Why ChatGPT Never Mentions Your Company

Service and Area Pages, Done Honestly The standard local play is a page per service and a page per town, and it fails when those pages are templated with a place name swapped in. Thin, near duplicate pages are treated as low quality and rarely provide anything worth quoting.

This matters because the prompt set is built from it, and a prompt set written from segment language measures your positioning rather than your market. If your brief says mid market operations leaders, the prompts will use that phrase and geo seo agency no buyer ever will.

If you will not name competitors, say that too, and understand it removes the highest performing content format from the plan. Better to have that argument in the brief than to have a comparison page written and then killed.

Keep a small number of deliberately hostile prompts in the set permanently. Questions asking whether you are expensive, slow or suitable only for large clients reveal what the system believes about your reputation, and the belief is often traceable to one specific source. Nobody enjoys reading those answers, and they generate more actionable work than the flattering prompts do.

Every inconsistency reduces confidence that scattered mentions describe one business. For a local business this is usually the single highest return work available, and it is tedious rather than difficult.

This frequently produces the first result of the engagement, because access failures are total and fixing them can change answers within days. It should also be short. A fifty page technical audit at this stage is usually padding drawn from a generic template.

A weak brief produces a generic proposal, and a generic proposal produces a generic engagement that spends the first two months discovering things you already knew. The brief is the cheapest lever you have over the quality of the work.

One local specific worth checking is how your opening hours and availability are stated across every listing. These are among the details most frequently quoted in local recommendations and among the most likely to be wrong, because they change seasonally and get updated in one place. An assistant confidently telling somebody you are closed is a lost job that leaves no trace in any report.

Second, prompts that presuppose a weakness: is this company expensive, are they slow, are they suitable for small clients. The answers reveal what the system believes about your reputation, and where the belief is wrong it points at a specific source you can correct.

A reasonable formulation: after two quarters, we expect movement in mention rate on buying intent prompts, improvement in the accuracy of how we are described, and new citations from the sources our baseline showed matter. If none of those move, we will treat the approach as unsuccessful.

How to Run the Ninety Day Review Ask three questions. Can you show me the prompt set is unchanged. Can you show me the raw answers. What specifically did you do, and which of the changes do you believe caused which movement.

One organisational habit makes this sustainable. Give the sales and support teams a single place to drop questions as they hear them, with no process attached beyond writing down the question in the customer's words. Anything more elaborate stops being used within a month, and a shared document with fifty verbatim questions in it is worth more than a formal intake process nobody completes.

A prompt set built from internal vocabulary measures how visible you are to people who already talk like you, which is a group that mostly consists of your own staff. It reliably produces flattering results and no useful information.

Where you serve several towns, resist the instinct to claim the widest possible area. A stated coverage radius that you genuinely honour is more useful than a list of thirty places you would only travel to reluctantly, because the specific claim gets quoted and the vague one does not. Being the obvious answer within a tight radius produces more work than being one of many possibilities across a county.

You asked it to recommend a supplier in your category. It named four companies, two of which you consider inferior to yours, and one you had never heard of. Your name did not come up, and it did not come up on the follow up question either.

The most citable content most businesses could publish already exists, unwritten, in sales calls and support tickets. It is the set of questions people actually ask, with the answers your team gives verbally every week and has never put on a page.

One test of whether a prompt set is any good is to run it and see whether the answers surprise you. A set that returns exactly what you expected is usually measuring your own assumptions, because the questions were written from them. Surprises indicate the prompts reached beyond the company's internal picture of its market, which is the entire purpose.

One diagnostic shortcut is worth knowing. Ask the assistant to describe your company rather than to recommend one. If it produces an accurate description but will not recommend you, the record exists and the corroboration is thin, which points at third party sources. If it produces a vague or wrong description, the record itself is broken, which points at access and identity. Those two findings lead to completely different quarters of work, and the question that separates them takes ten seconds to ask.