Research-Backed Prompt

Pricing Psychology & Willingness to Pay Research (Revenue Extraction)

Understand true willingness to pay, not just stated prices. 28% revenue lift from price optimization based on psychology. Most SaaS underprices significantly.

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Pricing Psychology & Willingness to Pay Research (Revenue Extraction)

Understand true willingness to pay, not just stated prices. 28% revenue lift from price optimization based on psychology. Most SaaS underprices significantly.

pricing-psychology

willingness-to-pay

revenue-optimization

price-elasticity

customer-research

economics

Variables

Your Product or Service *

Target Customer *

Current Price *

Prompt

Product/service: 
Target customer: 
Current price: 

Research willingness to pay:

1. Value quantification:
   - What economic value does this deliver?
   - How much would they lose without it?
   - What's their ROI if they buy?
   - How would they measure success?

2. Reference prices:
   - What do they currently pay for alternatives?
   - How much do they spend on related solutions?
   - What's their budget for this category?
   - What feels 'cheap' vs 'expensive'?

3. Pricing psychology:
   - Anchor price: "Most customers pay $X"
   - Charm pricing: Does 99/100 matter? (yes, 10% impact)
   - Bundling: What combinations increase WTP?
   - Scarcity: Does "limited slots" increase perception?
   - Social proof: "500 companies use this"
   - Decoy pricing: Does middle option anchor to higher tier?

4. Segmentation by WTP:
   - Who would pay premium? Why?
   - Who's price-sensitive?
   - Who's willing to try a lower tier?
   - What triggers upgrade?

5. Pricing experiments:
   - A/B test current vs 20% higher
   - Try 3 tiers vs 1
   - Test annual prepay discount (vs monthly)
   - Try usage-based vs flat

6. Frame pricing differently:
   - Monthly cost: $50
   - Daily cost: $1.67 (feels cheaper)
   - Cost per employee: $2.50 (justifies for team)
   - Annual cost: $600 (feels expensive)
   - ROI framing: "Saves $10k/year"

7. Test plan:
   - What's your riskiest assumption about price?
   - How would you test it?
   - What's 10% more? 20% more? 50% more?
   - Where's the drop-off point?

Examples

Input

{
  "product": "AI-powered content personalization engine",
  "customer": "E-commerce companies ($5M-$50M ARR)",
  "currentPrice": "$3000/month"
}

Output

Value quantification, reference prices, psychological pricing tactics, WTP segmentation, experiment designs, and pricing frame recommendations.

Sources

https://www.amazon.com/Priceless-Myth-Rational-Value-Explains/dp/0374534519

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