You Know Your Pricing Is Leaving Money on the Table... But You're Paralyzed

❌ You're undercharging - Competitors raise prices 20% while you stay flat, afraid of churn

❌ You're overcharging the wrong segment - Losing deals to "too expensive" when you'd discount anyway

❌ Your value metric is broken - Customers pay per-seat but value comes from reports generated

❌ You have no testing framework - Last pricing change was "founder gut feel + prayer"

❌ Consultants want $50K minimum - You're too small for Simon-Kucher, too big for guessing

❌ Pricing software requires 10K+ visitors/month - You have 100 customers and basic analytics

❌ You've delayed pricing optimization 6-18 months - Fear of breaking what's working

The Real Cost:

Every quarter you wait, competitors capture pricing power you'll never get back.

Example: A $2.8M ARR SaaS company delaying a value metric shift from per-seat to usage-based leaves $840K on the table annually (30% ARPU lift × customer base).

Your consultant quote: $75K + 4 months Your actual budget: $0 + 0 hours available

Introducing: The Safe-to-Test Pricing Experiments Framework (AI enabled)

The first AI-powered system that lets you design consultant-grade pricing experiments in 15 minutes - using ChatGPT, Claude, or Gemini you already have.

1. Safe Experiments (Not Revenue Russian Roulette)

• Test with 20-50 customers, not your entire base
• Pre-defined kill criteria (stop if churn spikes 3+ points)
• Grandfather clauses protect existing revenue
• Rollback plans included (customer apology templates ready)

2. AI-Powered Design (95%+ First-Draft Success)

• 18-variable megaprompt generates complete experiment plans
• 5 sections: Design, Value Discovery, Guardrails, Communication, Measurement
• Works with ChatGPT, Claude, Gemini (configs included)
• Copy-paste ready—no prompt engineering needed

3. Consultant-Grade Frameworks (At DIY Cost)

• 10 modules covering problem → implementation → validation
• Evidence-based strategies (15+ cited sources: OpenView, ProfitWell, Price Intelligently)
• 72 strategic questions to interrogate AI outputs
• Quality gates (125-point system) ensure production-readiness

WHAT YOU GET

Everything You Need to Run Your First Profitable Pricing Experiment This Week

Module Breakdown:

📚 9 Complete Execution Modules

1. Problem Analysis & Market Validation
2. The Megaprompt System ⭐ Core System
3. Context Framework + YAML Templates + 2 complete filled examples
4. Implementation Workflow
5. Testing & Validation Harness + Scoring Rubric (100 Points) + Retune Playbook
6. Advanced Techniques - 6 patterns: Chain-of-Thought, Prompt Chaining, CRITIC, Retrieval, Pre-Mortem, Optimization
7. Strategic Question Bank - 72 leverage questions across 6 categories
8. 5 winning patterns with impact
9. Quality Gates & Personalization - 5 quality gates (125-point system, pass threshold: 95/125)
   

🎯 Companion Prompts & Templates

• Main Megaprompt - Production-ready, copy-paste into any AI platform
• YAML Context Template - Fill your business details, generate personalized experiments

What Happens When You Stop Guessing and Start Testing

Evidence-Based Results

• 23% Higher Revenue Per Customer Companies testing pricing quarterly vs. annual-only reviewers
• 38% Higher Net Revenue Retention Usage-based SaaS vs. seat-based pricing models
• 40% Churn Reduction Transparent pricing communication vs. surprise price increases
• 52% Fewer Post-Deployment Failures AI systems with quality gates vs. no validation

Example ROI Calculation:

Scenario: Mid-market B2B SaaS, $8M ARR, 700 customers, $2,450 ARPU

Experiment: Value Metric Test (shift per-seat → usage-based)

• Pilot: 50 customers, 90 days
• Result: +30% ARPU ($2,450 → $3,200)
• Pilot Revenue Lift: $37,500 annual
• Scaled (50% of base): $525,000 annual revenue increase

Experiment Cost:

• Time: 10 hours (setup + monitoring) × $150/hr = $1,500
• Software: $0 (ChatGPT Plus $20/mo already owned)
• Total: $1,500

ROI: $525,000 / $1,500 = 350x first-year return

Perfect For Post-PMF Operators Who Are Too Big to Guess, Too Small for Consultants

Ideal Customer Profiles:

✅ Founders ($500K-$10M ARR)

• You've achieved product-market fit
• Pricing hasn't been touched since launch
• Board wants pricing power story for next fundraise
• Can't afford $50K+ consultant minimums
• Need data to justify pricing changes to investors

✅ CMOs & Growth Leads

• Responsible for conversion rate optimization
• Suspect pricing page is leaving money on table
• Don't have analytics platform for A/B testing
• Need campaign-integrated pricing experiments
• Want to test value metrics without engineering help
  

✅ Agency Owners

• Retainer pricing feels arbitrary ("$5K/mo because that's what we charge")
• Most pricing tools are SaaS-focused (you're services)
• Need to optimize retainer vs. project pricing
• Want to test scope-based pricing models
• Client retention is top KPI

NOT For:

❌ Enterprise ($50M+ ARR): You need Simon-Kucher, compliance lawyers, multi-region complexity

❌ High-Traffic Businesses (50K+ visitors/mo): Use Optimizely, VWO for real-time multivariate testing

❌ Complex Usage-Based (100+ pricing variables): You need Corrily, Stigg (ML-driven dynamic pricing)

From Zero to First Experiment in 15 Minutes

What You Get in Output:

1. Experiment Design Blueprint: Type, duration, sample size, cohort criteria, implementation steps
2. Value Discovery Framework: What to test, why it matters, decision tree
3. Guardrails & Kill Criteria: When to stop, rollback plan, pre-launch checklist
4. Communication Scripts: Customer email, stakeholder brief, internal monitoring (copy-paste ready)
5. Measurement Dashboard: Metrics to track, decision matrix (Scale/Iterate/Pause/Kill)

FAQ

Q: Do I need to be technical to use this?

A: No. If you can copy-paste into ChatGPT and fill out a form, you're good. No coding, no complex analytics setup.

Q: What AI platform do I need?

A: ChatGPT Plus ($20/mo), Claude Pro ($20/mo), or Gemini Advanced ($20/mo). Platform configs included for all three.

Q: How long does an experiment take to run?

A: Typical timeline: 60-90 days (2-3 billing cycles). You'll spend 30 min/week monitoring, 2-3 hours total for setup and analysis.

Q: What if my experiment fails?

A: That's the point of "safe-to-execute." You test with 20-50 customers (5-10% of base), not your entire revenue. Kill criteria stop bad experiments before damage. Rollback plans included.

Q: Is this just a prompt I could write myself?

A: Technically yes, if you spent 100+ hours researching pricing experimentation frameworks, testing with real businesses, and optimizing prompt structures. This is the distilled, production-ready version.

Q: Will this work for my industry (agency/e-commerce/fintech)?

A: Yes. The 9-dimension context framework adapts to SaaS, agencies, services, e-commerce, fintech. Examples included for each.

Q: Do I get updates? A: Currently this is v1.0 (November 2025). Updates TBD based on user feedback. (Honest answer: no guaranteed update schedule yet)