1. Introduction: the trap is talking about "AIs" as if they all looked alike
When a client says "we want to be visible in AI", they often lump ChatGPT, Perplexity, Google AI Overviews, Claude, Copilot and sometimes Gemini into the same category. It's understandable. To them, all of this looks like generated answers. For an SEO or GEO expert, this simplification is dangerous.
These engines don't create the same search experience. They don't show sources in the same way. They aren't used in the same contexts. They don't trigger the same behaviors. And most importantly, they shouldn't be measured with exactly the same criteria.
ChatGPT is often a tool for conversation, synthesis, reasoning and recommendation. Perplexity puts sources more at the center and lends itself very well to documentary audit. Google AI Overviews fits into the Google SERP and modifies an already existing SEO visibility. Claude is often used in contexts of writing, analysis and documentary work. Copilot is found in uses related to Microsoft, the web, productivity and sometimes the professional environment.
Simply saying "I want to be cited by AIs" is not enough. You need to ask: by which engine, on what questions, in what context, with what type of answer, and for what business objective?
This page offers a useful comparison, not a simplistic ranking. The goal is not to say that ChatGPT is better than Perplexity or that Google AI Overviews is more important than Claude. The goal is to help a freelance SEO, an agency or a GEO expert choose what to test, what to measure and what content to produce depending on the engine targeted.
If you want to dive deeper into each engine, you can read the dedicated pages for ChatGPT, Perplexity and Google AI Overviews.
2. The main comparison criteria
Before comparing engines, you need to choose the right criteria. Otherwise, you end up with a vague table where each engine is described as "fast", "useful" or "powerful". It doesn't serve much purpose.
The usage context
The first question is simple: in what situation does the user use the engine? ChatGPT is often used to explore, explain, rephrase, compare, prepare a decision. Perplexity is heavily used for sourced search. Google AI Overviews intervenes during a Google search. Claude is frequently used to analyze and write. Copilot can intervene in a browsing, productivity or business context.
The context determines which queries to test. A question asked to ChatGPT doesn't necessarily have the same form as a Google query triggering an AI Overview.
Source visibility
Some engines display sources more clearly than others. Perplexity is very interesting for this. Google AI Overviews shows supporting links in the Search environment. ChatGPT can display citations or a sources panel when search is used, but not all responses work like a sourced results page.
For GEO, this source visibility changes the audit method. When sources are visible, you can analyze the chosen pages. When they are less visible, you must observe the response more, the brand description, competitors mentioned and recurring formulations.
The type of answer produced
An engine can produce a short summary, a long answer, a comparison, a list, an action plan, a recommendation, a summary of sources, or an answer integrated into a SERP. These formats influence the content to produce.
A definition page can feed a short answer. A methodological guide can feed an action plan. A comparison can feed a recommendation. A clear product page can help an engine correctly rank a solution.
Possible measurement
Not all engines are measured with the same precision. In Google, you can cross AI Overviews presence, impressions, clicks and positions. In Perplexity, you can note the visible sources. In ChatGPT, you often have to work with question panels, screenshots, answer variations and citations when available.
GEO measurement must therefore remain adapted to the engine, otherwise it becomes falsely precise.
3. ChatGPT: the conversation and recommendation engine
ChatGPT is often the first engine clients think of. Its cultural weight is enormous. Many users employ it to understand a topic, compare options, prepare a decision, summarize information or ask for a recommendation adapted to their context.
What ChatGPT changes for GEO
ChatGPT works very well on conversational queries. The user can add constraints, ask for a level of explanation, rephrase, ask for a table, then ask for a final recommendation. Visibility therefore doesn't only depend on a fixed query.
For a brand, the challenge is to be correctly understood in these scenarios. ChatGPT needs to know what category to place you in, what problem you solve, who you address and why you're relevant.
Content to prioritize
For ChatGPT, the most useful content is clear definitions, comparisons, methods, expert FAQs, use cases, proof pages and very clear commercial pages.
Content that's too marketing-focused will be poorly usable. ChatGPT needs criteria, limits, examples and distinctions. If you want to be recommended for "GEO tool for SEO agency", you need to explain precisely what you do in this context.
Signals to monitor
Observe presence in responses, quality of description, place in recommendations, competitors mentioned, visible sources when they appear, and recurring errors.
Monitoring should include multiple formulations per intent. A single question is not enough.
