What GEO costs in 2026

Nobody in this category publishes prices, which is why you are reading this. We publish ours, so it costs us nothing to publish the ranges around them.

The observed market, mid-2026

Services pricing in AI visibility and generative engine optimisation runs from roughly $1,500 to $50,000 a month. That range is close to useless as stated, because the two ends are not the same product.

The credible mid-market band is $3,000 to $10,000 a month. Below that you are almost always buying content production with AI visibility language layered on top. Above it you are buying either enterprise scale, multi-market coverage, or a named practitioner’s time.

One-off audits sit at $2,500 to $7,500 depending on query volume and engine coverage. Fixed-scope build projects run $10,000 to $25,000.

Treat these as observed ranges rather than as a survey. Pricing in this category is soft, moves quickly, and is negotiated more often than it is published.

What sits inside each band

Under $3,000 a month

Usually: a prompt-tracking tool subscription, a monthly report generated from it, and two to four blog posts. Practitioners now write publicly that sub-$3,000 work in this category is SEO relabelled, and that is a fair description of what usually sits here.

Our own first retainer tier sits in this band, at $2,500 a month, so the test we would apply to it is what the fee buys rather than where it sits. Look for measurement across several engines with a stated run count, a source map, and entity and data publishing work. A tool subscription plus blog posts is content work at any price.

This is not automatically a bad purchase. If you have no measurement at all and no in-house capacity, a cheap monitoring subscription plus someone competent writing is better than nothing. Just know that you are buying content, and price it against content agencies rather than against specialists.

$3,000 to $10,000 a month

The band where the work changes shape. You should expect measurement across multiple engines with a stated run count, a source map rather than a mention count, technical remediation, and source presence work: profiles claimed and corrected, data contributed to industry reports, placements pursued where the source map says the models actually look.

The thing that distinguishes this band is that someone is doing outbound work on your behalf into third-party sources. That is slow, unglamorous, and it is where most of the movement comes from.

Above $10,000 a month

Multi-market or multi-language coverage, large query sets, a category where the competitive set is genuinely contested, or an engagement including engineering work on your own data infrastructure. Also where you find agencies charging enterprise rates for mid-market work, so ask what specifically justifies the step up.

What this costs for a proptech company specifically

What proptech work costs is set by one thing, and it is not a vertical premium.

Half the work is publishing data out of a production database. Lease comps, rent benchmarks, cap rate series, development cost benchmarks, absorption, transaction histories. Getting an aggregated, anonymised, dated slice of any of those onto a public URL with a method note attached is engineering, not writing, and engineering does not compress the way content does.

The asset is almost always already owned and unpublished. CompStak runs a give-to-get exchange where members earn credits by submitting lease and sale comps and spend them to view other people’s, so the comps sit behind an account rather than on a page. Northspyre tells development teams they can standardise deal, cost and vendor data across a portfolio to set benchmarks and build a proprietary database. Archer, Rockport VAL and ARGUS Enterprise are all sold as underwriting or valuation software, which puts the modelling inputs inside the model.

So the cost is the pipeline, not the research. Nobody has to go and find the data. Somebody has to decide what can be published without giving away the product, aggregate it, date it, and put it somewhere a crawler can reach.

A content agency quoting a monthly retainer is quoting for the other half of the work: the writing, without the pipeline. Set its fee against the writing inside a build rather than against the whole engagement, because the pipeline is the part it does not cover.

What the money buys in this vertical, and what it cannot buy, is set out in GEO for proptech.

Why the cheap end is cheap

The measurement is not expensive. This is the part the category does not advertise.

Running fifty queries across five engines at three runs each is roughly 750 to 1,000 API calls. At current grounded-search pricing that is tens of dollars, not thousands. A full index measuring forty companies across a category runs in the same order of magnitude.

So when a tool charges $500 a month for tracking, it is not the API bill you are covering. When an agency charges $10,000 a month, the measurement is a rounding error inside it. The cost is analysis, remediation, and the slow work of getting into sources you do not control.

Anyone pricing on the basis that the measurement is expensive either has not built it or is hoping you have not checked.

What you should refuse to pay for

Pipeline guarantees from AI answers. Attribution from generated answers is unreliable in 2026. A vendor promising attributed revenue is modelling and calling it measurement.

Ranking guarantees. The engines change retrieval behaviour without notice and without a changelog. Nobody can guarantee a position they do not control.

A dashboard as the deliverable. A login with charts in it is the cheapest part of this to build. If the monthly fee is mostly access to an interface, buy the tool directly and keep the difference.

Volume content. Twelve posts a month is a content retainer. It may be worth buying, but it is not what moves recommendation share, and the source map will tell you that within one measurement cycle.

Our published prices

For reference, since price anchoring should happen before a call rather than during one.

Engagement	Price	Term	First 90 days
Diagnosis	$1,200	One-time, 2 weeks	Counted in both totals
Retainer	$2,500 a month	3-month minimum	$8,700
Retainer with earned mentions	$4,000 a month	3-month minimum	$13,200

Both 90-day totals include the diagnosis. The build is done inside the first 3 months of either retainer rather than sold separately. Measurement depth is the same on both tiers: the higher one adds earned-mention work, not more queries.

We hold to one rule on price: cut scope rather than rate. A discounted rate for the same scope tells the next client the first number was invented.

How to buy without wasting the first quarter

Start with a fixed-scope audit, from anyone, including someone other than us. It gives you a baseline, and without a baseline no retainer can prove it did anything.

Insist the audit hands over the raw measurement data, not only the report. One row per run, per query, per engine, per brand, with the cited URL and timestamp. If a vendor will not hand that over, they are keeping you dependent on their interpretation of it.

Then contract the ongoing work on a named query set with a re-measurement date, measured identically both times. That single sentence in a contract does more for your outcome than any amount of diligence on the vendor’s methodology page.

Questions

What is a reasonable budget to start with?

A one-off, fixed-scope measurement of where you stand is the cheapest way to find out whether you have a problem worth spending on. Committing to a retainer before you have a baseline means paying monthly for work you cannot evaluate.

Why is monthly work more expensive than a one-off audit?

Because the expensive part is not the measurement, it is source presence. Getting listed, corrected, and cited in the places models already trust takes weeks per placement and does not compress. Measurement is the cheap part and always was.

Is GEO just SEO with a new name?

Partly, and anyone claiming otherwise is selling. Technical crawlability, structured data, and topical authority all still matter and are all borrowed directly from search. What is genuinely new is source presence work, meaning presence in the specific third-party sources a model retrieves for your category, which classic SEO never had to care about directly.