Modern Pricing & UBB
February 26, 2026 pricing

Willingness-to-Pay Research for Founders Who Hate Surveys

"What would you pay for this?" is the question that sounds obvious and produces useless data. Ask it in a survey and you get aspirational non-answers. Ask it in a sales call and you're letting your prospect set the anchor. Ask it in a focus group and you get groupthink contaminated by whoever speaks first.

Willingness-to-pay (WTP) research is hard because the question triggers social signaling, not genuine economic reflection. But there are rigorous methods that actually work — they just require more structure than a Google Form with a free text box.

Why Competitor Benchmarking Is the Wrong Starting Point

The first instinct of almost every founder is to open a few competitor pricing pages, pick a number in the range, and call it done. This is rational if you have zero other information and need to ship a pricing page today. It's a mistake if you're making a considered pricing decision.

Competitor pricing tells you what they think their customers will pay, filtered through their cost structure, their GTM motion, their positioning, and their historical pricing decisions. Their number has nothing to do with your customers' willingness to pay for your specific value proposition. ProfitWell's research (now Paddle's pricing team) on 30,000+ SaaS companies found that companies that set prices primarily based on competitor benchmarking underpriced by an average of 30%. The market average is set by companies with average pricing sophistication. If you match the average, you get average outcomes.

Van Westendorp: The Price Sensitivity Meter

Van Westendorp's Price Sensitivity Meter is a four-question survey methodology that finds the acceptable price range for a product without asking "what would you pay?" directly. The four questions:

  1. At what price would you consider this product so expensive you would not consider buying it? (too expensive)
  2. At what price would you consider this product to be priced so low that you would question its quality? (too cheap)
  3. At what price would you consider this product starting to get expensive, but still worth considering? (expensive but acceptable)
  4. At what price would you consider this product to be a bargain — a great buy for the money? (cheap / good value)

Plot the cumulative distributions of all four responses. The intersection of "too expensive" and "not expensive enough" gives you the acceptable price range. The intersection of "too cheap" and "not cheap enough" gives you the point of marginal cheapness — the price below which quality is questioned. Most founders are surprised to discover their optimal price point is significantly higher than their gut instinct.

Van Westendorp works best with 50+ responses from your target customer segment. It's not a replacement for quantitative market research, but it can be run in a day with your existing customer base and reliably surfaces a price range to work within.

Conjoint Analysis for Complex Products

When your product has multiple features with different value levels, conjoint analysis is the gold standard. You present respondents with a series of hypothetical product configurations — different combinations of features and prices — and ask them to choose their preference. Statistical analysis of the choices reveals the implied value each respondent places on each feature, and at what price trade-offs start occurring.

This is more sophisticated than most early-stage companies need, but it's essential if you're designing a tiered pricing structure and want to know which features should be in Starter vs. Pro vs. Enterprise. Conjoint data tells you which features justify tier upgrades and which are better served by inclusion in lower tiers to drive adoption. SBI's 2024 pricing research identifies conjoint analysis as the most reliable method for feature-level pricing decisions in B2B software.

The 5 Customer Interview Questions That Actually Work

For founders who want qualitative WTP signal without formal survey methods, these five questions — asked in sequence in a customer interview — consistently surface useful price anchors:

  1. "What would you be doing instead of this if our product didn't exist?" — This reveals the alternatives you're displacing and their implicit cost.
  2. "How much does [the problem you solve] cost you right now, in time and/or money?" — Quantify the pain. WTP correlates with pain magnitude, not feature count.
  3. "When you think about other tools you pay for, what's in that budget range?" — Let them anchor to something real they already pay for. This surfaces their mental budget category for your product.
  4. "If the price doubled tomorrow, would you still use it?" — Yes/no with reasoning. Push for the reasoning — that's where the insight is. "Yes, because we get 10x the value" is very different from "yes, because switching costs are too high."
  5. "At what price point would this become a no-brainer that everyone in your category should be using?" — This inverts the question and often surfaces a price lower than your current price — which is a feature-set problem, not a pricing problem.

These questions work because they're indirect. You're asking about behavior and context, not asking people to construct a hypothetical willingness-to-pay number. Real decisions produce real anchors. Hypotheticals produce noise.

The synthesis: do Van Westendorp with 50-100 survey respondents for the price range, do customer interviews with 10-15 ideal customers for context and qualitative signal, and use conjoint analysis if you're designing a multi-tier structure and need feature-level data. In that order. Competitor benchmarking is the starting point for the lazy and the validation for the disciplined.

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