Should I Charge $9, $19, or $29? How to Actually Answer This Instead of Guessing

You have narrowed it down to three numbers. Nine dollars feels safe but maybe too cheap to be taken seriously. Nineteen feels like the obvious middle choice, which is exactly what makes you suspicious of it. Twenty nine feels bold, maybe too bold, and you genuinely have no idea which of the three is actually right. So you pick one, mostly based on what a competitor charges or what number simply feels least uncomfortable to type into a pricing page, and you move on.

This is how most early pricing decisions get made, and it is almost entirely guesswork dressed up as a decision. The good news is that you do not need a data science team or an expensive consultant to do meaningfully better than a gut feeling. You need a specific, well tested technique that was built for exactly this situation.

Asking directly what someone would pay does not work

The most intuitive approach, simply asking potential customers what they would pay, is also one of the least reliable, and it is worth understanding exactly why before trying anything else. When there is no real money and no real commitment actually on the line, people have very little incentive to answer carefully or honestly. Someone might name a low number to seem financially savvy, or a high number to seem sophisticated, and either way their stated answer often has little connection to what they would actually pay once a real transaction is genuinely in front of them.

This is not a character flaw in the people you are asking. It reflects a well documented pattern that affects almost everyone when a hypothetical question replaces a real decision. Since this bias is so consistent, the smarter path is not asking the question more carefully. It is asking a different kind of question entirely, one that does not rely on a single direct number at all.

A four question technique built specifically for this problem

A widely used pricing research method sidesteps the direct question entirely by asking four related but differently framed questions about the same product. At what price would this feel so cheap that you would question its quality. At what price would this feel like a genuine bargain. At what price would this start to feel expensive. And at what price would this feel so expensive that you would not consider buying it at all.

Notice that none of these four questions ask directly what someone would pay. Each one anchors the respondent to a different psychological reference point, quality doubt, bargain, expensive, and prohibitive, which together triangulate toward a genuine, defensible price range rather than relying on one single, unreliable direct answer.

Turning four answers into an actual range

Once you collect these four answers from a reasonable number of people in your target market, even a modest sample, you can plot how the answers to each question accumulate across your respondents. The specific points where these accumulated answer patterns intersect define your acceptable price corridor: a lower bound near where prices start to seem too cheap to trust, and an upper bound near where prices start to seem prohibitively expensive.

This gives you something meaningfully more useful than nine, nineteen, or twenty nine as three isolated guesses. It gives you an actual range grounded in how your specific target market thinks about value for this specific type of product, which you can then use to make a more informed final decision rather than picking blind.

The range will not hand you one exact number, and that is fine

A common frustration with this approach is that it produces a range rather than declaring one single, definitive correct price. This is not a limitation to work around. It reflects an honest truth about pricing that a single number pretends does not exist: there genuinely is a range of prices your market will accept, not one precise correct answer sitting out there waiting to be discovered.

Your job at that point becomes choosing where within that defensible range to actually land, based on other real considerations. Are you trying to maximize volume and land toward the lower end of the range. Are you trying to signal premium positioning and land toward the higher end. Do you have reason to believe a specific number, like nineteen dollars specifically, carries a psychological advantage within your validated range. These are legitimate business judgment calls, but they are being made on top of real evidence about what your market will actually bear, rather than replacing that evidence entirely.

Test purchase likelihood directly as a second angle

A complementary technique presents your product at a specific price and asks directly whether someone would purchase it at that exact price, then repeats the question at different price points in sequence. Unlike the four question method, this approach anchors much more directly to an actual purchase decision, which some people find gives a more concrete, action oriented signal, even though it still relies on stated intent rather than a truly binding commitment.

Combining the resulting purchase likelihood at each tested price with the price itself lets you estimate expected revenue at each point, revealing which specific price is likely to maximize your actual revenue rather than simply maximizing the number of units sold at the cheapest tested price. A lower price that converts more people is not automatically the better choice once you do this multiplication and see the actual revenue outcome side by side.

Neither method replaces watching real behavior

Both of these techniques are genuine improvements over guessing, but they still rely on people telling you what they would do rather than actually doing it. Wherever it is realistically possible, validating your final range against real behavior, even something as simple as a small live test showing different prices to different groups of actual visitors and measuring genuine conversion, gives you a stronger, more trustworthy answer than stated preference research alone can ever fully provide.

This does not mean skipping the research phase and jumping straight to a live test. It means using the research to narrow a wide field of plausible prices down to a small, genuinely promising set worth testing further, rather than either guessing blindly or trying to test every conceivable price point live from day one at real cost and real risk to your actual customers.

Revisit your price as your product and market evolve

A price validated today is not necessarily still the right price a year from now. As your product adds real value, as your target customer shifts, or as your competitive landscape changes, the range your market will genuinely bear shifts along with it. Treating your initial pricing decision as permanent, rather than periodically revalidating it using the same techniques, leaves real money on the table in one direction or genuine customer resistance building quietly in the other.

Watch for the difference between what people say and what a real transaction reveals

Even the more structured pricing techniques described here still rely on stated responses rather than a fully binding commitment, and it is worth holding onto a healthy amount of skepticism even about a well constructed price range. If you have any way to test a small, real transaction, even something as modest as a limited early access offer at a specific price with a genuine payment required, that single real data point is worth more than a much larger volume of stated survey responses, because it reflects an actual decision rather than a hypothetical one.

This does not mean the research techniques described earlier are not worth doing. It means treating their output as a well informed starting range to test against reality, rather than as a final, settled answer that removes all remaining uncertainty about what your market will actually pay once real money changes hands.

Do not let a single competitor's price anchor you completely

It is tempting to simply look at what a similar competitor charges and treat that number as a natural ceiling or floor for your own pricing decision. This can be a useful reference point, but it carries a real risk if that competitor's price was itself never properly validated, since you could easily be anchoring your own careful research against a number that was just as much of a guess when it was originally set.

A more useful approach treats a competitor's price as one input among several, worth noting but not worth deferring to entirely, especially once you have your own genuine range from asking your own specific target market the right kind of question. Your customers, your specific value proposition, and your specific market may simply support a meaningfully different number than what a competitor, operating with their own history and their own possibly unvalidated pricing decision, happens to currently charge.

Bundle and tier decisions deserve the same rigor as the headline number

Founders often spend considerable energy debating a single headline price while treating decisions about tiers, bundles, or what is included at each level almost as an afterthought decided quickly and informally. These structural decisions frequently have as much impact on your actual revenue as the specific number you land on for any one tier, since they determine how customers self select into different levels of spending based on what they actually need.

The same underlying research techniques used to find a defensible price range can also inform how you structure what is included at each tier, by asking your target market directly what specific capabilities they would expect at a cheaper option versus what would justify paying meaningfully more. Treating tier structure as seriously as the headline price itself, rather than deciding it quickly based on what felt intuitive, often reveals a more profitable structure than the first version you would have landed on by instinct alone.

Replace the guess with an actual method

The choice between nine, nineteen, and twenty nine dollars does not have to be a coin flip dressed up in strategic language. It can be an actual, evidence based decision, built from techniques that have been used and refined across decades of real pricing research, requiring nothing more exotic than a willingness to ask your market the right kind of question instead of the obvious but unreliable one.

Our Market Research course walks through both of these pricing techniques in full detail, along with how to combine them with real behavioral data when you have access to it, so your next pricing decision is grounded in something more solid than which number happened to feel least uncomfortable to type into your pricing page this afternoon.