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Product Management Root Cause Analysis Question: Investigating loyalty program enrollment decline across multiple restaurant clients
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Nextsprints

Updated Jan 22, 2025

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Why has Punchh's loyalty program enrollment rate dropped by 15% across multiple restaurant clients in the past month?

Data Analysis Problem Solving Strategic Thinking Restaurant Technology Customer Loyalty SaaS
Data Analysis Customer Retention Root Cause Analysis Restaurant Tech Loyalty Programs

Introduction

The recent 15% drop in Punchh's loyalty program enrollment rate across multiple restaurant clients is a concerning trend that requires immediate attention. As we delve into this issue, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Framework overview

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

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be a seasonal component. Has this drop coincided with any particular season or holiday period?

Why it matters: Seasonal trends could explain temporary fluctuations. Expected answer: No clear seasonal correlation. Impact on approach: If seasonal, we'd focus on cyclical patterns; if not, we'd investigate other factors.

  • Considering the multi-client impact, I'm wondering about recent platform changes. Have there been any significant updates to the Punchh platform in the last 1-2 months?

Why it matters: Platform changes could affect user experience across clients. Expected answer: A minor update was rolled out. Impact on approach: If yes, we'd scrutinize the update; if no, we'd look at client-specific factors.

  • Thinking about user segments, I'm curious if this drop is uniform across all demographics. Do we see any particular user groups more affected than others?

Why it matters: Helps identify if the issue is global or segment-specific. Expected answer: The drop is relatively uniform. Impact on approach: If uniform, we'd look at broad issues; if segmented, we'd focus on specific user groups.

  • Considering potential data anomalies, I'm wondering about our measurement systems. Has there been any change in how we track or define enrollment rates recently?

Why it matters: Ensures we're not dealing with a data collection issue. Expected answer: No changes in measurement methodology. Impact on approach: If changed, we'd audit our data systems; if not, we'd focus on actual enrollment factors.

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