A competitor gets recommended for a feature you already offer. Your first reaction is understandable: “It's right there on our website.”
Before adding another landing page, check what “right there” looks like to someone who doesn't know your product. Can they verify the feature, understand its limits, and see whether it meets their requirement?
Start with the evidence and the buyer's task. That gives you a useful fix even when you can't explain exactly why an AI answer missed it.
Are you talking about the same capability?
Copy the exact question and the relevant part of the answer. List the requirement in plain language. Then ask the product owner whether you support that requirement today.
Similar feature names can hide meaningful differences. “Automated reports” could mean a scheduled email, a live dashboard, or a PDF sent to each client. A buyer asking for one may not be satisfied with another.
Check plan restrictions, release status, integrations, and exceptions. A feature in a private beta shouldn't be described as generally available. If the answer is accurate about a limitation, make that limitation clearer rather than trying to argue it away.
Find the page that proves it
Look at the product page, documentation, release note, and help article. Which is the best current explanation? Is the evidence limited to an announcement from months ago, or can a buyer find a maintained page?
Use this checklist:
- The feature is named in language customers recognize.
- The page explains the job it performs and who can use it.
- Requirements and limits appear beside the claim.
- A current example or setup guide shows how it works.
- Relevant product and help pages link to the explanation.
For a fictional reporting product, a useful sentence might be: “Schedule a PDF report to each client every Monday; scheduled delivery requires the Team plan.” Publish that only if the schedule, format, and plan have been verified. The point is to replace an ambiguous promise with an answer someone can check.
Inspect the sources without guessing the mechanism
Open the linked sources in the AI answer. Are they discussing the current product? Do they use an older feature name? Does your website appear at all?
If a source you own is wrong, correct it. If a partner page is out of date, request a factual correction through its normal process. Don't assume a matching old sentence proves where an uncited answer came from.
Sometimes the answer simply doesn't give enough evidence to diagnose the omission. Record that instead of inventing a reason involving training data, authority, or a hidden ranking rule.
OpenAI's search documentation explains that ChatGPT can use web search and linked sources. It doesn't provide a recipe that guarantees your feature will be included.
Improve the existing explanation first
If a relevant page already exists, update it. Put the answer near the feature description, use a concrete example, and link to the setup details. Avoid creating several pages that make the same claim in slightly different words.
Keep visible copy and metadata consistent. Structured data should match the visible page; it isn't a substitute for explaining the capability.
For a wider look at the work, our AEO introduction provides background. The immediate goal here is narrower: a buyer should be able to verify one feature and decide whether it fits.
Recheck the specific misunderstanding
Save the edit date and the evidence you added. Monitor the same neutral requirement question and a separate branded feature question over time. Record the tool and setup so the comparison remains useful.
Read the answers rather than relying on a mention total. Our AI share-of-voice guide explains why presence, recommendations, and citations need separate treatment.
If the error persists, keep the examples and investigate the sources again. If it disappears, note the observation without claiming the edit proved a causal effect. Either way, you've made the feature easier for a real buyer to understand.
