What caused the sudden 30% decrease in Tonal's strength score improvements for new users last week?

Introduction

The sudden 30% decrease in Tonal's strength score improvements for new users last week is a critical issue that demands immediate attention. This metric directly reflects the core value proposition of Tonal's smart home gym system, which promises personalized strength training and measurable progress. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term implications.

Step 1

Clarifying Questions (3 minutes)

• Given the abrupt nature of the decrease, I'm wondering about recent system changes. Have there been any software updates or algorithm adjustments in the past two weeks?

Why it matters: Software changes could directly impact strength score calculations. Expected answer: Yes, a minor update was pushed last week. Impact on approach: If confirmed, we'd prioritize investigating the update's impact.

• Considering user segments, I'm curious about the distribution of this decrease. Is the 30% drop consistent across all new user demographics, or are certain groups more affected?

Why it matters: Helps identify if the issue is universal or specific to certain user types. Expected answer: The decrease is more pronounced in users aged 40+. Impact on approach: We'd focus on factors that might disproportionately affect older users.

• Thinking about external factors, has there been any significant change in the onboarding process or initial workout recommendations for new users recently?

Why it matters: Changes in initial user experience could affect early strength improvements. Expected answer: No major changes to onboarding in the last month. Impact on approach: If confirmed, we'd look more closely at technical or user behavior factors.

• Regarding data integrity, I'm wondering about the reliability of our measurement systems. Have there been any reported issues with strength assessment accuracy or data collection in the past month?

Why it matters: Ensures we're not chasing a phantom problem due to faulty data. Expected answer: No known issues with data collection or accuracy. Impact on approach: If confirmed, we'd focus on actual performance issues rather than data anomalies.