4. Perplexity: the engine where sources speak loudly
Perplexity is particularly useful for GEO audits, because it often makes sources visible. You can see which pages feed a response, then analyze what they contribute.
What Perplexity changes for GEO
Perplexity puts documentary logic front and center. It searches, synthesizes and cites. This forces content to become citable: clear, structured, recent, precise, capable of answering a question without too much effort.
A page that hides useful information behind too much marketing discourse starts with a handicap.
Content to prioritize
Methodological guides, comparisons, in-depth definitions, field observations, studies, documentation pages and specialized content can work well.
Perplexity is also a good indicator of external sources. If comparisons or directories describe your offer poorly, it can influence the response.
Signals to monitor
Look at presence rate, citation rate as a source, source diversity, freshness of cited pages, recurring competitors and stability over time.
5. Google AI Overviews: the engine that extends SEO into the SERP
Google AI Overviews is different because it fits into Google Search. You shouldn't analyze it as an isolated chatbot. It modifies the SERP, clicks, links and the way users explore a topic.
What Google AI Overviews changes for GEO
AI Overviews can provide a summary directly in the results. Associated links can offer interesting visibility, but they can also redistribute attention. A page can be visible in the AI Overview without being the first classical result, or vice versa.
SEO fundamentals remain essential: indexing, quality, snippet eligibility, useful content, reliability. GEO doesn't replace these basics.
Content to prioritize
Content that answers complex queries, breaks down a topic, provides criteria, explains a method or synthesizes multiple dimensions is particularly important.
A page must be clear, indexable, structured, up-to-date and linked to a coherent thematic set.
Signals to monitor
Observe queries that trigger an AI Overview, supporting links, presence or absence of your site, quality of the synthesis, gaps with classical organic results and impact on clicks.
6. Claude: useful for analysis, but harder to audit as a public engine
Claude is often used to read, analyze, write, synthesize and manipulate documents. Depending on uses and available features, it can also work with web content or provided sources. But for a public GEO audit, it's generally simpler to observe than source-focused engines like Perplexity or a visible feature in Google Search.
What Claude changes for GEO
Claude is interesting because it can influence the way professionals analyze a market, compare solutions or write a recommendation. It's less just a search entry point, and more a work space.
For a B2B brand, this matters. If a consultant uploads multiple pages, reports or competitor content to Claude to prepare a recommendation, the clearest and most argued content has an advantage.
Content to prioritize
Long but well-structured content, reports, methods, case studies, argued comparisons and product documentation can be useful. Claude particularly values content that maintains clear logic over multiple paragraphs.
Signals to monitor
Measurement is more qualitative. You can test scenarios: ask for a comparison, provide multiple sources, observe how Claude describes your brand, see if it correctly identifies your strengths and weaknesses.
7. Copilot: AI visibility in a Microsoft environment
Copilot shouldn't be overlooked, especially in B2B, productivity, enterprise and assisted search contexts. Its interest depends heavily on the target market and user habits.
What Copilot changes for GEO
Copilot can intervene in web searches, productivity tasks, Microsoft environments and professional contexts. For certain targets, particularly B2B, it can become an important discovery or synthesis interface.
The risk would be testing only ChatGPT and Perplexity when decision-makers in a sector work more in the Microsoft ecosystem.
Content to prioritize
Clear, well-indexed pages oriented toward decision, with professional use cases, comparisons and proof are useful. Content must allow quick understanding of what a solution does and why it's relevant in a business context.
Signals to monitor
Test questions close to professional uses: tool choice, solution comparison, brief preparation, team explanation, action prioritization. Observe description, sources, competitors and recommendations.
8. Quick reading table
| Engine |
Dominant use |
GEO strength |
Point of caution |
| ChatGPT |
Conversation, recommendation, synthesis |
Very strong on complex scenarios and comparisons |
Sources sometimes less central depending on the mode used |
| Perplexity |
Sourced search, documentary response |
Excellent for analyzing visible sources |
A citation doesn't guarantee conversion |
| Google AI Overviews |
Google search enhanced |
Direct impact on SERP and supporting links |
Variable triggering depending on queries |
| Claude |
Analysis, writing, documentary work |
Strong for long and argued content |
Less direct public audit |
| Copilot |
Search and productivity in the Microsoft ecosystem |
Interesting in B2B and professional contexts |
Depends a lot on target use cases |
9. How to choose which engines to prioritize
You don't need to test everything with equal intensity. The choice depends on the market, uses and objective.
