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What GEO means for an agency, and why Google calls it SEO
Generative engine optimization describes work intended to improve a website’s or brand’s visibility in AI-generated answers. The 2024 paper that formalized the term, by Aggarwal et al., presents it as a framework for content creators to optimize visibility in generative engine responses. Google uses different vocabulary for the same territory. Its AI optimization guide on Google Search Central, last updated 10 July 2026 (UTC), notes that AEO and GEO are terms used for this work, then takes a clear position:
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“From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.” (Google Search Central, AI optimization guide)
The Tool Desk
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Two limits follow. Google’s guidance describes Google’s products only, so it should not be presented as the rulebook for other assistants. And none of the work below guarantees that a page will be cited.
Five service lines agencies can sell
Technical discovery and eligibility
Start with the prerequisites Google’s guide treats as foundational: indexability, crawl access, page experience, duplicate content, and whether pages meet Google’s Search technical requirements. Google says a page must be indexed and eligible for a snippet to appear in its generative AI features. Deliverables you can stand behind:
- A crawl and indexing audit covering crawl-blocking rules, canonical signals, and duplicate URL patterns, with each finding logged and its fix verified after release.
- Snippet-eligibility checks on priority URLs, recorded as pass or fail against Google’s Search technical requirements.
- A remediation list with owners, dates, and a re-check date for each fix.
Meeting these requirements is necessary but not sufficient. Google is explicit that satisfying them does not guarantee a page will be crawled, indexed, or served.
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Editorial improvement
Google’s guide says unique, useful content is likely to influence long-run presence more than other suggestions in the guide. The billable deliverable is content that answers real audience questions and adds something beyond commodity summaries: original data the client holds, named subject-matter experts, worked examples, and first-hand detail about the client’s products or services. Ask for an editorial brief per target topic, a named author with verifiable expertise, and an update log that records what changed on each page and when.
Measurement and reporting
This is where most recurring reporting sits. Baseline and periodically sample a declared set of prompts, platforms, and competitors. Record mentions, citations, citation prominence, accuracy, and referral outcomes, and label each result with its date and method. The method is set out below.
Client education
Clients often equate a model mention with a sale. Your job is to separate visibility indicators from business outcomes. Track qualified visits, leads, or sales wherever attribution is available. Do not equate a mention with a conversion, and do not claim causation without evidence. A short glossary in the first report, defining mention, citation, and referral, prevents most later disputes about what a number means.
Authority and external validation
Relevant independent coverage can sit inside a digital PR workstream. Sell it as earned media that serves the client’s audience, not as a lever for AI citations. Google’s guide explicitly cautions against seeking inauthentic mentions, and no source establishes that mentions reliably produce citations.
What you can and cannot promise
| Claim | Status | Basis |
|---|---|---|
| “We will find and fix crawl and indexing blockers on priority pages.” | Defensible as a deliverable | Within the technical audit scope; verify each fix after release. |
| “This client will be cited in AI answers.” | Not guaranteed | No source establishes a control agencies hold that guarantees serving or citation. |
| “Visibility on the agreed prompt set rose between two dated runs.” | Defensible with method disclosed | Requires a fixed prompt set, named platforms, and dated runs. |
| “AI mentions produced these sales.” | Only with attribution evidence | A mention is not a conversion; the attribution model must be shown. |
| “Press coverage will earn AI citations.” | Not promised | Google cautions against inauthentic mentions; no source links mentions to citations reliably. |
| “Our GEO score is the industry standard.” | Not established | The sources do not establish a universal GEO score; any composite score must be labeled as your own method. |
What the 2024 study measured, and what it does not show
The paper “GEO: Generative Engine Optimization” by Aggarwal et al. appeared in the Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024) and is available on arXiv. It reports that its tested GEO methods improved visibility by up to 40% across the queries and settings it evaluated, and up to 37% on Perplexity. It also reports that effectiveness varies across domains.
These are experimental findings. Use them to justify testing and measurement, not to forecast a client result:
- The 40% figure is the maximum gain observed in that evaluation, not an average across the market.
- The 37% figure applies to Perplexity in that evaluation and does not transfer to other platforms.
