I Tested 47 Different Price Points. $7.99 Made 3x More Than $2.99.
For six months, I was the idiot selling my app for $0.99.
Monthly revenue: $327 Active subscribers: 327 Churn rate: 68%
"But users want cheap apps!" I told myself while eating ramen for the third night straight.
Then I ran the most extensive pricing test I could afford. 47 different price points. 10,000 users. 6 months of data.
The result? My optimal price was $7.99. Not $0.99. Not $2.99. Not even $4.99.
At $7.99:
- Revenue increased 312%
- Churn dropped to 31%
- Support tickets decreased 74%
- User satisfaction actually went UP
Here's everything I learned about pricing psychology, why cheaper isn't better, and the exact framework for finding your optimal price point.
The Pricing Delusion That Nearly Killed My Business
My original pricing logic:
"If I price at $0.99, I'll get 10x more users than at $9.99. Same revenue, bigger audience!"
The reality:
- At $0.99: 327 users = $327/month
- At $7.99: 156 users = $1,246/month
- At $9.99: 128 users = $1,279/month
Half the users. Four times the revenue.
But that's not even the shocking part.
The Quality Paradox Nobody Talks About
Here's what happened to user behavior at different price points:
$0.99 users:
- 68% monthly churn
- 2.3 support tickets per user
- 14% left negative reviews
- Average session: 1.2 minutes
- Feature requests: 147/month
$7.99 users:
- 31% monthly churn
- 0.3 support tickets per user
- 2% left negative reviews
- Average session: 8.4 minutes
- Feature requests: 12/month
Higher prices didn't just mean more revenue. They meant better users.
The 47 Price Point Experiment
Here's exactly how I tested:
Phase 1: Wide Range Testing (Month 1-2)
Tested 10 price points from $0.99 to $19.99
- Split traffic evenly
- Tracked conversion and retention
- Minimum 100 users per price point
Results: Sweet spot between $5.99 and $9.99
Phase 2: Narrow Range Testing (Month 3-4)
Tested every $0.50 increment from $5.99 to $9.99
- $5.99, $6.49, $6.99, $7.49, $7.99, $8.49, $8.99, $9.49, $9.99
Results: Peak revenue at $7.99 and $9.99
Phase 3: Psychological Price Testing (Month 5-6)
Tested psychological variations:
- $7.99 vs $8.00
- $7.99 vs $7.97
- $9.99 vs $9.95 vs $10.00
- $7.99/month vs $79/year vs $0.26/day
Results: Monthly at $7.99 won everything
Phase 4: Bundle Testing (Month 6)
Tested tiers and bundles:
- Single tier at $7.99
- Three tiers at $4.99/$7.99/$14.99
- Freemium with $7.99 upgrade
Results: Single tier outperformed by 23%
The Psychology Triggers That Actually Work
After analyzing conversion data, these patterns emerged:
The Anchoring Effect
What didn't work: Starting with the cheapest option
What worked: Showing annual price first ($95.88/year), then monthly ($7.99/month) looked like a bargain
Conversion increase: 34%
The Goldilocks Principle
What didn't work: Single price point with no context
What worked: Showing "Most Popular" badge on middle option, even with one tier
Conversion increase: 19%
The Precision Paradox
What didn't work: $7.97 (feels like a discount store) $8.00 (feels expensive psychologically)
What worked: $7.99 (feels professional but fair)
Conversion difference: 12% higher than $8.00
The Commitment Test
What didn't work: Free trial then paid
What worked: Paid upfront with 30-day money-back guarantee
Conversion was lower (by 20%) but retention was higher (by 45%). Net positive: 31% more revenue.
The Hidden Costs of Cheap Pricing
What I didn't realize about $0.99 pricing:
Transaction fees killed me:
- Apple takes 30%: $0.30
- Processing overhead: ~$0.10
- Net per user: $0.59
I needed 14 users to make minimum wage per hour of support.
Support burden exploded: Low-price users expect premium support. I was drowning in "how do I?" emails for basic features clearly shown in onboarding.
Reviews tanked: $0.99 users left 3x more negative reviews. They treated the app as disposable.
Development suffered: Constant feature requests from users contributing $0.59/month made roadmap planning impossible.
The Premium Positioning Playbook
Here's how I repositioned from "cheap app" to "valuable solution":
Step 1: Language Overhaul
Before: "Simple task manager for everyone" After: "Professional productivity system for ambitious individuals"
Changed every word from casual to professional.
Step 2: Feature Framing
Before: Listing 47 features After: 3 core benefits with outcomes
Instead of "Sync across devices" → "Never lose work when switching from phone to laptop"
Step 3: Social Proof Upgrade
Before: "10,000+ downloads!" After: "Trusted by professionals at Apple, Google, and Microsoft"
Quality over quantity positioning.
Step 4: Comparison Reframe
Before: Comparing to free apps After: Comparing to $30/month professional tools
Made $7.99 look like incredible value.
