Priced vs Unpriced Concept Testing: When to Show Price
A worked lamp example explains when to show price, how to uncover assumed costs and what a priced-versus-unpriced comparison can support.
Show price in a concept test when the decision concerns a complete offer buyers could purchase. Leave it out when you need an earlier read on what the product means, which problem it solves or what people assume it would cost. The distinction matters because someone who likes a desk lamp at an imagined $25 hasn't evaluated the same offer as someone shown a $49 price.
An unpriced concept doesn't remove price from the buyer's thinking. It leaves the amount unstated. Before using a favorable response to justify development, find out which version of the offer the respondent had in mind.
What each version lets you decide
An unpriced test can help a product team decide whether a description communicates a useful idea before settling its commercial terms. Buyers can explain the job they think the product does, what seems unnecessary and what they would compare it with. That can be valuable while the team is still choosing a direction.
A priced test gives the buyer a specified cost to consider alongside those benefits. It belongs in decisions about whether to develop or pilot a particular offer. The price needs a basis: one item or a bundle, a one-time payment or a subscription, and any delivery charges or required commitment.
Relevant Insights treats price presence as an explicit concept-test design choice, alongside brand, copy and visual presentation. Specify that choice in the brief. A supplier shouldn't have to guess whether the study is exploring the product idea or evaluating an offer at its planned price.
Neither version answers every pricing question. Testing one price against no stated price doesn't identify the best price, reveal a demand curve or measure willingness to pay across the market. Those questions need their own design, covered in our pricing research methods guide.
A $49 lamp and the price buyers imagine
Consider a home-office accessories team deciding whether to prototype an adjustable desk lamp. Its intended buyers are US adults who work at home, use a desk lamp and expect to consider replacing it within six months. The product, terms and dollar amounts below are illustrative inputs for planning a study.
Both versions show the same lamp image and description: an adjustable arm, three brightness settings, and an included power adapter. The lamp plugs into an outlet; it isn't battery powered. It's sold through the team's online store as a one-time purchase, with delivery to the contiguous United States.
Version | Price information on the card |
|---|---|
Unpriced | The price line is omitted. All other product, purchase and delivery information stays the same. |
Priced | US$49 for one lamp and adapter, including standard delivery, before any applicable sales tax. No subscription. |
Keep the one-time purchase and absence of a subscription clear in both cards. The intended difference is disclosure of the dollar amount and what that amount covers. Save the exact text and image for each version so the report can identify what people actually saw.
The example isn't asking whether shoppers prefer a $49 lamp to a cheaper competitor. It's asking how the proposed lamp is interpreted with and without its stated price. A later choice study could compare the lamp with defined alternatives, including keeping the buyer's current lamp.
Our product concept statement guide explains how to turn product facts and purchase terms into a readable card. Keep the cards equally clear and polished; a rough unpriced sketch and a finished priced advertisement would change more than price disclosure.
A price reveal can't give you two first impressions
For a human study comparing independent first reactions, randomly assign eligible buyers to one version. Each person sees either the priced or unpriced lamp first. Plan enough responses for the comparison and buyer groups the business needs, with the same recruitment rules and core questions in both conditions.
Showing everyone the unpriced card and then revealing $49 can serve a different purpose. In an interview, the change can prompt a useful explanation: perhaps the buyer expected an inexpensive replacement, or assumed the lamp would include a feature it doesn't have. Ask what changed and why.
The later response is shaped by the earlier card and questions. It isn't an independent priced-first reaction. Pew Research Center's questionnaire guidance explains how earlier questions can influence later answers. Report a sequential reveal as a reveal exercise, rather than combining it with a separate-group comparison. Our monadic testing guide covers the exposure choices.
Keep brand information constant, too. Removing a familiar brand while hiding the price would combine two changes. If brand exposure is itself the decision, our branded vs unbranded concept-testing guide gives that comparison its own design.
The questions need to uncover the assumed offer
Begin with understanding. Ask buyers to describe what the lamp includes, how they'd use it and what problem, if any, it would solve at their desk. Then examine relevance, concerns and the alternatives they'd consider. Use the same wording and answer options for questions intended to be compared across conditions.
After those core answers, ask the unpriced group what they expected to pay and what they thought that amount included. Place this question late enough to preserve the intended initial reaction. Record “don't know” rather than forcing everyone to invent a figure. An assumed price is a clue about interpretation, not a maximum willingness to pay.
In the priced group, check what people believe the $49 covers and whether they noticed the delivery and tax terms. Someone who assumes a battery is included may be reacting to a different product, even if they read the price correctly. Don't explain the missing feature before collecting that first understanding.
Sapien can help examine these interpretations with data-grounded simulated buyers before a team commits to a larger study. For this lamp, the useful output would identify which benefits, omissions or price expectations need investigation. Keep simulated answers labeled, and use relevant human evidence when the decision depends on how actual shoppers respond to the price.
A weaker priced response needs an explanation
Suppose the priced version receives lower consideration. That finding alone wouldn't show that $49 is too high. Buyers might understand the offer and find poor value, misunderstand what's included, or like the idea only at a much lower assumed price. Those explanations call for different changes.
If buyers miss a genuine inclusion, improve its visibility and recheck understanding. If they understand the lamp but prefer keeping their current one, investigate whether the benefit warrants a replacement. If a lower price is commercially feasible, test that complete offer separately. Don't remove features or change the description at the same time and attribute the resulting difference to price alone.
Ask the report to show each condition, buyer group, exact question and answer option, with counts, percentages, valid answering bases and missing responses. Keep the full response distribution alongside any summary. Show differences and appropriate uncertainty for the human study design; keep coded explanations and assumed-price answers attached to their original condition. Generated response counts don't carry the same sampling interpretation as human responses.
The next commitment should match the evidence. An unpriced test can justify revising or developing an idea. A priced test can help choose an offer for a pilot. For the lamp team, spending on production still needs evidence about physical use, actual purchases and the economics of supplying the product at the chosen price.
