1# Pricing Research Methods
2 
3## Contents
4- Van Westendorp Price Sensitivity Meter (The Four Questions, How to Analyze, Survey Tips, Sample Output)
5- MaxDiff Analysis (How It Works, Example Survey Question, Analyzing Results, Using MaxDiff for Packaging)
6- Willingness to Pay Surveys
7- Usage-Value Correlation Analysis
8 
9## Van Westendorp Price Sensitivity Meter
10 
11The Van Westendorp survey identifies the acceptable price range for your product.
12 
13### The Four Questions
14 
15Ask each respondent:
161. "At what price would you consider [product] to be so expensive that you would not consider buying it?" (Too expensive)
172. "At what price would you consider [product] to be priced so low that you would question its quality?" (Too cheap)
183. "At what price would you consider [product] to be starting to get expensive, but you still might consider it?" (Expensive/high side)
194. "At what price would you consider [product] to be a bargain—a great buy for the money?" (Cheap/good value)
20 
21### How to Analyze
22 
231. Plot cumulative distributions for each question
242. Find the intersections:
25   - **Point of Marginal Cheapness (PMC):** "Too cheap" crosses "Expensive"
26   - **Point of Marginal Expensiveness (PME):** "Too expensive" crosses "Cheap"
27   - **Optimal Price Point (OPP):** "Too cheap" crosses "Too expensive"
28   - **Indifference Price Point (IDP):** "Expensive" crosses "Cheap"
29 
30**The acceptable price range:** PMC to PME
31**Optimal pricing zone:** Between OPP and IDP
32 
33### Survey Tips
34- Need 100-300 respondents for reliable data
35- Segment by persona (different willingness to pay)
36- Use realistic product descriptions
37- Consider adding purchase intent questions
38 
39### Sample Output
40 
41```
42Price Sensitivity Analysis Results:
43─────────────────────────────────
44Point of Marginal Cheapness:  $29/mo
45Optimal Price Point:          $49/mo
46Indifference Price Point:     $59/mo
47Point of Marginal Expensiveness: $79/mo
48 
49Recommended range: $49-59/mo
50Current price: $39/mo (below optimal)
51Opportunity: 25-50% price increase without significant demand impact
52```
53 
54---
55 
56## MaxDiff Analysis (Best-Worst Scaling)
57 
58MaxDiff identifies which features customers value most, informing packaging decisions.
59 
60### How It Works
61 
621. List 8-15 features you could include
632. Show respondents sets of 4-5 features at a time
643. Ask: "Which is MOST important? Which is LEAST important?"
654. Repeat across multiple sets until all features compared
665. Statistical analysis produces importance scores
67 
68### Example Survey Question
69 
70```
71Which feature is MOST important to you?
72Which feature is LEAST important to you?
73 
74□ Unlimited projects
75□ Custom branding
76□ Priority support
77□ API access
78□ Advanced analytics
79```
80 
81### Analyzing Results
82 
83Features are ranked by utility score:
84- High utility = Must-have (include in base tier)
85- Medium utility = Differentiator (use for tier separation)
86- Low utility = Nice-to-have (premium tier or cut)
87 
88### Using MaxDiff for Packaging
89 
90| Utility Score | Packaging Decision |
91|---------------|-------------------|
92| Top 20% | Include in all tiers (table stakes) |
93| 20-50% | Use to differentiate tiers |
94| 50-80% | Higher tiers only |
95| Bottom 20% | Consider cutting or premium add-on |
96 
97---
98 
99## Willingness to Pay Surveys
100 
101**Direct method (simple but biased):**
102"How much would you pay for [product]?"
103 
104**Better: Gabor-Granger method:**
105"Would you buy [product] at [$X]?" (Yes/No)
106Vary price across respondents to build demand curve.
107 
108**Even better: Conjoint analysis:**
109Show product bundles at different prices
110Respondents choose preferred option
111Statistical analysis reveals price sensitivity per feature
112 
113---
114 
115## Usage-Value Correlation Analysis
116 
117### 1. Instrument usage data
118Track how customers use your product:
119- Feature usage frequency
120- Volume metrics (users, records, API calls)
121- Outcome metrics (revenue generated, time saved)
122 
123### 2. Correlate with customer success
124- Which usage patterns predict retention?
125- Which usage patterns predict expansion?
126- Which customers pay the most, and why?
127 
128### 3. Identify value thresholds
129- At what usage level do customers "get it"?
130- At what usage level do they expand?
131- At what usage level should price increase?
132 
133### Example Analysis
134 
135```
136Usage-Value Correlation Analysis:
137─────────────────────────────────
138Segment: High-LTV customers (>$10k ARR)
139Average monthly active users: 15
140Average projects: 8
141Average integrations: 4
142 
143Segment: Churned customers
144Average monthly active users: 3
145Average projects: 2
146Average integrations: 0
147 
148Insight: Value correlates with team adoption (users)
149        and depth of use (integrations)
150 
151Recommendation: Price per user, gate integrations to higher tiers
152```
153