Most companies under-price both existing and new products/services. How do we know?

Because for new products, we have conducted more than 80 pricing research studies, and only one company had set their pricing correctly. The rest had opportunities to improve pricing by 10–300%. No, 100–300% is not at all unusual; in fact, 21% of the companies could charge this much more.

For existing products, our 120+ pricing research studies have shown that 9 out of 10 companies have prices below what they could charge. Typically, the range is 5–10%, although it is not uncommon to see even greater potential. The majority falls within 5–7%, yet results may vary considerably across different customer markets.

Understanding customers’ willingness to pay in detail has therefore proven to be one of the greatest levers for increasing revenue and profit. Most companies simply price too low due to fear, outdated ‘war stories,’ customers playing the game even when they have strong preferences for your product.

There are many pricing research methods each with their pros and cons.

Choosing the right pricing research method depends on the depth of insight required, the level of statistical robustness needed, and the complexity of customer decision-making you want to capture.

What we find serves most needs best is:

  • 1:1 interviews for depth,
  • Van Westendorp for simpler needs, and
  • Choice-based conjoint for more complex or advanced needs.

Please see the overview below, including starting prices that will apply in most cases.

Note regarding Van Westendorp: we have adapted it, since the original four-question approach has important limitations, which we have addressed.

Methodology 1:1 Interviews Quantitative – Adapted Van Westendorp Quantitative – Choice-Based Conjoint
Typical Sample Size 20 in-depth interviews 50+ structured interviews Varies (based on market/product complexity)
Key Insights
  • Customer perception of product value and pricing vs. competitors
  • Qualitative input on product/service improvements
  • Broad indicative understanding of price flexibility
  • Similar insights, as from from 1:1 interviews, but less dept, PLUS:
  • Price elasticity measurement
  • Identification of critical price points where customer switching is likely to occur
  • Similar insights as from Quantitative Price questioning, PLUS:
  • Competitive brand value assessment (if included)
  • Market simulation tool to predict real-world purchase behavior
  • Pricing elasticity across multiple product configurations
  • Optimization of product features based on economic value
Best Use Cases
  • When customer base is homogeneous
  • limited set of differentiation attributes
  • Deep-dive insights
  • When broader customer input is needed
  • For benchmarking price flexibility in competitive markets
  • To understand price thresholds for switching behavior
  • When robust statistical validation is required
  • To optimize complex pricing structures
  • For market-driven product and pricing strategies
Limitations
  • Subjective and qualitative
  • Small sample size
  • Less depth per customer than 1:1 interviews
  • Does not fully capture decision trade-offs
  • Requires more setup and customization
  • Higher complexity and cost, but strongest predictive power
Price €9,000 €14,000* (one country, ex. panel costs) €20,000* (one country, ex. panel costs)

* Starting prices. Sometimes there are additional needs, more countries to survey and requirement to recruit from panels that all bears extra costs.

What should you choose?

1:1 Interviews – Deep, Exploratory Pricing Insights

If you need a qualitative understanding of how customers perceive your pricing and product, 1:1 interviews provide rich, in-depth insights. This method is ideal for homogenous markets and niche markets.

Quantitative Traditional Price Questioning – Data-Backed Pricing Decisions

For companies needing a broader, more statistically robust assessment of price elasticity and competitive positioning, structured surveys provide clear decision points on pricing flexibility and switching behaviors. This approach is useful when customers are diverse and pricing decisions require stronger validation than qualitative interviews alone.

Advanced Choice-Based Conjoint – Predictive Market & Pricing Optimization

If you require high-confidence pricing insights, advanced conjoint research delivers a market simulator that replicates real customer purchasing behaviors. By analyzing trade-offs and competitive positioning, this approach optimizes product offerings and pricing structures to maximize revenue and market share.