Pricing Research Services

Set the Right Price with Confidence

Pricing research is a structured form of market research that identifies the optimal price for a product or service – balancing revenue potential, consumer willingness to pay, and competitive positioning.

But the right price is also a strategic decision. The price that maximizes revenue is often not the same as the price that maximizes market share, and there’s no universally correct answer – the right choice depends on a brand’s current position and goals. TRC’s pricing research is built to inform that decision, giving stakeholders the insight to weigh those trade-offs rather than just a single number.

At TRC Insights, we design and execute pricing research studies using quantitative methodologies including conjoint analysis, Van Westendorp Price Sensitivity Meter, and Gabor-Granger, helping brands in healthcare, financial services, technology, and consumer goods make confident, data-driven pricing decisions.

Talk to TRC pricing expert →

What’s a price people will accept? →

How sensitive is demand to price? →

How do we price against competitors? →

How do we package, bundle, and configure? →

The right pricing research method depends on where you are in the product lifecycle and what decision you need to make. Most pricing decisions come down to four questions – and each question has its own family of proven methodologies. Below are the four families of pricing research solutions we deliver, and the specific methods inside each.

Some methods answer just one of these questions quickly and efficiently; a few – conjoint analysis most of all – can answer several at once, which is why they sit among the most rigorous and resource-intensive.

Van Westendorp Price Sensitivity Meter (PSM)

The Van Westendorp PSM uses four open-ended price questions – “too cheap,” “bargain,” “expensive,” “too expensive” – to identify an acceptable price range and an optimal price point for a product or service. It’s a popular go-to method for narrowing a wide price hypothesis into a workable corridor before later-stage testing. Use it when leadership has a range of candidate prices and you need to defensibly tighten that range. Like open-ended WTP, it doesn’t include competitive products, so its read is on stand-alone acceptability rather than market share.

Open-Ended Willingness to Pay (WTP)

Open-ended WTP is the simplest pricing question in research: a single open-ended item asking what a respondent would pay for a product or service. It produces an average stated WTP that gives you a directional, ballpark price read very early in development. Use it when you need a fast sanity check before investing in concept refinement or a larger study. Limitation: it offers no competitive context, so the conclusions are broad and shouldn’t drive a final price decision on their own.

Gabor-Granger

Gabor-Granger asks each respondent a series of closed-ended purchase-intent questions across a range of prices presented in random order, generating a demand curve and supporting price elasticity estimates. It’s a classic, well-validated method for finding the revenue-maximizing price on a single product. Use it when you need a demand curve and a defensible price recommendation but the decision is about one product, not a competitive set or a feature trade-off. It’s more sample-efficient than monadic testing (described below) but may introduce some bias because respondents evaluate multiple prices.

Two-Dimensional Gabor-Granger (2D Gabor-Granger)

Two-Dimensional Gabor-Granger (2D Gabor-Granger, or 2D-GG), a TRC-developed extension of Gabor-Granger, measures price sensitivity against a second quantitative attribute (e.g. wait time in healthcare, data allowance in telecom, ad load in streaming, repayment term in fintech) and produces demand and revenue curves at each level of that second attribute. Use it when price is one of two attributes that jointly drive the decision and a more robust design, like conjoint, is more than the problem needs. The trade-off is scope: 2D Gabor-Granger handles only two quantitative attributes, so categorical features or three-plus-attribute decisions still call for conjoint.

Monadic Price Testing

Monadic price testing shows each respondent only one price for a product and measures purchase intent, producing the cleanest, least-biased read on demand at each price point tested. Because respondents never see multiple prices, there’s no anchoring or strategic bias to contaminate the result. Use it when you need defensible, unbiased numbers at specific candidate price points – for example, before locking in a launch price. The trade-off is sample size: each price point requires its own cell, so testing five prices means roughly five times the sample of a single-cell study.

Sequential Monadic Price Testing

Sequential Monadic Price Testing walks each respondent through a sequence of prices – starting high and stepping low or vice versa – and measures purchase intent at each step. It produces a price sensitivity curve and identifies the individual threshold where each respondent disengages, answering “how high is too high?” with precision. Use it when you need a demand curve but can’t afford the sample required for a full monadic design. The trade-off is mild bias: because respondents see multiple prices in sequence, the order can subtly influence their responses.

Max-Diff with Pricing

MaxDiff is, at its core, a feature-prioritization method: it presents respondents with sets of items and asks them to pick the most and least appealing in each set, generating a clean rank-order of relative preference across everything tested. Including competitors adds another layer where respondents consider the item and the brand together, so you can measure the interaction of the two.  With pricing, the items become priced options – either whole product or package tiers, or individual features each shown at a specific price point (feature-price pairs) – so you learn not just which features or packages people prefer, but how that preference holds up once a price is attached to each one. It’s especially useful when you have a defined set of priced options and need to know which combinations win and lose against each other. With both competitors and pricing you can find the relative strength of each item, brand, and price. Use it when ranking matters more than absolute share – for instance, prioritizing which of eight priced bundles to take to market, or which feature-price pairs deliver the most perceived value. It works best with a smaller, well-defined set of items; large item lists become respondent-burdensome.

