Three ways to ask without asking directly
Asking "how much would you pay?" produces useless answers. The methods that work force a choice, not an opinion.
- Conjoint analysis: the customer chooses between complete bundles, and the model infers the value of each attribute separately.
- NS Price Threshold: four price questions — too cheap, cheap, expensive, too expensive — that bound an acceptable range.
- Gabor-Granger: purchase intent is tested at different price points to trace the demand curve.
- Field experiments: different prices in comparable markets, with a control group.
The mistake of measuring the average
The average willingness to pay does not exist as an actual customer. What matters is the distribution: if 30% of the market pays 40% more for a specific attribute, the problem isn't the price but the absence of a higher tier that captures that segment. Correct measurement doesn't produce a number, it produces a portfolio architecture.
From the study to the decision
A willingness-to-pay study is only useful if it translates into three concrete decisions: which product tiers exist, which attribute justifies the price jump between one and the next, and on what metric to charge. Changing the billing metric — from unit to usage, from license to outcome — usually moves revenue more than adjusting the price level.
Validate in the P&L before launching
Every price recommendation must pass through a simulator that combines estimated elasticity, current mix, and variable cost, to show the range of profit impact under pessimistic, base, and optimistic scenarios. A committee approves price changes when it sees the floor, not just the ceiling.
Key takeaways
- Forced-choice methods give better data than direct price questions.
- The distribution of willingness to pay defines the portfolio, not just the price level.
- Changing the billing metric usually moves revenue more than adjusting price.
NS frameworks and reference sources
- Proprietary NS framework · P2P·NS — methodological notes from the Pricing & Revenue Management practice
- NS project base: anonymized cases by sector and geography
- Open market evidence and academic literature, recalibrated with client data
- McKinsey & Company — 'The power of pricing' (pocket-price waterfall)
- Simon-Kucher & Partners — Global Pricing Study
- Nagle & Müller — The Strategy and Tactics of Pricing
This article develops proprietary NS Business Strategy frameworks, drawing on our project base and on public industry literature and studies cited above. Figures are reference ranges; each project is measured against the client's actual data.