I want to find the optimal price range for [product].
Run me through Van Westendorp Price Sensitivity Meter.
Provide the questions and analysis framework.

I'm considering pricing at [$X, $Y, $Z].
Help me design a Gabor-Granger test to measure demand at each price.

I want to validate my $99/month pricing without asking "would you pay?"
What behavioral and indirect methods can I use?

## Pricing Research Methods

### Method Selection Guide

| Method | Best For | Sample Size | Complexity |
|--------|----------|-------------|------------|
| Van Westendorp PSM | Finding price range | 100-200+ | Medium |
| Gabor-Granger | Testing specific prices | 50-100 | Low |
| Conjoint Analysis | Feature/price trade-offs | 200+ | High |
| A/B Testing | Final validation | 500+ visitors | Medium |
| Behavioral Signals | Qualitative insights | 10-30 | Low |

### When to Use Each

**Van Westendorp (Price Sensitivity Meter):**
- You don't know where to start
- Want to find acceptable price range
- Have access to survey respondents

**Gabor-Granger:**
- You have candidate price points
- Want to test specific prices
- Need demand curve

**Conjoint Analysis:**
- Multiple features and price levels
- Need to understand trade-offs
- Have resources for complex analysis

**A/B Testing:**
- Already have traffic/users
- Testing final price decisions
- Want real conversion data

**Behavioral Signals:**
- Early stage, small sample
- Qualitative validation
- Can't run formal surveys

## Van Westendorp PSM

### The Four Questions

Ask respondents all four questions about the product:

1. **TOO EXPENSIVE:**
   "At what price would you consider this product to be so expensive
   that you would not consider buying it?"

2. **TOO CHEAP:**
   "At what price would you consider this product to be priced so low
   that you would question its quality?"

3. **EXPENSIVE BUT WORTH IT:**
   "At what price would you consider this product starting to get expensive—
   it's not out of the question, but you'd have to think about buying it?"

4. **GOOD VALUE:**
   "At what price would you consider this product to be a bargain—
   a great buy for the money?"

### Analysis

Plot cumulative distribution curves for each response:
- "Too Expensive" (cumulative from low to high)
- "Too Cheap" (cumulative from high to low)
- "Expensive" (cumulative from low to high)
- "Good Value" (cumulative from high to low)

### Key Price Points

| Point | Definition | Meaning |
|-------|------------|---------|
| **PMC** (Point of Marginal Cheapness) | Where "Too Cheap" intersects "Expensive" | Below this, quality concerns emerge |
| **PME** (Point of Marginal Expensiveness) | Where "Too Expensive" intersects "Good Value" | Above this, significant resistance |
| **OPP** (Optimal Price Point) | Where "Too Expensive" intersects "Too Cheap" | Best price for adoption |
| **IDP** (Indifference Price Point) | Where "Expensive" intersects "Good Value" | What people expect to pay |

### Acceptable Price Range
PMC to PME = your acceptable pricing range

### Interpretation Guide

**Narrow range (PMC close to PME):**
- Price sensitive market
- Commodity perceptions
- Strong competitor reference prices

**Wide range (PMC far from PME):**
- Price flexibility
- Differentiated product
- Segmentation opportunity

## Gabor-Granger Price Testing

### How It Works

Show product, then ask purchase intent at specific price points.
Start high or low, adjust based on response.

### Question Format

**Monadic (one price per person):**
Show each respondent only ONE price:
"Would you buy this product at $X?"
- Definitely would buy
- Probably would buy
- Might or might not buy
- Probably would not buy
- Definitely would not buy

**Sequential (multiple prices per person):**
If "Yes" → show higher price
If "No" → show lower price
Continue until you find their threshold

### Analysis

**Purchase Intent Translation:**
| Response | Probability |
|----------|-------------|
| Definitely | 90% |
| Probably | 70% |
| Might | 30% |
| Probably not | 10% |
| Definitely not | 0% |

**Demand Curve:**
| Price | Purchase Intent | Weighted % | Expected Revenue |
|-------|-----------------|------------|------------------|
| $49 | 80% | 68% | $49 × 68% = $33.32 |
| $79 | 60% | 48% | $79 × 48% = $37.92 |
| $99 | 40% | 32% | $99 × 32% = $31.68 |
| $149 | 20% | 14% | $149 × 14% = $20.86 |

**Optimal Price:** $79 (highest expected revenue)

### Sample Size Requirements

- 30-50 per price point (monadic)
- 50-100 total (sequential)
- Segment analysis requires more

## Pricing Validation Without Asking About Price

### Why Indirect Methods Matter
- People overestimate willingness to pay when hypothetical
- Real behavior differs from stated intent
- Indirect signals often more reliable

### Method 1: Reference Price Anchoring

**Questions to ask:**
- "What are you currently spending on [similar product/solution]?"
- "What's the most you've ever paid for [category]?"
- "What would you expect this to cost based on similar products?"

**Analysis:**
If they're spending $100/month on alternatives, $150 might be possible.
If they've never paid >$50 for similar, $200 is risky.

