Student pricing is available for eligible university email holders. View plans

NextSprints
NextSprints Icon NextSprints Logo
Product Design

Master the art of designing products

Product Improvement

Identify scope for excellence

Product Success Metrics

Learn how to define success of product

Product Root Cause Analysis

Ace root cause problem solving

Product Trade-Off

Navigate trade-offs decisions like a pro

All Questions

Explore all questions

Meta (Facebook) PM Interview Course

Practice Meta-focused PM cases

Amazon PM Interview Course

Practice Amazon-focused PM cases

Apple PM Interview Course

Practice Apple-focused PM cases

Google PM Interview Course

Practice Google-focused PM cases

Microsoft PM Interview Course

Practice Microsoft-focused PM cases

All Courses

Explore all courses

1:1 PM Coaching

Practice in a one-to-one session

Resume Review

Narrate impactful stories via resume

Guides Pricing
nextsprints logo

Not a member?

By proceeding, you agree to our Terms of Use and confirm you have read our Privacy and Cookie Statement.

nextsprints logo

Register to continue.

Login with Google Login with LinkedIn

By proceeding, you agree to our Terms of Use and confirm you have read our Privacy and Cookie Statement .

Company focus

Domo

Why has the average session duration for Domo's mobile app decreased by 25% in the last two weeks?

Prepared by NextSprints

12 mins
Report an error
Data Analysis Problem Solving User Experience Business Intelligence SaaS Mobile Apps User Engagement Product Metrics Root Cause Analysis Mobile Analytics BI Tools
Product Management Root Cause Analysis Question: Investigating decreased mobile app engagement for Domo

Introduction

The recent 25% decrease in average session duration for Domo's mobile app over the past two weeks is a significant issue that requires immediate attention. This metric is crucial for understanding user engagement and the overall health of our mobile product. I'll approach this problem systematically, focusing on identifying potential root causes, validating hypotheses, and developing both short-term 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 there might have been a recent app update. Has there been any significant changes or updates to the mobile app in the last month?

Why it matters: Recent changes could directly impact user behavior. Expected answer: Yes, there was an update two weeks ago. Impact on approach: If confirmed, we'd focus on changes introduced in that update.

  • Considering user segments, I'm curious about the distribution of this decrease. Is the 25% drop consistent across all user segments, or are some groups more affected than others?

Why it matters: Helps identify if the issue is universal or specific to certain users. Expected answer: The decrease is more pronounced among power users. Impact on approach: We'd investigate features commonly used by power users.

  • Given the nature of Domo's product, I'm wondering about any changes in data freshness or availability. Have there been any issues with data pipelines or integrations in the past two weeks?

Why it matters: Data quality directly impacts the app's utility. Expected answer: No significant data issues reported. Impact on approach: We'd shift focus to app functionality rather than data quality.

  • Considering external factors, has there been any significant change in competitor offerings or market conditions in the past month?

Why it matters: External factors could influence user behavior. Expected answer: No major market shifts, but a competitor launched a new feature. Impact on approach: We'd analyze our feature set against the competitor's new offering.

Subscribe to access the full answer

Image of author NextSprints

NextSprints

Updated Jan 22, 2025