- Separate the labels from the work
- Improve what readers can verify
- Choose a measurable scope
| Work area | Shared foundation | Potential additional GEO scope |
|---|---|---|
| Technical access | Approved public pages can be reached and understood | Inspect named-system controls and documented crawler behavior |
| Content | Accurate useful explanations and evidence | Review how selected generative answers represent those facts |
| Measurement | Relevant visibility, visits and business outcomes | Document bounded prompt samples and available AI visibility reports |
| Procurement | Clear deliverables and accountable review | Identify incremental work without duplicate billing |
| Outcome limit | No guaranteed organic ranking | No guaranteed citation or recommendation |
Original analysis. Google-specific claims follow current official guidance; other systems require separate verification.
Define GEO by the proposed work
GEO usually means generative engine optimization: work intended to improve how a business or its content appears in generative search experiences. SEO covers the broader work of helping appropriate search users find and use a website. The labels overlap, and providers may use GEO to describe very different deliverables.
Google's current generative-AI optimization guide explicitly treats optimization for its generative Search experiences as SEO. That is Google's stated perspective, not proof that every other answer service operates identically. Ask a provider which systems, pages, and user questions its proposal actually addresses.
A useful comparison therefore examines scope rather than competing acronyms. Technical access, factual content, clear business information, and meaningful measurement can support both. An AI-specific observation program may add useful evidence, but a new name alone does not establish a separate technical requirement or a superior result.
Separate established foundations from bounded experiments
Foundational work includes making intended public pages accessible, explaining the offer accurately, and organizing information so readers can evaluate it. If an important service page is broken or misleading, fixing it has a concrete purpose regardless of whether an AI system later cites it.
Experimental work might examine how a defined set of questions is answered across selected systems and dates. That can reveal missing explanations or factual inconsistencies. It should be reported as a sample of observations, not as a complete measurement of what every customer sees.
Ask what evidence would change the recommendation. If a proposed tactic remains mandatory whether it produces useful observations or not, the business cannot evaluate it. Keep uncertain methods limited, documented, and separate from necessary corrections that are already supported by the website's actual condition.
Use current Google inclusion controls
Google's newer guidance requires an eligible indexed page and inclusion in Search generative AI features through the relevant Search Console control. The control documentation says Include is the default, with inheritance possible for child properties, and notes worldwide rollout on August 31, 2026. Eligibility still does not guarantee appearance.
The documented exclusion option concerns specified generative Search features rather than general Search ranking, and it is separate from AI-training controls. This distinction matters when an owner considers visibility or content-use choices. Do not change a setting merely because a sales proposal uses the word optimization.
Have an authorized owner inspect the actual property and inherited settings when that review is in scope. A public article cannot establish how a particular account is configured. Record the observation and any approved decision, and preserve the difference between reading a control and changing it.
Make the content useful enough to support a decision
A generative summary may draw from a page, but the page must still serve people who visit it directly. Explain the conditions that change an answer, identify the source of factual claims, and show what a customer should do next. Short sentences without context can be easy to quote while remaining unhelpful.
Use the business's real knowledge where available: approved process details, original demonstrations, supported examples, and clearly defined limitations. Do not invent firsthand experience, clients, or results to make an article seem distinctive. A labeled hypothetical example can explain reasoning, but it is not evidence that the business completed that work.
Google's current guide says its Search systems do not use llms.txt for special visibility treatment and do not require content to be split into tiny pieces. Other systems may have different documentation. Evaluate a technical request against the named system rather than treating a fashionable file or format as a universal requirement.
A fictional packaging supplier comparison
Imagine a fictional packaging supplier whose prospects compare stock cartons with custom printed packaging. Its existing page lists both but does not explain what information is needed for an estimate or which decisions affect suitability. The supplier has no approved case study or measured conversion result to publish.
A useful shared SEO and GEO assignment could clarify the actual intake requirements, explain the distinction between available stock products and separately scoped custom work, and add an original preparation worksheet. Product specifications and availability would be approved by the supplier rather than inferred by a writer.
An optional observation exercise might record answers to a small set of realistic comparison questions and check whether the supplier is described accurately. Missing citations would not prove that the new page failed. The first reviewable result is a better supported explanation; visibility is a separate external outcome.
