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Company focus

GupShup

Why has GupShup's chatbot builder tool experienced a 50% increase in error rates during bot deployments in the past 48 hours?

Prepared by NextSprints

15 mins
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Problem Solving Data Analysis Technical Understanding SaaS AI/ML Customer Service Root Cause Analysis Chatbots API Integration Error Diagnostics Deployment Optimization
Product Management Root Cause Analysis Question: Investigating sudden increase in GupShup chatbot deployment errors

Introduction

GupShup's chatbot builder tool has experienced a 50% increase in error rates during bot deployments in the past 48 hours. This sudden spike in errors is concerning and requires immediate attention to maintain the platform's reliability and user satisfaction. I'll approach this issue systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

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 this could be related to a recent update. Has there been any system or software update in the last week?

Why it matters: Recent changes often correlate with sudden performance shifts. Expected answer: Yes, a minor update was pushed 3 days ago. Impact on approach: If confirmed, I'd focus on changes introduced in that update.

  • Considering the scale of the issue, I'm wondering about its distribution. Is this increase in error rates uniform across all users or concentrated in specific segments?

Why it matters: Helps determine if it's a systemic issue or limited to certain user groups. Expected answer: The increase is more pronounced for enterprise users. Impact on approach: I'd prioritize investigating enterprise-specific features or integrations.

  • Given the nature of chatbot deployments, I'm curious about the error types. Are these primarily syntax errors, integration failures, or runtime errors?

Why it matters: Different error types point to different root causes. Expected answer: Mostly integration failures with third-party APIs. Impact on approach: I'd focus on recent changes in API integrations or external dependencies.

  • Considering potential external factors, have there been any significant changes in usage patterns or traffic in the last 48 hours?

Why it matters: Unusual traffic spikes or changes in user behavior could strain the system. Expected answer: No significant changes in overall traffic, but a 20% increase in API calls. Impact on approach: I'd investigate if the increased API calls are related to the errors.

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NextSprints

Updated Mar 29, 2025