- Domain differences mean a result in one vertical does not carry over to another.
The study’s second argument matters more for agency reporting. Generative answers cite sources as inline citations of varying length and prominence, so the authors argue for purpose-built visibility measures. Compare the presence, position, prominence, relevance, and influence of citations, rather than assuming classic blue-link rank is a complete measure.
Google’s guidance: what to stop selling
Google’s guide makes several specific negative statements. Do not sell the following as requirements for Google’s AI features:
- A special
llms.txtor other machine-readable AI file. Google says there is no requirement to create one. - Chunking pages into small passages, or an ideal page length for AI search. Google says neither is required.
- Rewriting content into a special style for AI systems. Google says sites do not need to do this.
- Structured data or special schema markup for generative AI search. Google says it is not required, and there is no special markup for it.
- Inauthentic mentions, or mass-produced pages designed to manipulate rankings or AI responses. Google says these are not sound strategies.
Google also advises evaluating third-party SEO advice, and warns that no third-party tool has access to its internal ranking or AI systems. A tool that claims to reveal how Google ranks or cites pages is describing its own sampling, and your reports should say so.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A measurement program clients can audit
Google’s Search Console includes a Generative AI performance report for Google’s generative Search features. Nothing in the available sources establishes a universal GEO score, so build the program around a method the client can inspect.
- Write the prompt set before the first run. Keep the list fixed across reporting periods, and record which topic, intent, and client product each prompt covers.
- Declare platforms and competitors. Name each assistant or search surface you sample and each competitor brand included in the comparison.
- Set a sampling cadence and date every run. Record whether each run was manual or tool-assisted, and the location it was run from.
- Record the metrics in the table below for every run.
- Pull Google’s own data from Search Console and keep it separate from third-party samples. Do not blend the two into one number.
- Track referral outcomes where attribution exists, and report them in their own section.
| Metric | What it captures | Limit to state in the report |
|---|---|---|
| Mention presence | Whether the brand appears in the answer to a prompt | Depends on the prompt set and the run date |
| Citation presence | Whether a client URL is cited | The cited URL may be a different page from the one you optimized |
| Citation prominence | Where the citation sits and how much text surrounds it | The sources do not provide a standardized scale; define your own rubric |
| Accuracy | Whether statements about the client are correct | Requires human review of each sampled answer |
| Competitor comparison | How named competitors fare on the same prompts | Valid only within the declared prompt set |
| Referral outcomes | Visits, leads, or sales where attributed | A mention is not a conversion; state the attribution model |
Choosing monitoring software
AI search visibility tracking is an active software category, and vendors describe their own services in detail. Vendor positioning is not validation of efficacy. Evaluate candidates on these criteria:
- Platform coverage: which assistants and search surfaces are sampled, and whether that list can change.
- Repeatability: can the same prompt set be rerun on a fixed schedule?
- Prompt-set control: can you add, freeze, and export prompts?
- Citation and source detail: are cited URLs and surrounding text captured?
- Transparent methodology: is sampling documented well enough to explain to a client?
- Time series: is history retained for trend reporting?
- Referral attribution: can outcomes be linked to visits?
- Auditability: can each reported claim be traced back to a stored answer?
These criteria follow from the paper’s multidimensional measurement argument and general reporting practice. They are not an industry standard. Check current features and partner terms directly with each vendor before you resell or recommend one.
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Packaging the work and setting prices
The available sources do not establish GEO agency revenue, market size, adoption, or conversion impact. Price from your own delivery costs rather than from category benchmarks, and structure engagements in phases so each deliverable can be verified:
- Audit and baseline (fixed scope): technical eligibility review, content gap review, and the first measurement run with its method note.
- Remediation and content (scoped by page or topic count): fixes verified after release, and editorial briefs for the prioritized topics.
- Ongoing sampling and reporting (recurring): repeat runs on the same prompt set, a short written interpretation, and a separate referral section.
Write the limits described above into the statement of work, in the same words you use in reporting. Clients who have agreed to those limits in writing are far less likely to hold you to outcomes you cannot control.
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