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4.5 KiB
4.5 KiB
Pricing Research Methods
Van Westendorp Price Sensitivity Meter
The Van Westendorp survey identifies the acceptable price range for your product.
The Four Questions
Ask each respondent:
- "At what price would you consider [product] to be so expensive that you would not consider buying it?" (Too expensive)
- "At what price would you consider [product] to be priced so low that you would question its quality?" (Too cheap)
- "At what price would you consider [product] to be starting to get expensive, but you still might consider it?" (Expensive/high side)
- "At what price would you consider [product] to be a bargain—a great buy for the money?" (Cheap/good value)
How to Analyze
- Plot cumulative distributions for each question
- Find the intersections:
- Point of Marginal Cheapness (PMC): "Too cheap" crosses "Expensive"
- Point of Marginal Expensiveness (PME): "Too expensive" crosses "Cheap"
- Optimal Price Point (OPP): "Too cheap" crosses "Too expensive"
- Indifference Price Point (IDP): "Expensive" crosses "Cheap"
The acceptable price range: PMC to PME Optimal pricing zone: Between OPP and IDP
Survey Tips
- Need 100-300 respondents for reliable data
- Segment by persona (different willingness to pay)
- Use realistic product descriptions
- Consider adding purchase intent questions
Sample Output
Price Sensitivity Analysis Results:
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Point of Marginal Cheapness: $29/mo
Optimal Price Point: $49/mo
Indifference Price Point: $59/mo
Point of Marginal Expensiveness: $79/mo
Recommended range: $49-59/mo
Current price: $39/mo (below optimal)
Opportunity: 25-50% price increase without significant demand impact
MaxDiff Analysis (Best-Worst Scaling)
MaxDiff identifies which features customers value most, informing packaging decisions.
How It Works
- List 8-15 features you could include
- Show respondents sets of 4-5 features at a time
- Ask: "Which is MOST important? Which is LEAST important?"
- Repeat across multiple sets until all features compared
- Statistical analysis produces importance scores
Example Survey Question
Which feature is MOST important to you?
Which feature is LEAST important to you?
□ Unlimited projects
□ Custom branding
□ Priority support
□ API access
□ Advanced analytics
Analyzing Results
Features are ranked by utility score:
- High utility = Must-have (include in base tier)
- Medium utility = Differentiator (use for tier separation)
- Low utility = Nice-to-have (premium tier or cut)
Using MaxDiff for Packaging
| Utility Score | Packaging Decision |
|---|---|
| Top 20% | Include in all tiers (table stakes) |
| 20-50% | Use to differentiate tiers |
| 50-80% | Higher tiers only |
| Bottom 20% | Consider cutting or premium add-on |
Willingness to Pay Surveys
Direct method (simple but biased): "How much would you pay for [product]?"
Better: Gabor-Granger method: "Would you buy [product] at [$X]?" (Yes/No) Vary price across respondents to build demand curve.
Even better: Conjoint analysis: Show product bundles at different prices Respondents choose preferred option Statistical analysis reveals price sensitivity per feature
Usage-Value Correlation Analysis
1. Instrument usage data
Track how customers use your product:
- Feature usage frequency
- Volume metrics (users, records, API calls)
- Outcome metrics (revenue generated, time saved)
2. Correlate with customer success
- Which usage patterns predict retention?
- Which usage patterns predict expansion?
- Which customers pay the most, and why?
3. Identify value thresholds
- At what usage level do customers "get it"?
- At what usage level do they expand?
- At what usage level should price increase?
Example Analysis
Usage-Value Correlation Analysis:
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Segment: High-LTV customers (>$10k ARR)
Average monthly active users: 15
Average projects: 8
Average integrations: 4
Segment: Churned customers
Average monthly active users: 3
Average projects: 2
Average integrations: 0
Insight: Value correlates with team adoption (users)
and depth of use (integrations)
Recommendation: Price per user, gate integrations to higher tiers