Local Businesses And The AI Recommendation Problem

This is a plan rather than an explanation. It assumes you have already accepted that some of your buyers are asking an assistant for recommendations before they contact anybody, and that you would prefer to be named.

Compare What Each of You Wrote Where a competitor's own page is cited, open it next to your equivalent and read both as a machine would. Count the sentences on each that could be lifted, attributed and remain true and useful out of context.

If the budget is substantial, add the earned coverage work, which is the slowest and most expensive component and the one you genuinely cannot do quickly on your own. Buying that first, before the cheap fixes are done, is the most common way money gets wasted in this field. ai seo company

One overlooked cost is your own time. Every engagement in this field needs somebody inside the business to confirm figures, approve crawler changes and answer factual questions, and a plan that assumes this is free will stall. Budget a few hours a month explicitly and name the person, because the alternative is an agency waiting on answers and billing for a month in which little shipped.

The Details That Get Quoted Locally Local recommendations turn on practical specifics, and most local sites omit all of them. Your actual coverage radius. Whether you handle emergency call outs and at what hours. Typical price range for a common job. Whether you are licensed, insured and to what level.

Two implications follow regardless of which system you are studying. Being findable by the underlying search step is necessary, and being worth quoting once fetched is what decides whether you are used. Almost everything actionable sits in those two requirements.

A retainer describing ongoing optimisation and strategic guidance with no countable deliverable is a subscription to a relationship. It may still be worth having, and you should know that is what you bought.

Gemini and Google Surfaces Closest to conventional search infrastructure, which has a practical consequence: work that improves your standing in Google search tends to carry over here more than it does elsewhere.

Then re-run the same ten prompts a month later and compare. Attributing improvement to a specific fix is only possible because you recorded the starting point, which is the argument for doing the teardown before the work rather than after it.

Test it rather than assuming. Load your key pages with JavaScript disabled and see what survives. If the product specifications, pricing, service areas and contact details vanish, that is what a machine reads.

It also appears more conservative in commercial categories, hedging or declining to make a direct recommendation more often than the others. Where it does recommend, established entity signals seem to matter, which favours brands with consistent details and long records over newer entrants.

The condition is that the output has to be yours to keep and act on elsewhere, including the prompt set. An audit that only makes sense inside that agency's retainer is a sales document with a price attached.

Write these plainly and prominently. A page that says we serve the wider area and offer competitive pricing contains nothing a model can use. A page that says we cover a fifteen mile radius, charge a fixed call out fee, and can usually attend within four hours can be quoted directly into an answer.

Making Any Model Safe Four clauses do most of the protective work regardless of structure. The prompt set and baseline archive belong to you and leave with you. Raw answers ship with every report. Scope is stated in countable units. And there is a defined review point with agreed criteria before the contract auto renews.

How to Judge It at Day Ninety Re-run the original fifty prompts, the same number of times, under the same conditions. Compare against the baseline on three measures: how often you are named, whether the description of you is accurate, and which sources are being cited.

Why Local Is More Exposed The classic local query is a recommendation request with a geographic constraint, and that maps directly onto what a generated answer does well. Somebody asking who to call for a specific job in a specific town receives two or three names rather than a map and a list to work through.

The risk is scope drift into activity that is easy to report and hard to value. The protection is to have the retainer specify countable units: prompt set runs per month, listings audited, corrections submitted, pages published or rewritten, outreach attempts made.

A false trade off gets invented early in most of these projects. Somebody proposes stripping the design, flattening the copy and restructuring everything around what a crawler finds convenient, and somebody else correctly points out that this would make the site worse for customers.

Days One to Fourteen: Find Out Where You Stand Somebody writes fifty questions your buyers would ask, in their words. They run each one three times across the two or three assistants your customers use, from a signed out session, and record the full answers and every source cited.