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Company focus

Restaurant365

What factors are contributing to the 30% increase in customer support tickets related to Restaurant365's payroll processing feature in the last quarter?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving Cross-Functional Collaboration Restaurant Technology SaaS Fintech Root Cause Analysis SaaS Customer Support Payroll Systems Restaurant Management
Product Management Root Cause Analysis Question: Investigating surge in payroll support tickets for restaurant software

Introduction

The recent 30% increase in customer support tickets related to Restaurant365's payroll processing feature is a critical issue that demands immediate attention. This surge in support requests not only impacts customer satisfaction but also strains our support resources and potentially signals underlying problems with the feature itself. To address this challenge, 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.

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 recent change in the payroll processing feature. Has there been any significant update or modification to this feature in the last quarter?

Why it matters: Recent changes often correlate with increased support tickets. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on the update's impact; if no, we'd look at other factors.

  • Considering user segments, I'm wondering if this increase is uniform across all customer types. Are we seeing this 30% increase consistently across different restaurant sizes or types?

Why it matters: Helps identify if the issue is universal or specific to certain user groups. Expected answer: The increase is more pronounced in larger restaurant chains. Impact on approach: If segmented, we'd tailor solutions to specific user groups; if uniform, we'd look for system-wide issues.

  • Given the nature of payroll processing, I'm curious about the timing of these tickets. Is there a pattern in when these support tickets are being submitted, such as around specific payroll cycles?

Why it matters: Temporal patterns can indicate systemic issues or user behavior trends. Expected answer: Tickets spike at the end of each month. Impact on approach: If cyclical, we'd investigate end-of-month processes; if random, we'd look at broader system issues.

  • Considering the metric itself, I'm wondering about the nature of these support tickets. Has there been any change in how we categorize or track payroll-related support tickets in the last quarter?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes in ticket categorization. Impact on approach: If changed, we'd need to re-baseline our data; if unchanged, we can trust the 30% increase figure.

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NextSprints

Updated Jan 22, 2025