An Honest Look At AI SEO Agency Pricing Models

Why That Breaks the Old Playbook The old playbook assumed that if you occupied a high position, you got the visit. That link between position and visibility has weakened. Ahrefs looked at 15,000 long-tail prompts across four assistants in July 2025 and found roughly 80 percent of the cited pages did not rank for the original query at all.

Log the conditions with every run, including which assistant, which mode, whether web access was enabled and the date. When a result moves sharply, the conditions log is usually what tells you whether the world changed or your setup did.

What a Local Business Should Do This Month Run five prompts asking for a business like yours in your town, from a signed out session, and record who gets named and what gets cited. Then fix every listing on the sources that appeared, starting with the phone number and address.

This section sounds procedural and it is the foundation of everything after it. A prompt set quietly edited between runs makes every trend line in the document meaningless, and it is the easiest way to manufacture improvement without doing anything.

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.

A Single Topic Site Has No Redundancy A site covering one subject has no second chance. If the handful of pages describing that subject are not readable, there is nothing else for a system to fall back on.

What to Spend Where If the budget is small, buy the audit and do the listings work yourself. Correcting your presence on the sources that already get cited is the highest return activity available and it requires attention rather than expertise.

Pricing in this field is unusually opaque, partly because the work is new and partly because the absence of an independent scoreboard makes it hard for a buyer to tell whether they are getting value. That combination invites vague scoping.

You are unlikely to read all of it, and its presence changes the incentives entirely. An agency that knows the raw evidence ships with the report writes a different summary than one that knows it will not be checked.

How You Will Know It Is Working Ask for the raw answers, not a score. A credible report shows you the exact prompts, the exact text an assistant returned, and which pages were cited. You should be able to read it and form your own judgement without trusting anyone's index.

And in a fast moving category where competitors are actively publishing, monthly can miss a shift. Even then, keep the full set monthly and run a small subset more frequently rather than expanding everything.

The Prompt Set, Unchanged The report opens with the prompt set used, versioned and dated, and a statement that it is identical to last month's. If it changed, the change is listed explicitly with a reason, and the previous series is kept alongside so comparisons remain honest.

Work Completed, in Countable Units Listings claimed, with names. Errors corrected, with the source and what was wrong. Pages published or rewritten, with URLs. Technical changes made, with dates. Outreach attempted and its outcome, including refusals.

One scheduling detail improves comparability more than it should. Run on roughly the same date each month rather than whenever somebody remembers. Retrieval behaviour and the freshness of competing sources both vary over a month, and a series taken at irregular intervals introduces variation that looks like a trend.

The specific damage is that somebody sees a dip, rewrites a page, sees the number recover for unrelated reasons, and concludes the rewrite worked. That false lesson then gets applied elsewhere. A slower cadence with more runs per prompt is more informative than a faster one with fewer.

When to Test More Often Three situations justify a tighter loop. During an active campaign where you need to attribute a specific change, weekly runs on a subset of prompts are reasonable, provided you accept the variance.

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.

Build the run into an existing routine rather than creating a new one. Measurement programmes in this field fail through quiet abandonment rather than through a decision, and a modest set attached to an established monthly process survives far longer than an ambitious one that depends on somebody remembering to start it.

And pick a narrow enough definition of what you do that the existing coverage is thin. Competing to be the best documented answer to a specific question is a solvable problem. Competing for a broad category against everyone is not, and the small operators who do well here are almost always the ones who narrowed first. structured data for ai search