboarding Teardown:

Link: Stable Money | Onboarding Teardown

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Activation Metrics:

Activation Hypotheses and Metrics for Achieving 90-Day Retention Goal

As we strive to achieve our 90-day retention goal, I've identified key activation hypotheses based on our user data and behaviour patterns. Below, I outline each hypothesis along with suggested metrics to measure their effectiveness:

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1. Completion of Aadhaar and PAN Verification Early Increases Activation and Retention Metrics:

* Percentage of users completing Aadhaar verification within 2 days.

* Percentage of users completing PAN verification within 2 days.

* Conversion rate from D0 to D7 for users completing both verifications within 2 days.

* Retention rate at D90 for users completing both verifications within 2 days.

Explanation: Early completion of Aadhaar and PAN verifications demonstrates initial commitment and trust from users. This hypothesis suggests that users who complete these verifications early are more likely to activate and remain engaged over 90 days, contributing to higher retention rates.

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2. Profile Completion Accelerates User Activation and Retention Metrics:

* Percentage of users completing basic profile information within 1 day.

* Average time taken to complete full profile after initial sign-up.

* Retention rate at D30 for users with completed profiles within 1 day.

* Percentage of users who engage in additional features after profile completion.

Explanation: Swift completion of the profile indicates high user intent and initial engagement. Users who complete their profiles early are expected to activate faster and exhibit sustained engagement, thus enhancing their likelihood of staying with our product over the 90-day period.

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3. Engagement with Emergency Fund Goal Setting and FD Finder Feature Enhances Long-Term Retention Metrics:

* Percentage of users setting Emergency fund goals within 3 days.

* Number of unique FDs searched within the first week.

* Retention rate at D90 for users who set goals and use FD finder within 3 days.

* Average number of FDs added to watchlist per user.

Explanation: Active engagement with Emergency fund feature and financial product exploration indicates a strong commitment to financial planning. Users who utilise these features early on are likely to have clearer financial objectives and hence, are expected to exhibit higher retention rates over the 90-day period.

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4. Regular Interaction with Multiple Bank Pages Increases Conversion and Retention Metrics:

* Percentage of users visiting 3+ different bank pages weekly.

* Time spent per session on bank pages.

* Conversion rate from bank page visits to Payment Success

* Retention rate at D90 for users with frequent bank page interactions.

Explanation: Continued exploration across multiple bank offerings suggests deeper user interest and engagement with financial options. Users who regularly interact with various bank pages are anticipated to convert more often and maintain higher retention rates, supporting our 90-day retention goal.

Key Considerations:

* Life Time Value (LTV) Focus: Each hypothesis and its metrics are aimed at driving sustainable user engagement and value over time.

* Data-Driven Optimization: Regular cohort analysis and refinement of metrics based on user behaviour insights will be critical to optimizing our activation strategies.

* Iterative Approach: We will continuously iterate and test these hypotheses to ensure they effectively contribute to achieving our 90-day retention goal, aligning closely with our product roadmap and user-centric focus.

By focusing on these activation hypotheses and measuring their impact through defined metrics, we aim to enhance user activation and retention, ultimately driving long-term success for our product.