Step 5: Visual Premium-ization
Before: Playful, colorful design After: Minimal, professional aesthetic
Every pixel started saying "this is serious software."
The Pricing Metrics That Actually Matter
Stop tracking these:
- Total downloads
- Conversion rate in isolation
- Day 1 revenue
Start tracking these:
Customer Lifetime Value (LTV): $0.99 price: $1.47 LTV $7.99 price: $25.73 LTV
Payback Period: How long to recoup customer acquisition cost $0.99: Never (CAC > LTV) $7.99: 1.3 months
Revenue per Install: Total revenue divided by total installs $0.99: $0.41 $7.99: $3.87
Support Cost per User: $0.99: $2.31 (losing money per user!) $7.99: $0.43
Word-of-Mouth Coefficient: How many users each customer refers $0.99: 0.13 $7.99: 1.47
The International Pricing Discovery
Regional pricing taught me even more:
United States: $7.99 optimal United Kingdom: £6.99 optimal (not direct conversion) Germany: €8.99 optimal (higher than US!) India: ₹199 optimal (lower purchasing power) Japan: ¥980 optimal (psychological pricing)
Lesson: Don't just convert currencies. Test each market.
Regionalizing prices increased international revenue by 67%.
The Subscription vs One-Time Dilemma
I tested both models extensively:
One-time purchase at $39.99:
- High initial revenue
- 73% piracy rate
- No recurring revenue
- Harder to justify updates
Subscription at $7.99/month:
- Predictable revenue
- Continuous value delivery expected
- Lower piracy
- Easier to iterate
Winner: Subscription by 430% over 12 months
The key: Position as ongoing service, not product.
The Pricing Migration Strategy
How to raise prices without losing everyone:
For Existing Users:
What I did:
- Grandfathered current users at old price forever
- Sent email explaining new value additions
- Offered voluntary upgrade with bonus features
- Never forced migration
Result: 23% voluntarily upgraded to higher price
For New Users:
Week 1: Updated App Store quietly Week 2: Changed website pricing Week 3: Updated all marketing materials Week 4: Ran "last chance at old price" campaign
Result: Surge of signups before increase, smooth transition after
The Competitive Pricing Trap
My competitors were priced at:
- Free (with ads)
- $1.99/month
- $2.99/month
- $4.99/month
I thought I had to match them. Wrong.
By pricing at $7.99, I:
- Positioned as premium alternative
- Attracted users who valued quality
- Had budget for better development
- Could afford real customer support
Being the expensive option became our differentiator.
The Failed Experiments Worth Sharing
Pay-what-you-want: Average payment: $0.73. Total disaster.
Usage-based pricing: Too complex, users hated uncertainty.
Feature-gated tiers: Users felt nickel-and-dimed.
Discount promotions: Attracted worst users, trained people to wait for sales.
Lifetime deals: Short-term revenue spike, long-term support nightmare.
Simple, single, clear pricing won every time.
Your Pricing Test Framework
Week 1: Baseline Measurement
- Current price performance
- Calculate true LTV
- Document support burden
- Track user quality metrics
Week 2-3: Test 2x Current Price
- Split test 50/50
- Track all metrics, not just conversion
- Survey both groups
- Calculate true revenue impact
Week 4-5: Test 3x Current Price
- Even if it seems crazy
- You might be surprised
- Premium positioning might work
- Track quality metrics especially
Week 6: Analyze and Decide
- Compare LTV, not conversion
- Factor in support costs
- Consider user quality
- Make data-driven decision
Expected outcome: Optimal price 2-5x higher than you think
The Mindset Shift That Changes Everything
Old thinking: "Will people pay this much?" New thinking: "Am I delivering this much value?"
Old thinking: "Lower price = more accessible" New thinking: "Right price = sustainable business"
Old thinking: "Compete on price" New thinking: "Compete on value"
Old thinking: "Apologize for charging" New thinking: "Proud of the value we deliver"
Your price is a signal. Cheap signals cheap. Premium signals premium.
What I Know Now About Pricing
Your first price is wrong. Test immediately and continuously.
Higher prices attract better customers. They value what they pay for.
Support costs matter. Factor them into unit economics.
Simple beats complex. One good price beats three confusing tiers.
Value perception is malleable. Same product, different positioning, 10x price.
Grandfathering builds loyalty. Never punish early supporters.
Most developers underprice by 3-5x. You're probably one of them.
The Bottom Line on Pricing
That $0.99 price wasn't serving anyone:
- I couldn't build a sustainable business
- Users didn't value the product
- Support was unsustainable
- Development was unfunded
At $7.99:
- Revenue supports continuous improvement
- Users are invested in success
- Support is manageable
- Can afford to build amazing features
Your price isn't just a number. It's a statement about your value, your users, and your vision.
If you're not slightly uncomfortable with your price, it's too low.
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P.S. - Still pricing at $0.99? You're not building a business. You're subsidizing strangers' productivity with your time. Your app is worth more. Charge accordingly.