Brand-Price Trade-Off (BPTO)

Brand-Price Trade-Off is a choice-based exercise where respondents repeatedly choose among competing brands at varying prices, revealing how much premium each brand can command before customers switch. It produces brand price premiums, switching curves, and share-of-preference projections across competitive scenarios. Use it when the central question is competitive positioning – for example, quantifying how much more your brand can charge than a private-label or category leader before losing share. The trade-off is scope: BPTO handles brand and price only, not feature differences, and it can grow complex quickly when many brands and price levels are tested.

Conjoint Analysis (Choice-Based and Adaptive)

Conjoint analysis – the most powerful and flexible technique in pricing research – has respondents repeatedly choose among priced product concepts that vary on features, brand, and price, mathematically separating how much each attribute (and each price level) drives the decision. It produces a market simulator capable of estimating willingness to pay, price elasticity, competitive share, optimal feature configurations, and revenue-maximizing price points across virtually any “what if” scenario.

Use it whenever the pricing decision is genuinely multi-dimensional – feature trade-offs, tiered offerings, brand and price together, or competitive launches. It requires defined feature and price ranges, more complex design and analysis, and larger samples, which is why TRC pairs every conjoint engagement with senior methodologists from design through simulator delivery.

Explore TRC’s choice-modeling expertise:  Bracket™  •  Two Dimensional Max-Diff (2DMD)™  •  Agile Suite™

Menu-Based Choice (MBC)

Menu-Based Choice presents respondents with a menu of priced items, add-ons, or modules and lets them select any combination they’d actually buy, mirroring how customers shop à la carte and bundled offerings in the real world. It produces a market simulator that estimates the expected take rate for each menu item at a given price, from which you can calculate revenue and evaluate pricing and packaging decisions, including bundle discounts, add-on pricing, and tiered menus. Because it captures which items respondents choose together, MBC also reveals which products act as complements or substitutes. Use it when the pricing decision is about menu and bundle design, common in software, financial services, telecom, and subscription businesses. MBC is more complex and longer for respondents than other methods, requires careful design, and benefits from larger samples.

Build-Your-Own (Configurator) with Pricing

Build-Your-Own – also called configurator-based research – lets respondents construct their ideal product by selecting feature levels (basic, standard, premium) at the prices you specify, revealing which feature combinations and price points customers actually choose. Because everyone builds from the same menu, patterns emerge: features almost everyone keeps signal must-haves, while selectively chosen ones point to nice-to-have or premium upgrades. The output shows preference by feature level and by combination, useful for designing tiered offerings and good/better/best lineups. Use it when you have a well-defined feature list and want to see what bundles customers self-assemble.

Greenbook.org, the market research industry directory, reached out to our clients and verified their reviews of TRC.

What is pricing research?

Pricing research is a category of market research that uses surveys, choice exercises, and statistical modeling to determine how customers will respond to different prices, price packages, and competitive positions. It produces evidence-based recommendations on launch prices, price changes, bundle structures, and revenue-maximizing strategies.

Which pricing research method should I use?

The right method depends on the decision you need to make. For an early-stage ballpark price, use open-ended WTP or Van Westendorp. For a demand curve at specific price points, use monadic testing, price laddering, or Gabor-Granger. For pricing against named competitors, use BPTO or MaxDiff with pricing. For bundles, tiered offerings, or feature-and-price trade-offs, use Build-Your-Own, Menu-Based Choice, or conjoint analysis.

What is the difference between Van Westendorp and Gabor-Granger?

Van Westendorp asks four open-ended price questions (too cheap, bargain, expensive, too expensive) to identify an acceptable price range and an optimal price point — it’s a stand-alone acceptability read. Gabor-Granger asks closed-ended purchase-intent questions across a range of specific prices to produce a demand curve and price elasticity estimate — it gives you a revenue-maximizing price recommendation. Van Westendorp is faster and earlier-stage; Gabor-Granger is more rigorous and later-stage.

What is conjoint analysis in pricing research?

Conjoint analysis is a choice-based research method in which respondents repeatedly choose among priced product concepts that vary on features, brand, and price. Statistical modeling then separates how much each attribute and each price level drives the decision, producing a market simulator capable of estimating willingness to pay, price elasticity, competitive share, and revenue-optimal configurations across virtually any “what if” scenario.

How long does a pricing research study take?

Timelines depend on methodology and complexity. A Van Westendorp or open-ended WTP study can field and report in 2–3 weeks. A Gabor-Granger or monadic study typically runs 3–5 weeks. A full choice-based conjoint or Menu-Based Choice study, including design, fielding, modeling, and simulator delivery, generally runs 6–10 weeks. TRC’s Agile Suite™ accelerates several of these timelines significantly.

How does TRC choose the right pricing research method for a project?

TRC’s senior methodologists scope every project around three things: the decision the client needs to make, the stage of the product or pricing lifecycle, and the constraints on sample, time, and budget. Method selection is the first deliverable on every engagement, and it’s done by senior team members — not by a junior account manager filling a template.