AI SearchAnswers.

An engine that is about to name three vendors has to be confident the thing it is naming exists, does what the user needs, and can be described without contradiction. It builds that confidence from your site, your structured data and independent sources that discuss you.

When those three disagree, or when the last of them is simply absent, the safest move for the model is to name a competitor it can verify. Most invisibility cases we open are not a content problem at all. They are an identity problem: the same company described four different ways across its own pages, with no machine-readable link between them.

The overlap is larger than most vendors admit. Google's own guidance on its generative experiences, updated 10 July 2026, still lists conventional SEO, genuinely useful content and technical accessibility as the foundation. There is no separate mandatory GEO technology and no structural shortcut.

What actually changes is the unit of success. In SEO you win a position. In GEO you win a sentence, and sometimes a link next to it. That shifts the work toward clear claims, clean entity data and sources an engine can stand behind.

The longer comparison is here.

It should never be prioritized over pages that genuinely answer a question. If an agency is leading its pitch with llms.txt as a headline deliverable, that is a useful signal about the rest of the proposal.

Cipion publishes one at cipionmarketing.com/llms.txt on the same logic: cheap, harmless, not the point.

In practice that means three things. Answer the question in the first 40 to 60 words of the page, before any preamble, because that block is what gets lifted. Use the wording real people use, not internal product language. And make the claim checkable, with a date, a number or a named source, because an engine summarizing for a stranger prefers a sentence it can stand behind.

What does not work: keyword stuffing, publishing the same page for forty cities, or adding schema to a page that says nothing. Google's spam policies explicitly cover scaled content abuse, and a thin page with perfect markup is still a thin page.

Worth setting expectations honestly: appearing in an AI Overview is not something anyone can guarantee, and the set of citations for a given query changes over time. The longer guide is here.

Neither acronym is used by the platforms themselves. Google's guidance for its generative experiences, updated 10 July 2026, still describes conventional SEO, genuinely useful content and technical accessibility as the foundation. There is no AEO specification and no mandatory GEO technology. Anyone selling you one of the two labels as a distinct product owes you an explanation of what is actually different in the work.

Where a real difference shows up is in measurement. The older AEO playbook aimed at a snippet you could open, see and screenshot. A generated answer is assembled per query and varies between runs, so the honest unit is frequency of mention across repeated runs of a fixed set of prompts, not a position. On the Google side there is now one native signal: the generative AI performance report in Search Console, whose worldwide rollout was announced on 31 August 2026, gives impressions from AI Overviews and AI Mode by page, country, date and device. It does not give clicks or conversions.

So the useful question is not which acronym an agency prefers. It is what they will measure, how often they will rerun it, and what the baseline looked like before the work started. The longer AEO walkthrough is here.

For Google the bar is documented and short. Its AI features guide says a page must be indexed and eligible to be shown in Google Search with a snippet to appear as a supporting link in AI Overviews or AI Mode, with no additional technical requirements. So noindex, nosnippet, data-nosnippet and a tight max-snippet all limit what can be shown. Search Console also has a Search generative AI control. It includes your site by default, but a property inherits the setting from its closest parent that stopped inheriting, so check it on every property you own before blaming the content.

ChatGPT and Perplexity each run their own search crawler. OpenAI states that sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers, although they can still appear as navigational links. GPTBot is a separate agent used for model training, so blocking it does not remove you from ChatGPT search. Perplexity says PerplexityBot surfaces and links websites in its results, and recommends allowing it in robots.txt and permitting its published IP ranges. A security plugin, CDN bot rule or hosting firewall can block these crawlers even when robots.txt allows them, so check your server and CDN logs for refused requests from those agents.

If access is clean and you are still absent, the problem has moved up a layer: the engines can reach you but have no reason to name you. That is an entity and content question, covered in the first answer on this page, and it takes longer. Fixing access makes you eligible, not chosen, and nobody can honestly promise when or whether an engine will cite you. When we audited our own domain in September 2026, this layer was where the first findings were, including a robots.txt that allowed GPTBot but not OAI-SearchBot. The full list is in how to program an agent to run your GEO maintenance.

Google's own documentation for AI Overviews and AI Mode, last updated on 10 December 2025, states that a page only needs to be indexed and eligible to show with a snippet, with no additional technical requirements, and it lists keeping Business Profile information up to date among the basics. Google's local ranking help page names the three factors behind local results: relevance, distance and prominence, and says plainly that there is no way to request or pay for a better local ranking. A local business controls relevance through accurate categories, services and page content, and influences prominence through the reviews, links and coverage it earns. Distance depends on where the searcher is, so no provider can guarantee that a local business appears for every nearby query, in the map results or in an AI answer.

Google Business Profile guidelines set the boundary on what a local business can claim. A profile is only allowed for a business that has a physical location customers can visit or that travels to its customers, and a service-area business cannot list a virtual office unless that office is staffed during business hours. Creating profiles or near-identical city pages in towns where the business has no real presence breaks those guidelines, and mass-produced location pages can also fall under Google's spam policy on scaled content abuse. The honest local playbook is narrower: one accurate profile per real location, one website page for each service the business actually offers, and the same name, address and phone number wherever the business is listed.

The main difference between local and national GEO is the unit of measurement. A national brand tracks whether it is named across broad category prompts, while a local business should track a short list of prompts that include its city or neighborhood, such as a service plus a place name, and log the answers every month with the date and the platform. Answers to local prompts also shift with the searcher's location, so a single test from one address is not a baseline. Search Console's generative AI report shows impressions by page, country, date and device, not by city or by query, so for a local business the prompt log remains the main evidence. A sensible first step is a technical and entity review like the one in our GEO audit checklist.

