Insight
Compare GEO pricing through scope, evidence, ownership, and handback, not a vendor rate card or a promise of mentions, citations, traffic, or revenue.
The right way to compare generative engine optimization pricing is to price an inspectable scope, not a promised citation or blended visibility score. Ask what questions will be tested, which pages will be reviewed or changed, how answers will be captured, who owns each action, and what records your firm keeps at handback.
A useful proposal separates three things:
GEO is commonly described as work to improve visibility in generated answers. Foundation’s GEO explainer provides that public framing. For a buyer, however, the useful question is not whether a proposal uses the label “GEO.” It is whether the scope leaves an evidence trail your team can inspect.
The market includes different delivery scopes and pricing structures. Verified 10 October 2026. Digital Elevator’s AEO and GEO pricing guide is one current competitive example. That variety is a reason to compare scope, not to treat any published vendor amount as a universal benchmark.
Put every proposal into the same scope table before comparing it. A lower fee can simply mean fewer prompts, fewer surfaces, no implementation, or no usable handback. A higher fee can hide the same gaps behind a broad “visibility” label.
| Scope area | What the proposal should define | What the buyer should receive |
|---|---|---|
| Baseline and capture design | Exact buyer prompts, tested surfaces, run conditions, capture date, and classification rules | A versioned prompt set and a complete baseline capture |
| Technical eligibility | Indexing and snippet eligibility checks, relevant crawler controls, and recorded limitations | A findings log that separates access issues from content issues |
| Entity and source clarity | The firm, services, experts, claims, and public pages included in the review | A source inventory that ties each visible claim to a page and owner |
| Content fixes | Named pages, proposed edits, supporting sources, approvals, and exclusions | A page-change record showing what changed and why |
| Measurement and handback | Later run conditions, comparison method, raw evidence, and unresolved questions | Comparable observations plus the underlying files and URLs |
| Governance and ownership | Decision rights, approvers, delivery owners, storage location, and access after the engagement | An owner for every action and an explicit transfer of working records |
Scope should also state what is excluded. Examples include new page production, technical implementation, third-party publishing, tool subscriptions, or repeated capture runs. Exclusions are not defects when they are visible. They become a pricing problem when the buyer discovers them after approval.
If you need the underlying capture method, use the AI visibility audit guide. If you need a fuller deliverables specification for a provider, use the GEO consulting guide. Together, they give you a common vocabulary for comparing proposals without pretending that identical labels describe identical work.
Choose the engagement shape from the decision your firm needs to make. Do not start with a preferred billing model and work backward.
| Engagement | Best fit | Minimum defined scope | Handback test |
|---|---|---|---|
| Audit | You need a baseline, priorities, and an implementation decision | Prompt set, run conditions, raw answers, citations, source inventory, technical checks, and prioritized gaps | Can another team inspect the evidence and price the next step? |
| Defined implementation project | You already know which approved gaps or pages must change | Named pages, approved claims, edits, owners, acceptance criteria, and before-and-after change records | Can the buyer see exactly what was changed without inferring a promised outcome? |
| Ongoing operating cadence | Your team will repeat captures, approve changes, and maintain the record | Stable method, declared review dates, change control, recurring backlog, owners, and later observations | Can each reporting period be traced to raw evidence and compared under compatible conditions? |
An audit is not a smaller retainer. It is a bounded decision product. It should tell the firm what was observed, where the public-source gaps are, and which actions deserve approval.
A defined project buys implementation against an accepted backlog. Its end condition should be changed pages and transferred records, not “better visibility.” An ongoing cadence buys repeated observation and operations. It makes sense only when the proposal names what repeats, who reviews it, and how method changes are disclosed.
Tools may support any of these models, but a software subscription is not a substitute for a scoped engagement. The LLM SEO tools guide can help you distinguish capture and workflow capabilities from the consulting work required to define prompts, validate claims, approve edits, and assign ownership.
Require the underlying records, not only a dashboard or summary score. At minimum, the buyer should receive:
These records protect the buyer from two common ambiguities. First, a percentage can conceal the questions and conditions behind it. Second, a later citation can be presented as proof that a particular edit caused the change. The records show what appeared and what changed; they do not reveal an engine’s internal reasoning.
Ask where the files will live, which formats can be exported, and whether your team retains access after the contract ends. Ownership is part of scope. A handback that cannot be reviewed outside the vendor’s account is not equivalent to a transferable evidence set.
Technical work should be priced against named checks and fixes. “AI readiness” is too broad to compare on its own.
For Google’s AI features, existing SEO fundamentals still apply. A page must be indexed and eligible to appear in Google Search with a snippet to qualify as a supporting link. Google also says no special AI file or special schema is required, and meeting technical requirements does not guarantee crawling, indexing, serving, or inclusion. Google Search Central: AI features and your website
For OpenAI, the proposal should distinguish search inclusion from potential model training. OAI-SearchBot concerns search, while GPTBot concerns content that may be used to train foundation models; the controls are independent. Eligibility still is not a promise that a page will appear. OpenAI crawler documentation
A technical line item should therefore say whether the provider will only diagnose, also implement, or verify implementation later. It should name the pages or controls in scope and identify who can authorize changes. Do not pay a premium merely because a proposal adds an “AI” prefix to standard search checks. Pay for a defined review, an actionable finding, and, when included, a recorded fix.
Use contract language that describes work the provider controls. A provider can control whether it delivers a prompt set, captures an answer, checks a claim, edits an approved page, or assigns an owner. It cannot control whether an engine ranks, mentions, cites, or sends traffic to that page.
Rewrite vague proposal language before comparing it:
The same boundary applies to reporting. A deliverable can document that a mention or citation appeared under recorded conditions. It cannot promise that the observation will repeat. A page-change record can prove an edit happened. It cannot, by itself, prove why a later answer changed.
This distinction does not make the engagement less ambitious. It makes the purchase inspectable. Your firm can judge delivery, preserve uncertainty, and decide what to run next without converting an observation into a guarantee.
Use the same questions with every provider:
Reject a proposal that cannot expose its scope without relying on a proprietary score. Ask for a revision when the fee is clear but the number of prompts, pages, captures, edits, owners, or review cycles is not. A vendor price is evidence of what that vendor charges under its own terms; it is not proof of likely outcomes or fair value for a different scope.
Get the operations audit to define the prompt set, source baseline, evidence record, ownership, and handback before you compare implementation proposals.
Written by Loïc Guyon (Tileo), an international operator who builds AI-native ventures in public.
Compare the exact prompts, surfaces, pages, technical checks, content changes, capture runs, owners, and handback records included. Do not compare fees until each proposal exposes the same scope boundaries and exclusions.
No. An audit is a bounded baseline and decision product. An ongoing engagement repeats a declared capture, review, change, and handback cadence under recorded conditions.
No. A provider can guarantee controlled deliverables such as captures, reviews, approved page changes, and records. It cannot control or promise rankings, mentions, citations, traffic, or revenue.
The handback should include exact prompts, run conditions, raw answers, visible citations, claim checks, page changes, owners, and later observations. The buyer should be able to inspect and export those records.
No. Google says no special AI file or special schema is required for its AI features. Existing search fundamentals apply, and technical eligibility does not guarantee crawling, indexing, serving, or inclusion. Google Search Central
