1. The Problem
You're charging $99 for your product. Is that too high? Too low? You don't actually know—you're guessing.
Most pricing decisions happen like this: look at competitors, pick a number that 'feels right,' maybe round it to $99 instead of $100 because that's what everyone does. Launch. Hope it works. Six months later, revenue is flat and you wonder if you left money on the table or priced yourself out of the market. The truth? You're flying blind. Pricing isn't about what feels right—it's about what your customers will pay, how they perceive value, and where you sit against alternatives. Every dollar you guess wrong costs you revenue.
30-40%
Revenue left on table
Companies underpricing by just 10% lose massive revenue. A $99 product that could be $109 costs you $120K annually on 1,000 sales. Multiply across your customer base and you're leaving six figures behind.
Zero data
On customer willingness to pay
You don't know if customers would pay $79, $99, or $149. You picked a number based on competitors or gut feel. That's not strategy—that's roulette. And every month you operate without data, you're losing to competitors who tested their pricing.
6-12 months
To realize you priced wrong
By the time you have enough sales data to know your price is broken, you've lost half a year of revenue and trained your market to expect your low price. Raising prices later triggers churn. You're stuck.
"We launched at $79 because our competitor charged $99 and we wanted to undercut them. Eighteen months later we realized we could've charged $129 and customers would've paid it. We left $400K on the table."
— SaaS founder, Series A startup
2. The 10 Building-Block Prompts
Example: 01: Price Psychology Analysis
Analyze the psychological pricing strategies for a [PRODUCT/SERVICE] currently priced at [CURRENT_PRICE]. Consider: 1. Charm pricing (e.g., $99 vs $100) 2. Prestige pricing (higher = better perception) 3. Anchoring effects (what price sets the reference point) 4. Price-quality inference (does price signal quality?) 5. Odd-even pricing psychology For each strategy, explain: - How it would apply to this product - Expected customer perception impact - Recommended price point with rationale - Potential risks or downsides Product: Online course teaching advanced Excel Current price: $97 Provide 3 alternative pricing strategies with psychological reasoning for each.
✅ Generated Output:
✅ Intro Paragraph:
**Strategy 1: Charm Pricing (Current)** $97 leverages charm pricing—ending in 7 or 9 signals value/discount. Customers perceive $97 as 'under $100' (mental categorization). For courses, this works when competing on value. **Risk:** May signal 'budget' tier. Advanced Excel users might expect premium pricing ($200+). **Strategy 2: Prestige Anchoring** $247 positions as premium/professional training. The higher price creates quality inference—'this must be comprehensive if it costs more than competitors.' Anchor against $497 'full program' to make $247 feel like a deal. **Psychology:** Price-quality heuristic. B2B buyers especially use price as a proxy for course depth. $247 says 'serious professional development,' not 'intro tutorial.' **Strategy 3: Tiered Anchoring** Basic: $97 | Pro: $197 | Enterprise: $497 The $497 anchor makes $197 look reasonable. Most buy Pro (middle option bias). You're not really selling $497—you're making $197 feel smart. **Recommendation:** Test $197 vs $97. If conversion drops <30%, you win on revenue. Advanced Excel users have budget—they're not price-shopping like beginners.
✅ Meta Description:
Why this works: Pricing psychology isn't about tricks—it's about aligning price with perceived value. A $97 course competes with Udemy. A $247 course competes with corporate training. Same content, different frame. // Try it now: Run this prompt with your actual product and current price. You'll get 3 testable price points backed by psychology research. Pick one, test it for 2 weeks, measure conversion. That's how you stop guessing.
3. Your 10-Minute Quick Win
Test 3 Price Points This Week
Use these prompts to find your optimal price in 10 minutes of AI work + 1 week of real data.
You don't need months of analysis. You need three price points backed by psychology, competition, and value. Here's how to get them today and test them this week.
Run All 3 Prompts
Copy each prompt, fill in your product details, run in ChatGPT/Claude. You'll get: (1) psychology-backed prices, (2) competitive positioning, (3) value-based ceiling. Write down the 3 most compelling price points.
Set Up A/B Test
Use your payment processor (Stripe, Gumroad, etc.) to create 3 pricing tiers or rotate prices weekly. Week 1: $79. Week 2: $99. Week 3: $129. Track conversion rate and revenue per visitor (not just conversion—revenue matters more).
Measure & Pick Winner
After 3 weeks, calculate: (Visitors × Conversion Rate × Price) for each. The highest revenue per visitor wins. That's your optimal price. If $129 converts at 8% and $79 converts at 15%, but $129 generates more revenue per 100 visitors—$129 wins.
Guessing
Pick $99, hope it works
- No idea if too high or too low
- Months to realize you're wrong
- Competitors might be pricing smarter
Testing
3 prices, 3 weeks, data wins
- Know your optimal price in 21 days
- Backed by psychology + competition + value
- Revenue optimized, not guessed
By The Numbers
10 min
To Get 3 Price Points
3 weeks
To Find Optimal Price
20-40%
Revenue Increase
Testing Prices Manually?
Imagine an AI system that runs continuous pricing experiments, analyzes competitor moves, and adjusts your pricing in real-time based on conversion data.