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Product Management RCA Question: Investigating AI-powered content recommendation engagement drop for Sprinklr
Image of author vinay

Vinay

Updated Dec 3, 2024

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Why has the engagement rate for Sprinklr's AI-powered content recommendations dropped by 15% over the past month?

Data Analysis Problem Solving Technical Understanding SaaS Social Media Management AI/ML
Product Strategy Data Analysis Engagement Metrics Root Cause Analysis AI Recommendations

Introduction

The recent 15% drop in engagement rate for Sprinklr's AI-powered content recommendations is a critical issue that demands immediate attention. This analysis will systematically investigate potential root causes, validate hypotheses, and propose targeted solutions to address the engagement decline 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 have been a recent algorithm update. Has there been any change to the AI recommendation system in the past month?

Why it matters: Algorithm changes can significantly impact recommendation quality and user engagement. Expected answer: Yes, there was a minor update to improve personalization. Impact on approach: If confirmed, we'd focus on analyzing the algorithm change and its effects.

  • Considering user segments, I'm curious about the distribution of the engagement drop. Is the 15% decrease uniform across all user types, or are certain segments more affected?

Why it matters: Identifying specific affected segments can help pinpoint the root cause. Expected answer: The drop is more pronounced among newer users. Impact on approach: We'd investigate onboarding processes and initial user experience if this is the case.

  • Thinking about external factors, have there been any significant changes in content supply or quality from content providers in the last month?

Why it matters: Content quality directly impacts engagement rates. Expected answer: No major changes reported from content providers. Impact on approach: If confirmed, we'd focus more on internal factors and user behavior.

  • Considering system performance, have there been any reported issues with recommendation loading times or errors in the past month?

Why it matters: Technical issues can severely impact user engagement. Expected answer: Some intermittent slowdowns were reported but deemed minor. Impact on approach: We'd investigate the correlation between performance issues and engagement drops.

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