Problem vs Symptom
Products fail when teams solve what they can see instead of what is actually causing it.
Teams spend months solving the wrong problem.
A food delivery app’s daily active users dropped 12% over the last month.
What is the actual problem?
Symptom vs problem
Symptom
What you observe. It tells you something is wrong, rarely why.
- Orders dropped
- Users are uninstalling
- Engagement reduced
- Watch time declined
Problem
The underlying reason causing the symptom. It explains the why.
- Checkout became slower
- Recommendations turned irrelevant
- Pricing confused users
- Onboarding became harder
How weak and strong thinking differ
Strong PMs investigate causes before proposing solutions.
“Users aren’t opening the app enough. Let’s send more notifications.”
Strong PM thinking
Real-world product patterns
Decisions users feel every day, read as a response to a visible symptom rather than the deeper problem.
The shift toward Reels
TikTok's watch time and engagement were growing fast.
Instagram pushed Reels-first: full-screen feed, heavier recommendations, TikTok-style discovery.
Instagram's core value — the friend and follow graph — may not be the behaviour that drives TikTok. Copying the format strained the thing users came for.
Search becoming ad-heavy
The business needed stronger monetization and seller promotion.
Search and discovery filled with sponsored products, promoted listings, and ads inside results.
The core shopping need is trustworthy, efficient discovery. Ad density competes directly with the ranking users rely on to find the best product fast.
Notification pressure
Users stop opening the app once an active job search ends.
More notifications — profile views, appearing in searches, new jobs, recruiters hiring.
This may simply be a low-frequency product. People need it intensely during a search and rarely between. Pushing engagement makes it feel spammy without addressing that.
How strong PMs investigate
- 01
Symptom
The visible, measurable thing that moved.
- 02
Where it happens
Which segments, cities, or funnel steps actually shifted.
- 03
Break down the funnel
Decompose the workflow to isolate the step that changed.
- 04
Investigate causes
Pricing, release, onboarding, trust, competition — what changed?
- 05
Validate with data
Test the leading explanation before committing a fix.
- 06
Then solve
Design the fix against the cause, not the signal.
Think of a product feature you found annoying or unnecessary. What symptom was the team likely reacting to — and what deeper problem might it have missed?
Symptoms are visible. Problems are causal. Strong PMs don’t react to the metric that moved — they find what moved it.