If you're working a B2B brand
Prioritize ChatGPT, Perplexity, Google AI Overviews and Copilot. Decision-makers can use ChatGPT to frame a topic, Perplexity to search for sources, Google to validate, and Copilot in a professional environment.
If you're working a media or editorial site
Google AI Overviews and Perplexity become very important, because source visibility and impact on clicks are central. ChatGPT remains useful for understanding how the topic is synthesized.
If you're working a SaaS
Strongly test comparison queries, tool choice, use cases and business problems. ChatGPT and Perplexity are priorities, Google AI Overviews too if queries trigger syntheses.
If you're working a local business
Google remains central, but ChatGPT and Copilot can influence recommendation searches. You need to test geo-localized queries, choice criteria, reviews, directories and local sources.
10. Practical tips for auditing multiple engines
- Build a question panel by intent, not just by keyword.
- Test each engine separately, with the same families of questions.
- Note brand presence, competitors, sources and description quality.
- Compare gaps between engines: they often reveal positioning problems.
- Prioritize queries that influence a business decision.
- Transform each major absence into a hypothesis: missing content, weak source, blurry category, insufficient proof.
- Re-test after corrections, because GEO is piloted over time.
A good audit doesn't seek to prove that the brand is "visible in AI". It seeks to understand where it's visible, where it isn't, why, and what needs to be corrected.
11. Building a multi-engine GEO score
Comparing engines becomes much more useful when you implement a simple score. Not a pseudo-scientific score with three decimals. A working score, understandable, that helps prioritize.
The idea is to rate each engine on an identical or similar question panel, then look at the gaps. A brand can be strong in Google AI Overviews, average in Perplexity and almost absent in ChatGPT. This diagnosis is much more actionable than a generic sentence like "AI visibility is low".
Criterion 1: presence
Does the brand appear in the response? If yes, on how many queries? Is it present only on informational questions, or also on comparison and choice questions?
Presence alone isn't enough, but it gives a first reading. Total absence on business queries is a strong signal.
Criterion 2: role in the response
Being mentioned isn't the same as being recommended. A brand can appear as a secondary example, technical source, main option, alternative, or just a name in a list. The role must be qualified.
In an audit, I prefer a brand cited three times as a relevant option over a brand mentioned ten times in generic lists.
Criterion 3: accuracy of the description
Does the response correctly describe the offering, features, sector, limits and target audience? A poor description can be more dangerous than absence, because it guides the user toward a false conclusion.
This criterion is particularly important for offerings that evolve quickly, like AI tools, SaaS or specialized services.
Criterion 4: sources and evidence
When sources are visible, look at which ones support the response. Are they internal, external, recent, specialized, reliable? If engines rely mainly on competitor sources, the problem isn't just editorial. It may be documentary and reputational.
Criterion 5: stability
An answer obtained only once isn't enough. Re-test over time, with multiple formulations. Stable visibility is worth more than an isolated appearance.
12. Example of multi-engine analysis
Let's take a GEO agency that wants to be visible on queries related to auditing presence in AI responses.
In ChatGPT, it appears when the question explicitly mentions "GEO agency", but not when the user asks "how to audit AI citations for a SaaS brand". This indicates that positioning is understood, but use cases aren't associated enough with the brand.
In Perplexity, the agency is never cited as a source. Responses rely on two competitor guides and a media article. This shows a deficit of citable content or external sources.
In Google AI Overviews, an agency page appears as a support link on "difference between SEO and GEO", but not on audit or KPI queries. This indicates that the educational base works, but methodological content needs strengthening.
In Claude, when you provide multiple site pages, the model understands the expertise well but finds deliverables vague. This reveals a commercial clarity problem.
In Copilot, the brand is absent from general recommendations, but appears if the user searches for its name. This signals weak visibility in comparison sources.
The action plan becomes obvious: create or strengthen a GEO audit page, produce content on KPIs, improve commercial pages, get a few useful external mentions, then re-test queries in each engine.
13. Adapt content based on the engine
The editorial base remains common, but some adjustments are smart.
For ChatGPT, clarify scenarios
Write content that answers complete situations: "for an agency", "for a SaaS", "for an e-commerce", "to convince a client", "to prioritize after an audit". ChatGPT is very often used in this conversational logic.
For Perplexity, make pages citable
Provide clean definitions, short methods, lists of criteria, update dates, precise examples. Perplexity must be able to select your page as a source without guessing where the useful information is.