Do not generalize one crawler's behavior to every system
Different services document different crawlers and access purposes. Perplexity, for example, publishes its own crawler information. Review the named service's current guidance before making access decisions, and distinguish crawling for discovery from other uses such as training or user-requested retrieval where the documentation does so.
A crawler entry in a log does not establish that the content was cited, recommended, or responsible for a lead. Likewise, allowing access is not a promise of inclusion. The report should state what was actually observed and avoid turning technical availability into a business-result claim.
Preserve privacy and publication boundaries. A draft, private account page, or restricted document should not be exposed simply to increase accessible content. The owner's approved publication intent comes before a speculative visibility tactic. Any changes to sitewide access rules need their own clear scope and authorization.
Use the current reports for what they measure
Google announced dedicated Search Generative AI performance reports in June 2026 and updated the announcement to say they reached websites worldwide on August 31. The announced views describe impressions and dimensions such as pages, countries, dates, and devices for Search. These are visibility measures, not a dedicated sales report.
Keep website visits, successfully delivered inquiries, and accepted business opportunities in separate appropriate measurement. A page can receive an impression without a visit. A visitor can return through another channel, and an inquiry's source may remain uncertain. Do not rename impressions as AI leads.
For the fictional packaging supplier, compare the available visibility record with the page's actual content and inquiry quality. If several customers ask the same unanswered question, improve the explanation. If attribution is incomplete, retain that uncertainty instead of assigning every new request to the latest content initiative.
Evaluate visibility samples and vendor scores carefully
A provider may use a set of prompts to monitor brand mentions or citations. Ask for the question wording, systems, dates, geographic or account context where relevant, and the rule for counting a mention. Repeated prompts can vary, so a small sample should not be presented as a stable market share.
Inspect whether the sample resembles meaningful customer decisions or was chosen to make the business appear. A branded question and an unbranded category comparison answer different questions. Keep them separate, and preserve examples of inaccurate or missing descriptions alongside favorable observations.
If a proprietary score is used, request its definition and limitations. It may be a useful trend within one unchanged method, but it is not automatically comparable with another tool's score. A number becomes more useful when it leads to a specific, supported improvement rather than an unexplained monthly ranking chart.
Buy a concrete work plan rather than a replacement promise
An SEO scope may include technical diagnosis, information architecture, content review, and reporting. A GEO-labeled scope may include some of those same tasks plus system-specific observations. Ask which work is genuinely additional and which would duplicate an existing engagement.
Define deliverables such as a reviewed page, corrected factual claim, tested public access, or documented visibility sample. Require accountable source review and a clear distinction between recommendation, implementation, and observed outcome. No provider can responsibly guarantee that an independent generative system will recommend the business for every relevant question.
Dappr offers SEO and AI-search work and therefore has a commercial interest in the comparison. Bring current pages, real customer questions, approved expertise, and the available reports. The useful decision is how to improve and measure the actual customer journey, while keeping experiments proportionate to the evidence.
Questions before you begin
Does GEO replace SEO?
Not as a universal rule. Google explicitly describes optimization for its generative Search features as SEO, and many practical tasks overlap. Other services have their own systems and guidance. Compare the proposed pages, technical checks, research, and reporting before paying for a second package that may duplicate existing work.
Is llms.txt required to appear in Google AI answers?
Google's current generative-AI optimization guide says Search does not use llms.txt for special visibility or ranking treatment. That does not establish how every other service behaves. Ask which documented system requirement a proposed file addresses, and do not treat adding it as proof of improved AI-search performance.
Can Search Console control inclusion in Google generative features?
Google documents a Search generative AI control with Include, Exclude, and inherited settings. Include is the default, and account-specific configuration needs authorized inspection. This is distinct from a guarantee of appearance and from controls for training or general Search inclusion. Read the current scope before changing anything.
Do AI visibility impressions prove that the campaign generated leads?
No. Impressions describe visibility under the report's definitions. Visits, completed requests, qualification, and sales need separate records and careful attribution. A simultaneous increase in several measures is worth investigating, but it does not by itself prove that a particular AI appearance caused a business outcome.
What should a small business request from a GEO provider?
A named scope, source-backed content improvements, system-specific documentation, transparent observation methods, and understandable limitations. Ask who reviews claims and how results connect to meaningful customer tasks. Avoid guaranteed citations, invented experience, or proprietary scores presented without enough explanation to support a decision.