AI product concept testing

Screen a product idea before you build it or buy stock

A product concept test answers an early question: is this idea, at this price, worth more time and money? SellTo.us shows your product to a crowd of AI-simulated shoppers built for the audience you choose, and reports who leans toward buying, who doesn’t, and the reasons they give. It is a fast first filter, not a replacement for real customers.

Test Your Idea for Free1,000 AI-simulated participants · no card needed · free if eligible

When a quick concept test helps

How a test works

1. Describe the product. Paste the text a customer would see, add the price and up to 5 photos. Choose the country, city and the kinds of shoppers you’re aiming at.
2. The crowd is built. An AI model splits your audience into shopper groups (8, 25 or 100 depending on test size), each with its own ages, jobs, budget level and habits, then creates individual shoppers from those groups.
3. Each shopper answers. Would buy, maybe or wouldn’t buy, plus a short reason, for every version you entered.
4. The report is counted and checked. Percentages are counted by code from the answers, and the written parts are checked against those numbers before you see them. See the methodology for the details.

What you get

Every report includes the share of simulated shoppers who would buy each version, results by shopper group, the main reasons to buy and not to buy, labeled shopper quotes, ideas to test next and a list of the claims in your description that need evidence. Larger tests add a photo vote, an ad targeting guide and, at 100,000 shoppers, results by city. Monthly plans give 10 tests a month from $49.

Reading the result well

• Look at the groups, not just the total. An idea that most shoppers pass on can still be strong with one group you can reach cheaply.
• Read the reasons. “Too expensive”, “I don’t trust the claim” and “I already have one” call for very different fixes.
• Change one thing at a time. If two versions differ in price and wording at once, the report says so and suggests a follow-up test that isolates each change.
• Treat small gaps as small. A few points between versions in one simulated run isn’t a reason to commit budget.

What it can’t tell you

• It isn’t a demand forecast. A high share of “would buy” answers from simulated shoppers says the idea is worth checking with real people, not how many units you’ll sell.
• No accuracy is claimed. Results haven’t been measured against real sales, and each test is run once, so how much the numbers would move on another run isn’t measured. More on the limits.
• Your claims aren’t checked. If the description says “lab-tested” or “lasts 30 days”, the report lists it as your claim to verify; it doesn’t confirm it.
• Things a shopper can’t see aren’t tested: build quality, delivery, support and how the product holds up over time.

Then check it with real people

Every report ends with concrete next steps, such as a small paid ad test to the most interested group, a pre-order or waitlist page, and short interviews with 5–10 people who match that group. These tell you what real customers do; the simulated test helps you decide what to put in front of them first.

Example: in our sample report for a made-up self-cleaning bottle, the version that scored highest was also cheaper and worded differently, so the report recommends testing the price and the wording separately before deciding.

Related: Startup idea validation · App idea testing · Service idea testing · AI focus groups · Ad concept testing · Full methodology