Product and pricing strategy research
Product and pricing research turns "what should we build and what should it cost?" into measurable questions: test concepts, prioritize features, optimize packages, and quantify pricing opportunities with methodologies designed for complex markets. Razberri fields these studies with the methods pricing work actually uses, pretested with AI personas first, because pricing questions are the easiest for respondents to misread.
Which pricing research methods does Razberri support?
Razberri ships with the pricing and prioritization methods in the box: MaxDiff, conjoint, Van Westendorp, Gabor-Granger, forced ranking, trade-off exercises, packaging and tier tests, and dynamic follow-ups. All are available as preconfigured question modules rather than instruments rebuilt from scratch for every study.
| Method | Question it answers | When to use it |
|---|---|---|
| Van Westendorp (Price Sensitivity Meter) | What price range does the market consider acceptable? | Early-stage pricing, or products without an established reference price |
| Gabor-Granger | How likely are buyers to purchase at specific price points? | Testing demand and revenue trade-offs across candidate prices for a defined offer |
| Conjoint | Which combinations of features and price do buyers prefer? | Package design and feature-price trade-offs, where attributes compete |
| MaxDiff | Which features or messages matter most, in rank order? | Prioritizing long lists (features, claims, needs) where rating scales flatten everything to 'important' |
| Packaging and tier tests | Which bundle structure fits how the market buys? | Moving from a single price point to a price architecture |
How do you measure willingness to pay with a survey?
Never by asking "what would you pay?" outright: direct asks invite bargaining, not truth. Structured methods work around that: Van Westendorp locates the acceptable price range from four framed price-perception questions, and Gabor-Granger measures purchase likelihood at specific price points to trace a demand curve.
Which to use depends on how defined the offer is: Van Westendorp suits an offer whose price anchor doesn't exist yet; Gabor-Granger suits a concrete offer with candidate price points to stress; conjoint takes over when price is one attribute competing among several. Because every method here rests on respondents parsing carefully framed questions, instrument quality is the whole game, which is what the pretest section below is about.
How do you prioritize features with MaxDiff?
MaxDiff shows respondents small sets of features and forces a choice: which matters most, which least. Repeated across randomized sets, those forced trade-offs yield a ranked, spaced priority list, where a rating scale would have let respondents call everything important.
The output reads directly into roadmap and packaging decisions: what belongs in the core offer, what carries an upgrade tier, what nobody will pay for. Cut the results by segment to see whose priorities differ: segmentation groups respondents by needs, behavior, and spend, then compares every metric across the segments that matter.
Why pretest pricing surveys with AI personas first?
Because willingness-to-pay and concept questions are the most misunderstanding-prone instruments in survey research: a respondent who misreads a price frame or a feature description produces confident, wrong data. A persona pretest run is cheap insurance on the study that sets your price.
Razberri drafts AI personas from your audience definition and runs them through the draft instrument; they surface leading phrasing, questions the audience cannot answer, and logic dead-ends while a fix still costs nothing. See AI persona pretesting. Pricing studies also deserve the mechanical pass: overlapping price ranges, flipped scales, and screener leaks are exactly what a systematic pre-launch pass exists to catch.
Frequently asked questions
Do I need conjoint, or is a simpler method enough?
Match the method to the decision. A single product hunting for an acceptable range: Van Westendorp. A defined offer testing candidate price points: Gabor-Granger. Features and price competing inside a package decision: conjoint. Prioritizing a long feature list: MaxDiff. Complexity you don't need buys longer surveys and harder analysis.
Why do pricing questions need extra care in wording?
Price framing is fragile: an ambiguous currency basis, an unclear billing period, or a leading frame shifts answers systematically rather than randomly. That is why pricing research pairs structured methods with a real pretest (personas plus careful human review) before the study everyone will quote gets fielded.
How quickly can pricing analysis turn around?
Analysis runs while fieldwork is still open: prebuilt methods execute the moment responses land, and natural-language queries cut live results without exports or an analyst queue. The readout takes shape during fielding, not weeks after it.
Does this work for B2B pricing studies?
Yes. The harder part of B2B pricing is reaching the right respondents, and that is screener work: qualifying the roles, firmographics, and behaviors that make a respondent worth listening to, across verticals like technology, healthcare, industrials, and financial services.
Talk to us about your research.
Book a 30-minute walkthrough and see a study built on your own case context: designed, pretested with AI personas, and ready to field.