What actually drives the price of a discoverability audit

Ask what a discoverability audit costs and the assumption underneath the question is almost always the same: that the price tracks the size of the business. A bigger company, a bigger number. It's a reasonable guess. It's also wrong. The audit doesn't price your turnover. It prices the distance between where your buyers look for a supplier and where your business can actually be found — and that distance has very little to do with how many people you employ.

Two firms of identical size can be quoted figures that differ by a factor of four. The gap is never the size of the firm. It's the size of the job. So before you compare quotes, it helps to know what the work is actually made of, because each part of it is a separate lever on the price.

What you're paying someone to find

A discoverability audit answers one commercial question: if a qualified buyer started researching your category today, how likely are they to discover, trust and shortlist you before they discover a competitor? Everything in the price is a function of how thoroughly you want that question answered — across how many of the places buyers now look, and how far into the cause of the gap you want to go. The cheap version checks one surface and stops. The honest version checks the places buyers have actually moved to.

The first lever: how wide you look

A buyer forming a shortlist today might never reach a results page. Between 58 and 70 percent of Google searches now end without a click (SparkToro/Datos and Similarweb, 2024–2025), rising to 80 to 83 percent when Google's AI Overviews appear — and those overviews now show on 13 to 25 percent of searches (Semrush, 2025). So a real audit doesn't just check where you rank. It checks what ChatGPT, Gemini, Perplexity and Google's AI answer actually return for the queries your buyers type, and which competitors get named instead of you. More surfaces, more queries, more named competitors benchmarked against you — each one adds hours, and hours are what the invoice is really counting.

The second lever: how tangled your data already is

Most of the real work isn't measuring. It's untangling. Answer engines assemble a picture of your business from many sources — your site, your Google Business Profile, directories, your schema markup, third-party mentions — and they trust that picture in proportion to how well those sources agree. When your name, address, category and description match everywhere, there is little to correct. When they disagree in nine places — an old company name here, a former address there, a category that contradicts your own homepage — the audit has to find every contradiction before anyone can fix it. A firm that has rebranded, moved, or changed its offer in the last few years almost always carries more of this debt than it expects. This is the single largest variable in the price, and the one nobody asks about up front.

The third lever: a finding, or a finding you can act on

A number on a page is cheap to produce. A number you can act on is not. The lowest tier of an honest audit is a manual review of the trust factors, a single score on a published scale, and the finding: here is where you stand, and why. The next tier adds a prioritised roadmap — what to fix first, in what order, for the most movement. The top tier adds done-with-you implementation. The diagnosis underneath is the same; what changes is how far someone walks the road with you. In my own pricing that runs €1,500 for the diagnosis, €3,000 with a 90-day roadmap, and €6,500 with done-with-you implementation — a fixed fee at every level, no retainer. The version that bills monthly for "ongoing audit" is the most expensive of all, precisely because it never defines when the job is finished.

The lever that should move the price — and rarely does

There is one factor that ought to change the number more than any other, and most quotes ignore it: how deep you go. A shallow audit tells you that you're invisible. A deep one tells you why — and the why often sits at a different layer than people expect. Sometimes a business isn't absent from AI answers because its data is messy or its citations are thin. It's absent because the engines can't tell what it is: the positioning is unclear, the category is confused, the offer reads like four other firms' offers. No amount of schema markup fixes that. I've made the longer version of this argument in where the money is better spent — authority and citations versus traditional SEO. A good audit is honest about which layer your problem actually lives on, because paying to fix the wrong layer is the most expensive mistake on this list.

So what should you actually pay?

Pay for the narrowest honest version first: the diagnosis. It's the cheapest tier, and the only one that tells you whether the rest is worth buying at all. Everything after it — the roadmap, the implementation, the months of your own team's time — should be a decision you make with the finding in front of you, not a sum you commit to in the hope a finding will justify it.

And before you pay for any of it, ask the question one layer up: is your problem a discoverability problem at all, or a commercial decision that was never properly made? That one costs nothing to start, and it's the question I'd rather you answered first.