How to Solve an 80% Drop-Off in a Mobile App — A Practical Case Study
From data analysis to team plan — how I approached this retention challenge step by step
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One of the biggest challenges in product education today is the gap between theory and real-world decision-making. Frameworks are great — but they won’t help much if you’ve never applied them under real constraints.
Recently, I was asked to solve a mobile product case as part of a hiring process. The task focused on a common but tough challenge: user retention during the first week.
In this case, I’ll walk you through how I apply product thinking in a real scenario:
🔎 How I analyze behavioral and qualitative data
💡 How I form 5 product hypotheses and score them using a light ICE framework
🎯 How I select one hypothesis for MVP testing
🛠 How I build a team plan — including user story, UX ideas, success metrics, and edge cases
🚨 (Bonus) Link to the full Figma prototype preview
This breakdown might be helpful if you:
– are preparing for a PM interview
– want to see what practical product thinking actually looks like
– work in a startup with limited resources
📌 Full breakdown below — curious to hear what you'd do differently!
The Case Setup
Imagine you’ve just launched a mobile app called NutriTrack — designed for people who want to eat healthy without spending hours planning meals.
Here’s what it does:
Automatically generates a personalized weekly meal plan
Tracks calories and macronutrients
Helps users stay on track with daily meal check-ins
When a new user signs up, they:
Choose a goal (lose weight, maintain, or gain)
Go through a short onboarding survey
Receive a tailored weekly nutrition plan
Can mark meals as “completed” or swap items any time
The Problem?
Despite a smooth onboarding and personalized suggestions, over 80% of new users stop using the app by Day 2 or 3, without completing even one week of the plan.
Let’s dive into the solution 👉
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