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Company focus

Riskified

What factors are contributing to the sudden drop in merchant adoption of Riskified's Policy Protect feature in the APAC region?

Prepared by NextSprints

15 mins
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Data Analysis Market Understanding Problem-Solving E-commerce Fraud Prevention SaaS E-Commerce Root Cause Analysis Feature Adoption Fraud Prevention APAC Market
Product Management Root Cause Analysis Question: Investigating sudden drop in Riskified's Policy Protect adoption in APAC region

Introduction

The sudden drop in merchant adoption of Riskified's Policy Protect feature in the APAC region is a critical issue that requires immediate attention. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term and long-term implications for our product strategy.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Given the regional specificity, I'm wondering about market dynamics. Has there been any significant change in the APAC e-commerce landscape recently?

Why it matters: Understanding regional context is crucial for pinpointing the issue. Expected answer: Possible shifts in market trends or new regulations. Impact on approach: Would focus on regional-specific factors if confirmed.

  • Considering the feature's core functionality, I'm curious about recent changes. Have there been any updates to Policy Protect in the last 3-6 months?

Why it matters: Product changes often correlate with adoption fluctuations. Expected answer: Information on recent feature updates or lack thereof. Impact on approach: Would investigate feature-specific issues if changes occurred.

  • Thinking about user segments, I'm interested in the adoption patterns. Are we seeing this drop across all merchant types, or is it concentrated in specific segments?

Why it matters: Helps narrow down potential user-specific issues. Expected answer: Data on affected merchant segments. Impact on approach: Would tailor analysis to specific user groups if applicable.

  • Reflecting on the term "sudden," I'm wondering about the timeframe. Over what period did we observe this drop in adoption?

Why it matters: Helps correlate the issue with potential triggering events. Expected answer: Specific timeframe of the adoption decline. Impact on approach: Would align investigation with the identified timeline.

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Updated Mar 29, 2025