What caused the sudden 30% decrease in conversion rates for Instapage's A/B testing feature last week?

Introduction

The sudden 30% decrease in conversion rates for Instapage's A/B testing feature last week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and business.

I'll approach this problem by first clarifying the context, ruling out external factors, and then diving deep into the product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be related to a recent product update. Has there been any significant change to the A/B testing feature in the past two weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a UI update. Impact on approach: If yes, I'd focus on the update's impact on user experience and workflow.

• Considering the magnitude of the drop, I'm wondering about potential technical issues. Have there been any reported errors or performance degradation in the A/B testing feature?

Why it matters: Technical issues can severely impact conversion rates. Expected answer: No major errors reported, but some users mentioned slower load times. Impact on approach: If performance issues are confirmed, I'd prioritize technical investigation.

• Given that this is a conversion rate decrease, I'm curious about user behavior changes. Has there been any shift in the types of users accessing the A/B testing feature recently?

Why it matters: Different user segments may interact with the feature differently. Expected answer: No significant change in user demographics noted. Impact on approach: If user composition hasn't changed, I'd focus more on the feature itself rather than user-related factors.

• Considering potential data anomalies, I'm wondering about the reliability of our tracking. Has there been any change in how we measure or calculate the conversion rate for this feature?

Why it matters: Metric definition changes can cause apparent performance shifts. Expected answer: No changes to the metric definition or tracking system. Impact on approach: If confirmed, I'd rule out data tracking issues and focus on actual performance factors.