A buyer arrives at a demo expecting a plan you retired last year. They did not necessarily read the wrong pricing page themselves. They may have asked an AI assistant, received a confident answer and brought that answer into the conversation.
The tempting response is to rewrite the current page again. Sometimes that is necessary. But first, investigate the answer. An old review, a forgotten help article or a comparison post may still carry the previous offer. An answer can also be wrong without giving you a reliable source for the mistake.
The useful task is to build a consistent current pricing record and track which contradictions remain. You cannot correct an engine directly in the same way you can edit a web page.
Capture the answer before changing the page
Save the prompt, date, engine and full response. Record the exact claim that is wrong: the billing unit, starting price, plan name, minimum commitment or included features. “Pricing is inaccurate” is too broad to assign as a task.
Open any citations and check whether they actually support the statement. OpenAI’s guidance on reviewing search results notes that sources and citations can be outdated or incorrect. Treat a citation as a place to investigate, rather than proof that you have found the cause.
Repeat the same question and try a small set of natural variations. A mistake that appears consistently across related questions deserves a different priority from a single unsupported response.
A current pricing page is only one source. Check the outdated pages an answer is still citing.
Build a pricing fact sheet
Before requesting updates, agree the current offer internally. The reference should answer the questions a buyer would ask before doing the arithmetic.
What is the billing unit: user, team, usage or something else?
Which billing period does the displayed price cover?
Are minimum seats, usage limits or commitments involved?
Which features change between plans?
Does a legacy offer still apply to existing customers?
Where can someone verify the current terms?
Separate public acquisition pricing from exceptions such as a negotiated enterprise agreement. The goal is a dependable explanation of the advertised offer, not an attempt to fit every commercial arrangement into a single sentence.
Fix the owned sources first
Start with a readable pricing page. Put the plan names, billing basis, prices and important limits in text. A table is useful when the products can be compared fairly that way; clear explanatory paragraphs matter just as much when the offer has conditions.
Review the help center, onboarding material, integration pages and older launch posts. Do not make the buyer reconcile several current-looking pages that describe different offers. Where historic pricing needs to remain available, label its period and audience clearly and point to the current page.
Decide whether an old page should be updated, retained as an archive or redirected to a useful replacement. That is an editorial decision. Removing a page is not automatically the right answer, especially if existing customers still need its information.
Work through the external correction queue
Prioritize the review sites and directories that actually appear in the wrong answers. Send the publisher the specific outdated claim, the correct replacement and a direct link to the current reference. A concise correction is easier to check than a general request to refresh a company profile.
Keep a status for each source: requested, acknowledged, updated and rechecked. A sent email is not the same as a corrected listing. The queue also makes it clear which changes depend on someone else’s publishing schedule.
Comparison posts need particular care. Correct factual errors without asking the author to change an honest judgment or remove a legitimate criticism. Accurate third-party information is more useful than a polished but unsupported endorsement.
Measure the correction separately from awareness
Track the percentage of observed answers quoting retired pricing. Log accurate answers, wrong answers and answers that avoid the price as distinct outcomes. A lower error rate caused only by fewer price statements is different from a clearer current explanation.
Do not promise a universal correction date. Your own page, external listings and answer generation are different systems, and the order of their updates can vary. Continue checking the same prompt set after a source changes and keep any unresolved examples visible.
The Tallyhaus case study illustrates this workflow: one consistent pricing reference, a source correction queue and repeated checks. The method is more useful than repeatedly publishing the same announcement and hoping every old version disappears.
Maya Okafor
Co-founder, strategy. Nine years in B2B search before Answerline.
