Positivity After Failure
"When you lose a game now as opposed to surfacing your blunders and your horrible stuff that you did, we flip it on its head and so we show you your brilliant moves, your best moves, and we have coach say something encouraging... That change alone grew game reviews by 25%, subscriptions by 20%." - Albert Cheng
What It Is
Positivity After Failure is a design principle for handling user failure states. Instead of showing users what they did wrong (the "logical" approach for learning products), show them what they did right and deliver encouragement. The counterintuitive insight: users engage more with failure feedback when it's framed positively.
This challenges the assumption that users want to learn from mistakes. In reality, failure already feels bad—compounding it with criticism drives disengagement. Positive framing creates psychological safety that increases willingness to try again.
How It Works
The Counterintuitive Insight
At Chess.com, 80% of users who reviewed their games did so after a win, not after a loss. The team expected users would want to analyze their mistakes. They were wrong.
What users say they want: "Help me learn from my mistakes" What users actually do: Avoid revisiting failure; seek validation
Traditional (Cold) Pattern
After user fails:
- "Here's what you did wrong"
- List of mistakes/blunders
- Analysis of failure points
- Implicit message: "You're bad at this"
Positivity Pattern
After user fails:
- "Here's what you did brilliantly"
- Highlight best moments
- Encouraging message about the journey
- Implicit message: "You're capable, keep going"
How to Apply It
Audit your failure states - Where in your product do users fail? What do they see? Look for "cold patterns" (criticism, red colors, error lists).
Flip the framing - For each failure state, ask: "What did the user do RIGHT?" Lead with that instead.
Add encouragement - Include explicit messages that normalize failure as part of the journey:
- "Losing is just part of learning"
- "Everyone struggles with this at first"
- "You're making progress"
Use warm design language - Change colors, icons, and copy from warning/error patterns to achievement/progress patterns.
Measure engagement, not just completion - Track whether users return after failure, not just whether they see the failure screen.
Example: Chess.com Implementation
Before:
- After losing a game, show the user their blunders
- Highlight worst moves in red
- Analysis focuses on mistakes
After:
- After losing a game, show the user their brilliant moves
- Highlight best moves
- Coach says: "Losing is just part of learning, keep it up"
Results:
- 25% increase in game reviews
- 20% increase in subscriptions
- Significant user retention improvement
Expansion: The insight was then applied to puzzles, lessons, and other failure states across the product.
When to Use It
- Learning products where users frequently fail
- Products with skill progression
- Onboarding flows where new users struggle
- Any feature with measurable user performance
- Products competing with entertainment (where failure = friction)
When NOT to Use It
- Safety-critical contexts where failures must be highlighted
- Professional tools where users need accurate feedback
- B2B contexts where users are experts seeking precision
- When users explicitly opt into "hard mode" or detailed analysis
The Psychology
- Loss aversion - Failure already feels like a loss; don't pile on
- Self-efficacy - Belief in capability drives persistence
- Positive reinforcement - Rewards increase behavior frequency
- Identity protection - Users avoid experiences that threaten their self-image
Source
- Guest: Albert Cheng
- Episode: "Finding hidden growth opportunities in your product"
- Key Discussion: (00:11:34) - Chess.com game review transformation
- YouTube: Watch on YouTube
Related Frameworks
- Explore and Exploit for Growth - How this insight was expanded across Chess.com
- Gamification Three Pillars - Broader engagement framework