Why has Lenskart's virtual try-on feature seen a 30% drop in usage over the past month?

Introduction

Lenskart's virtual try-on feature, a cornerstone of their digital eyewear shopping experience, has encountered a significant 30% drop in usage over the past month. This decline raises concerns about user engagement and potential impacts on conversion rates. I'll approach this issue systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term strategies to address the problem.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has this 30% drop been compared to the same period last year?

Why it matters: Seasonal trends could explain usage patterns. Expected answer: No significant seasonal variation observed. Impact on approach: If seasonal, we'd focus on annual patterns; if not, we'd investigate recent changes.

• Considering user segments, I'm curious about the distribution of the drop. Is the 30% decrease uniform across all user groups or concentrated in specific segments?

Why it matters: Helps pinpoint if it's a global issue or specific to certain users. Expected answer: Drop is more pronounced among new users. Impact on approach: If segment-specific, we'd tailor solutions to those groups; if uniform, we'd look at platform-wide issues.

• Thinking about recent updates, have there been any changes to the virtual try-on feature or related systems in the past 1-2 months?

Why it matters: Recent changes often correlate with performance shifts. Expected answer: Minor UI update implemented 6 weeks ago. Impact on approach: If changes occurred, we'd scrutinize their impact; if not, we'd look at external factors or gradual user behavior shifts.

• Considering technical aspects, has there been any change in the definition of the usage metric or the systems measuring it?

Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No changes to metric definition or measurement systems. Impact on approach: If changed, we'd recalibrate our analysis; if not, we'd focus on actual usage patterns.