Introduction
The decreased adoption rate of RippleNet among new financial institutions this quarter is a critical issue that requires immediate attention. As we analyze this product challenge, I'll employ a systematic framework to identify, validate, and address the root cause while considering both short-term and long-term implications for our business.
To tackle this problem effectively, I'll start by clarifying the context, then rule out external factors before diving deep into our product ecosystem. We'll break down the metrics, gather relevant data, form hypotheses, and conduct a thorough root cause analysis. Finally, we'll develop a comprehensive plan to validate our findings and implement solutions.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Changes in onboarding could directly impact adoption rates. Expected answer: No significant changes to onboarding processes. Impact on approach: If changes were made, we'd focus on those specific alterations.
Why it matters: Different institution types may have varying adoption barriers. Expected answer: Some shift towards smaller, regional banks. Impact on approach: We'd analyze adoption rates by institution type and size.
Why it matters: Competitive pressures could be drawing potential adopters away. Expected answer: No significant changes from major competitors. Impact on approach: If there were changes, we'd need to reassess our value proposition.
Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No changes to the definition or measurement of adoption rate. Impact on approach: If changed, we'd need to recalibrate our historical data for accurate comparison.
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