seomodoPicture this: a potential customer asks an AI assistant to recommend someone who does exactly what your business does. It lists three companies. One is your competitor. Yours is missing. It's tempting to declare an AI visibility emergency. I would ask a few questions first.
Start with the question, not the insult.
A recommendation is only meaningful in the context of the buyer's question. Did they ask for the cheapest provider, the most experienced, someone local, or a specialist serving a particular industry? Those are different buying decisions.
If an assistant recommends a company for emergency plumbing in Seattle, that observation says very little about who it would recommend for commercial plumbing maintenance. A generic brand-name test won't show the difference.
- Record the exact buyer question and the market it describes.
- Capture which businesses are named, which are recommended, and which websites are cited.
- Check the date, provider and search mode. Repeat selected questions to see what changes.
A competitor's appearance is a clue. It isn't an explanation.
The assistant may cite a service page, directory, editorial article, or review site. The recommendation and its citation are evidence of what appeared in that answer, not proof of what caused the model to choose the business.
I'd inspect the cited sources and compare the businesses' public claims. Does the competitor make the service easier to understand? Is its geographic coverage clear? Does it publish proof of relevant work? Are third-party sources describing the offer more clearly than its own website?
Sometimes the answer is better content. Sometimes it's a missing service page, inconsistent descriptions across sources, or a technical issue that keeps crawlers from reading the page. Occasionally, the observed result is simply not consistent enough to justify a major decision.
Measure the gap before you commission a rewrite.
One answer is a screenshot. A repeatable set of buyer questions is a diagnostic. You need a fixed baseline to compare observations over time, plus deeper prompts for industry and service specifics.
That's the distinction behind Seomodo. Its full audit records 188 answers across search-enabled APIs from four providers, while a fixed 12-question baseline per provider is used for its visibility score. The additional answers help examine context and repeat behavior. These APIs can behave differently from the consumer apps.
Then decide what deserves money.
I'd prioritize changes that improve a real buying decision: clear service pages, credible proof, accurate business details, and pages that answer the questions buyers ask before hiring. I'd give the lowest priority to edits justified only by a mysterious score.
Your goal isn't to win a single chatbot response. It's to make the business a credible answer to the right customer's question, and to have enough evidence to know what changed.
A missing mention is a signal to investigate, not a blank check for optimization.