The Pricing-Page Readiness Checklist for AI

You can get a first read on your Worth, the ANSWER category that measures whether AI states your price and value accurately, by checking two things: how readable your pricing is to an engine, and what AI actually says when asked. This checklist covers both. For the full background, see the Worth pillar guide.

Part 1: Is Your Pricing Readable to AI?

Engines can only repeat a price they can read. Work through these readiness checks on your own pricing.

1. Public. Your price, or at least your pricing structure, is visible without a login, a demo request, or a "contact sales" gate.
2. Text, not image. Prices are real text on the page, not baked into a graphic an engine cannot parse.
3. Current. The page reflects today's tiers and numbers, with no stale figures lingering from a past change.
4. Structured. Tiers, what each includes, and what drives cost are laid out clearly, so the right number is easy to extract.
5. Value alongside price. Each price is paired with the concrete outcomes it buys, not just a feature list.
6. Consistent everywhere. The same numbers appear on your site, your listings, and any third-party pages you can influence.

Any "no" is a place an engine is likely to guess or reuse an old figure.

Part 2: What Does AI Actually Say?

Now test the output. Run these prompts, replacing the brackets with your details.

1. "How much does [brand] cost?"
2. "Is [brand] worth the price for [customer type]?"
3. "What's the typical ROI on [brand]?"
4. "Is [brand] expensive?"
5. "How does [brand] pricing compare to [competitor]?"

The 3 Rules

1. Log out. Run every prompt in a logged-out or private session, so the engine is not drawing on your history.
2. One fresh chat per prompt. Start a new conversation each time, so one answer does not color the next.
3. Use your real market. Run the prompts in the geography you actually sell into, because answers and currencies vary by location.

Run each on at least 2 engines, for example ChatGPT and Perplexity, plus Google's AI answers if you can.

How to Read the Results

For each answer, note whether the price is accurate, the framing is fair, and a value story is present. Accurate numbers with a credible value story mean strong Worth. A wrong or outdated number points to a readability gap from Part 1. An "expensive" framing with no value context means you need a clearer value story or have a hostile source to correct. The patterns and fixes are explained in Priced Wrong at the Worst Moment.

What This Check Cannot Tell You

A pricing spot check is a useful hint, not a baseline. It covers a few prompts, on one occasion, scored by eye, and answers vary from ask to ask. A real measurement runs many price and value questions, repeats them, covers more engines, and scores every answer the same way so the result is stable and trackable, especially across pricing changes. Doing that by hand after every change is a real undertaking, which is the honest reason most teams have it run for them.

If your check turns up wrong numbers or unfair framing, the next step is a proper baseline and a fix plan. A HiBot audit measures your Worth across engines and ranks what to fix first. The tactics are in How to Improve Your Worth Score. Download the ANSWER whitepaper to see the method, or request an AI visibility audit at hibot.com.