Why has the conversion rate for mortgage refinance applications on NerdWallet decreased by 20% since the new calculator feature was launched?

Introduction

The recent 20% decrease in conversion rate for mortgage refinance applications on NerdWallet following the launch of a new calculator feature is a critical issue that demands immediate attention. This significant drop in a key performance metric could have far-reaching implications for user satisfaction, revenue, and overall product success. To address this complex problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking the new calculator might be directly related to the conversion drop. Has there been any change in user feedback or support tickets since the launch?

Why it matters: This could indicate if users are struggling with the new feature. Expected answer: An increase in negative feedback or support requests. Impact on approach: If confirmed, we'd focus on usability issues in the new calculator.

• Considering potential data discrepancies, has there been any change in how conversion rate is measured or tracked since the new feature launch?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes in measurement methodology. Impact on approach: If there were changes, we'd need to reassess the actual impact.

• Given market fluctuations, have there been any significant changes in mortgage rates or lending policies during this period?

Why it matters: External factors could be influencing user behavior. Expected answer: Some market changes, but not drastic enough to explain a 20% drop. Impact on approach: If significant changes occurred, we'd need to factor in market conditions.

• Thinking about user segments, has the decrease been uniform across all user groups, or are certain segments more affected?

Why it matters: Helps identify if the issue is universal or specific to certain users. Expected answer: The decrease varies across segments. Impact on approach: If specific segments are more affected, we'd tailor our solution accordingly.