For Google AI Overviews, strengthen sub-questions
Work on content that answers multiple angles of a complex query. Pages must be indexable, eligible for snippets, well-structured and linked to a coherent thematic set.
For Claude, prioritize argumentation
Claude can be used to analyze long documents. Content that explains a method, defends a point of view, details limits and presents concrete cases can better withstand analysis.
For Copilot, think professional context
Content oriented toward decision, productivity, team, budget, comparison and business integration is particularly useful. It must help a professional user transform a response into action.
14. Mistakes to avoid in an engine comparison
The first mistake is looking for a winner. That's not the point. One engine can be priority for one brand and secondary for another.
The second mistake is comparing responses obtained with prompts that are too different. If you test a very precise question in ChatGPT and a vague query in Perplexity, the comparison isn't worth much.
The third mistake is only looking at brand presence. You also need to look at description quality, sources, competitors, angles, stability and role in the response.
The fourth mistake is drawing a conclusion after a single session. Responses vary. You need to repeat, document and accept uncertainty.
15. Choose engines based on business objective
The best engine to prioritize rarely depends on personal preference. It depends on what you want to achieve. Brand visibility, lead generation, editorial credibility, sales assistance, presence in comparisons: each objective calls for a different reading.
Objective: be discovered
If the goal is to be discovered by users who don't yet know the brand, Google AI Overviews, Perplexity and ChatGPT are priorities. Google still captures a large share of initial searches. Perplexity helps users who want sources. ChatGPT influences early shortlists in conversational questions.
In this case, work mainly on definitions, choice guides, comparisons and pages that answer broad but qualified questions.
Objective: be recommended
If the goal is to be recommended as a solution, ChatGPT and Copilot become very important, especially in B2B. The user often asks "which tool to choose", "which agency to contact", "which method to apply". The response can guide a decision before site visit.
You then need to clarify use cases, differences from competitors, proof, limits and adapted user profiles.
Objective: become a source
If the goal is to be cited as a reference, Perplexity and Google AI Overviews are particularly interesting. Visible sources let you see if your content is actually used to build a response.
In this case, prioritize citable content: detailed methods, studies, clean definitions, observed data, practical guides, regularly updated pages.
Objective: correct a bad perception
If engines describe a brand poorly, the goal isn't first to get more visibility. You need to correct understanding. This goes through site pages, external sources, comparisons, public sheets and vocabulary consistency.
This work concerns all engines, but ChatGPT is often revealing because it rephrases a lot. A repeated bad rephrasing indicates a positioning or source problem.
Objective: defend expertise
For an agency or expert, Claude, ChatGPT and Perplexity can be very useful to test. Users aren't just looking for a name. They're looking for a method, a market reading, an ability to explain and prioritize.
Content must therefore show judgment: what to do, what not to do, in what order, with what limits. This is often where overly neutral content loses.
Objective: protect an established brand
For an already-known brand, the risk isn't just absence. It's poor synthesis. An engine can simplify the offering, forget a product evolution, cite an old source or compare the brand to players who don't compete in the same category.
In this case, GEO work looks like perception management. You need to verify brand responses, comparisons, competitor queries, external sources and official pages. The goal is to reduce the gap between what the brand actually is and what engines say.
Objective: enter a shortlist
For a younger brand, the objective can be simpler: appear in the first solution lists. ChatGPT, Perplexity and Copilot are then very important, because they can build a shortlist in seconds.
Content must help the engine justify the brand's presence: clear use case, neat category, differentiation, proof, examples, coherent external sources. Without these elements, the brand remains hard to recommend.
This work takes patience, but it avoids depending solely on brand awareness or an isolated SEO position.
And in a market where early recommendations can be generated without a site visit, this shortlist presence is often worth more than simple display.
16. Conclusion: there isn't one GEO, but multiple visibility terrains
Comparing generative engines forces you out of slogans. ChatGPT, Perplexity, Google AI Overviews, Claude and Copilot aren't piloted exactly the same way.
The foundation remains common: clarity, reliability, structure, examples, proof, sources, thematic consistency. But measurement, response formats, uses and priorities change depending on the engine.
In my view, this is where good GEO experts will distinguish themselves. Not by promising overall visibility "in AI", but by building precise reading: which engine, what query, what source, what response, what action.
Generative visibility isn't one block. It's a set of terrains. And each deserves its own reading.