### Method 2: Value Quantification

**Questions to ask:**
- "How much time does this problem cost you per week?"
- "What's the cost of this problem not being solved?"
- "If this saved you X hours/week, what's that worth?"

**Analysis:**
If problem costs them $500/month in time, $100/month solution seems cheap.
Price relative to quantified value, not arbitrary numbers.

### Method 3: Trade-off Questions

**Instead of:** "Would you pay $X?"
**Ask:** "Which would you choose?"
- Option A: $79/month with features X, Y, Z
- Option B: $49/month with features X, Y only
- Option C: Free with feature X only

**Analysis:**
Distribution reveals price sensitivity and feature value.

### Method 4: Commitment Testing

**Real commitment signals:**
- "Would you put $50 down as a deposit for early access?"
- "Would you sign a letter of intent at $X?"
- "Would you pay for a paid pilot at $X/month?"

**Analysis:**
Real money > stated intent.
Even small commitment = strong signal.

### Method 5: Negotiation Simulation

**Questions to ask:**
- "If this was $X, would you push back? At what price would you push back?"
- "What price would make this an easy decision?"
- "What price would require significant justification internally?"

**Analysis:**
- "Easy decision" price = conservative but low-friction
- "Push back" price = ceiling

## Pricing Analysis Framework

### Data Synthesis

| Method | Finding | Confidence |
|--------|---------|------------|
| Van Westendorp | Range: $X - $Y, OPP: $Z | High/Med/Low |
| Gabor-Granger | Optimal: $X | High/Med/Low |
| Reference prices | Currently paying $X | High/Med/Low |
| Value quantification | Problem worth $X/month | High/Med/Low |
| Commitments | X people committed at $Y | High/Med/Low |

### Triangulation

**Look for convergence:**
- If Van Westendorp OPP = $89
- And Gabor-Granger optimal = $79
- And reference prices = $50-100
→ Price in $79-99 range is validated

**Red flags:**
- Wide divergence between methods
- Reference prices far below target
- No commitments at target price

### Price Setting Decision

| Factor | Weight | Your Finding | Score |
|--------|--------|--------------|-------|
| Research-based optimal | 30% | | |
| Competitive positioning | 25% | | |
| Value quantification | 25% | | |
| Commitment signals | 20% | | |

### Pricing Model Validation

Also validate the MODEL, not just the price:
- Subscription vs. one-time
- Per user vs. flat rate
- Monthly vs. annual
- Usage-based vs. fixed

**Questions to test model:**
- "How do you typically pay for software like this?"
- "Would you prefer monthly or annual billing?"
- "Does per-user pricing make sense for your team?"

### Risk Assessment

| Price Point | Upside | Downside | Risk Level |
|-------------|--------|----------|------------|
| $79 (low) | Faster adoption | Leave money on table | Low |
| $99 (mid) | Balanced | May need to discount | Medium |
| $129 (high) | Max revenue | Slower adoption | High |

**Recommendation format:**
"Launch at $[X] based on [evidence]. Plan to test $[Y] with segment [Z] within 90 days."

## Pricing Validation Plan

**Product:** _______________
**Target price:** _______________
**Launch date:** _______________

### Methods to Use
- [ ] Van Westendorp PSM (n=100+)
- [ ] Gabor-Granger (n=50+)
- [ ] Reference price research
- [ ] Value quantification
- [ ] Commitment testing
- [ ] A/B testing (if traffic available)

### Timeline
- Week 1-2: Customer interviews (reference prices, value)
- Week 3-4: Survey (Van Westendorp/Gabor-Granger)
- Week 5: Analysis and decision
- Week 6: Commitment testing

### Decision Criteria
Price validated if:
- Within Van Westendorp acceptable range
- Gabor-Granger shows >30% intent
- Reference prices support
- 3+ commitments obtained

## Van Westendorp Price Sensitivity Survey

**Product Description:**
[Clear description of product and value proposition]

**Screening:**
1. Are you a [target customer]? Y/N
2. Do you currently experience [problem]? Y/N

**Price Questions:**

Q1: At what price would you consider [product] to be so expensive
that you would NOT consider buying it?
$_______________

Q2: At what price would you consider [product] to be priced so low
that you would question its quality?
$_______________

Q3: At what price would you consider [product] starting to get expensive—
it's not out of the question, but you'd have to think about buying it?
$_______________

Q4: At what price would you consider [product] to be a bargain—
a great buy for the money?
$_______________

**Additional Context:**
Q5: What do you currently pay for [similar/alternative]?
$_______________

Q6: What would you expect a product like this to cost?
$_______________

name: pricing-validation
category: validation
subcategory: pricing-research
version: 1.0
author: MKTG Skills
source_expert: Van Westendorp, Gabor-Granger
source_work: Price Sensitivity Meter, Price Management
difficulty: intermediate
estimated_value: $5,000 pricing research project
tags: [pricing, validation, research, Van-Westendorp, willingness-to-pay, YC]
created: 2026-01-25
updated: 2026-01-25