How Do You Check Whether AI Engines Quote Your Prices Correctly?

How do you check whether AI engines quote your prices correctly?

Ask them the questions your buyers ask, record the answers, and compare every number against your own pricing source of truth. Do it in ChatGPT, Perplexity, Gemini, Claude, and Google's AI features, once a month. Then trace each wrong answer to the page it came from and fix that page, not the engine.

Pricing is one of the first things buyers want to know about software, and some now ask an AI assistant before they visit your site. Pricing is also one of the easiest things for an AI answer to get wrong. Old prices linger on blog posts and comparison sites. Annual and monthly figures get mixed up. A discontinued plan keeps showing up in summaries.

A wrong price in an AI answer does real damage. It either scares off a buyer who thinks you are too expensive, or it creates an awkward sales call when the real number is higher than what they were told. A short monthly check catches most of it.

Why do AI engines get prices wrong?

AI engines get prices wrong because they assemble answers from many pages, and those pages disagree. Your current pricing page, an old blog post, a third-party review from last year, and a comparison site may all state different numbers. The engine picks or blends them, and the result can be outdated, mislabeled, or simply mixed up.

Billing period confusion is the most common error. If your pricing page shows an annual per-month figure by default without a clear label, a summary can easily present it as the monthly price. I wrote about how the default toggle shapes that in whether your pricing page should show annual or monthly first.

The second common error is stale content on your own site. Launch announcements, old case studies, and blog posts written when prices were different all keep stating the old numbers. To an AI engine, those are just more pages from your domain that seem authoritative.

Which questions should you ask the engines?

Ask the questions a real buyer would type, not just your brand name. Use variations like "how much does your product cost," "your product pricing per user," "cheapest plan for your product," "your product versus competitor price," and "does your product have a free plan." Each phrasing can pull different sources.

Include at least one question about each plan and one about the free tier or trial, if you have one. Add a comparison question against your closest competitor, because comparison answers often pull from third-party sites with older data.

Write the questions down and reuse the same set every month. Consistency is what turns a one-off curiosity into a tracking system. You want to see whether answers improve after you fix pages, and that only works if the questions stay the same.

Which AI engines should you check?

Check the engines your buyers actually use. For most B2B products that means ChatGPT, Perplexity, Gemini, Claude, and Google's AI Overviews or AI Mode in regular search. Each engine retrieves and weighs sources differently, so a price that is right in one can be wrong in another.

Google's case is worth understanding because it is closest to traditional search. Google's documentation on AI features says that "to be eligible to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to be shown in Google Search with a snippet." So if your current pricing page has indexing problems, older pages may fill the gap.

For the other engines, use their standard consumer apps with web search turned on where that is an option, because that is what buyers see. Note the date and the engine for each answer, and save the cited sources if the engine shows them.

How do you record and score the answers?

Use a simple table with one row per question and engine: the date, the price stated, whether it matches your source of truth, and which sources were cited. Score each answer as correct, partly correct, or wrong. Track the share of correct answers over time as your headline number.

Partly correct is a useful category. It covers answers that get the number right but the billing period wrong, or list the right plans but miss a recent price change. These are often the easiest to fix, because the engine is already close.

I keep this in Airtable, with a view that filters to wrong answers and their cited sources. That view becomes the work list for the month. A spreadsheet works just as well if that is what your team uses.

How do you trace a wrong answer back to its source?

Start with the citations. Engines that show sources, like Perplexity and Google's AI features, often point straight at the page that caused the problem. When no source is shown, search your own site and the major review sites for the wrong number. The page that states it is usually your culprit.

On your own site, look for the wrong figure in blog posts, old announcements, help docs, and comparison pages. Update or remove the outdated number, and link to the live pricing page instead of restating prices in many places.

When the problem is a third-party site, contact them with the correct information. Review platforms and comparison sites often have a way for vendors to update listings. Keep a record of what you asked for and when.

What should your pricing page do to be quoted correctly?

Your pricing page should state every price in plain text, with the billing period right next to the number, the currency clearly marked, and a visible last-updated date. Avoid prices that only appear inside images or scripts. The clearer and more consistent the page, the easier it is to quote accurately.

One page should own your pricing. If prices appear on many pages, each one is a chance for an old number to survive. I explained the general problem in what happens when two of your pages answer the same question, and pricing is the most expensive version of it.

Do not rely on special tricks. Google states that "there are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." Clear, crawlable, consistent pricing does more than any markup trick ever will.

How often should you run this check?

Monthly is a good default, plus a check two to four weeks after any price change. Price changes are when wrong answers spike, because old figures are everywhere and the new page has not been picked up yet. Running the check after a change shows you how long the old price lingers.

The same routine works for competitor pricing, which helps sales prepare for objections. I described a related process in how to audit what AI engines say about a competitor.

Over time, your correct-answer share should rise and stay high. If it drops, something changed: a new third-party page, a leftover blog post, or an indexing problem with your pricing page.

What should you do next?

Write ten pricing questions a buyer would ask, run them in the AI engines your buyers use, and log each answer with its date, price, and sources. Fix the wrong ones by updating or removing outdated pages, making your pricing page the single clear source, and contacting third-party sites with stale numbers.

Repeat the same questions next month and watch the correct-answer share. That one number tells you whether buyers are hearing the right price before they ever reach your site.

If you want help setting up AI visibility tracking for your pricing and fixing the pages behind wrong answers, reach out. Let's chat about your site.