Why has the adoption rate of Kushki's tokenization feature declined among new merchants in the past month?

Introduction

The recent decline in Kushki's tokenization feature adoption among new merchants is a critical issue that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product strategy.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose a comprehensive plan for validation and resolution.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to the tokenization feature in the past 1-2 months?

Why it matters: Recent changes could directly impact adoption rates. Expected answer: Yes, there was a UI update. Impact on approach: If yes, we'd focus on the change's impact on user experience.

• Considering the specificity to new merchants, I'm wondering about our onboarding process. Have we made any changes to how we introduce or explain the tokenization feature to new merchants?

Why it matters: Changes in communication could affect understanding and adoption. Expected answer: No changes to onboarding. Impact on approach: If no, we'd look more closely at the feature's perceived value or external factors.

• Given the focus on adoption rate, I'm curious about our definition. How exactly are we measuring "adoption" of the tokenization feature?

Why it matters: Ensures we're analyzing the correct metric. Expected answer: Adoption is measured by active usage within the first 30 days. Impact on approach: This would help us focus on specific timeframes and user behaviors.

• Thinking about potential technical issues, have there been any reported problems or increased error rates with the tokenization feature recently?

Why it matters: Technical issues could directly impact adoption. Expected answer: No significant increase in error rates. Impact on approach: If no, we'd shift focus to user perception and value proposition.