Google's documentation, last updated on 10 December 2025 and read on 30 September 2026, says a page must be indexed and eligible to be shown in Search with a snippet, and that there are no additional requirements or special optimizations for AI Overviews or AI Mode. Google lists three practical basics: allow crawling in robots.txt, make content findable through internal links, and keep important content in textual form. Google also names the controls that limit appearance: robots.txt directives for Googlebot, preview controls such as nosnippet and max-snippet, and noindex. For Google, the work is ordinary search hygiene, and the AI features sit on top of it.

OpenAI's crawler documentation says OAI-SearchBot surfaces sites in ChatGPT search, and a site that blocks it will not be shown in ChatGPT search answers, though it can still appear as a navigational link. OpenAI says robots.txt changes take about 24 hours to apply and recommends allowing its published IP ranges. GPTBot is a separate crawler used for model training, so allowing search does not require allowing training. Perplexity's documentation says PerplexityBot exists to surface and link sites in Perplexity results, is not used to train foundation models, and should be allowed in robots.txt along with its published IP ranges. Perplexity-User visits pages when a person asks a question.

The shared groundwork across all three platforms is a site that can be crawled, pages that are indexed where an index applies, and copy that states plainly who the business is and what it offers. No platform documents a mechanism that turns eligibility into a citation, so measurement should be a dated log of the same prompts on each platform, reported as observations and never as guaranteed results. A technical and entity review like the one in our GEO audit checklist is a sensible first step, and the answer on brand invisibility above covers what to check when access is fine and the brand still does not show up.

It reports impressions from AI Overviews and AI Mode, broken down by page, country, date and device. That is a real measurement and a genuine step forward.

What it does not give you: clicks or conversions attributable to AI answers. The data is also counted inside your Web totals rather than as a separate audience, so it cannot be added on top of existing numbers. Before promising a client this report, confirm the property actually has it and has enough impressions to be worth reading.

Citation share is the percentage of your tracked prompts where your domain is cited at all. Answer presence is whether the brand is named even without a link, which matters because ChatGPT often does exactly that. Position is where you sit in the citation list when you are there.

Anything presented to you as an exact "AI traffic" or "AI revenue" figure is an estimate built on assumptions. Estimates are fine. Estimates presented as measurements are not.

Build a fixed set of 20 to 40 prompts covering your category, run them on a schedule, and record which domains are cited, in what position and with what framing. Keep the set fixed, because changing the prompts between runs destroys the comparison.

That log is the only honest baseline for AI visibility work. It measures what the engine actually returned, on a date, rather than what a tool estimated.

The practical consequence is asymmetric. Perplexity is easier to audit, because the sources are right there and a click can produce measurable referral traffic. ChatGPT is easier to underestimate, because a brand can shape the answer a buyer reads and generate almost no trackable click while doing it.

If you judge AI search purely by referral traffic in analytics, you will conclude ChatGPT does nothing for you. That conclusion is usually wrong.

What makes the log longitudinal is what stays constant. Same prompt text between rounds, same number of repetitions, fresh sessions with no history, and the country and language written down on every run. Report citation frequency as valid runs citing your domain divided by total valid runs, and publish the denominator next to it. Keep the unfavorable runs too, because a log with the bad weeks deleted cannot show a trend. If you want the run automated rather than done by hand, the method is in how to program an agent to run your GEO maintenance.

Two second signals are worth pairing with it. Your own access logs identify Perplexity by user agent: per Perplexity's bot documentation, checked on 21 September 2026, PerplexityBot surfaces and links websites in Perplexity search results and is not used to crawl content for foundation models, while Perplexity-User visits a page to help answer a question a user just asked. Referral sessions from perplexity.ai in your analytics are a floor rather than a total, since referrer data gets lost along the way. Search Console's generative AI performance report, announced for worldwide rollout on 31 August 2026, reports AI Overviews and AI Mode impressions only, so it tells you nothing about Perplexity.

Be honest about the ceiling on all of this. Mention frequency inside your own battery is not share of voice and not exposure among real users, it is what one prompt set returned on one date. Third-party trackers run the same prompts for you, which is convenient and can be worth paying for, but their output is a sample as well, and a sample presented as a measurement is the same mistake either way. Keep "we were cited" separate from "we were described correctly", because a confident wrong description is its own problem and usually the more urgent one.

Start with the only first party data in the category, which is free. Search Console's generative AI performance report, announced for worldwide rollout on 31 August 2026, covers impressions from AI Overviews and AI Mode grouped by page, country, date and device. Checked against Google's own help page on 22 September 2026, it reports impressions only: no clicks, no average position, no query dimension and no split between AI Overviews and AI Mode. That is also the ceiling on what anyone can sell you about Google, so a dashboard showing your ranking inside AI Overviews is not reading Google data. It is running its own prompts.

The second category does exactly that, on a schedule, and records whether you were mentioned and which sources were cited. Useful, and worth paying for if it saves you the work, but the output is a sample rather than share of voice no matter what the dashboard calls it. Judge these products on evidence handling instead of on the size of the score: does it store the full response text with the engine, date, country and number of repetitions, can you export the raw log, and does it keep the runs where you did not appear. A single AI visibility score with no prompt list and no denominator behind it is a number, not a measurement. The method underneath is the same one described in our AEO guide for ChatGPT and Perplexity, and running it by hand for two weeks tells you what you would be buying.

The third category is ordinary technical crawling, and it is the one most brands skip while shopping for trackers. Google's AI features documentation, checked on 22 September 2026, says a page has to be indexed and eligible to be shown with a snippet, and that there are no additional technical requirements to appear in AI Overviews or AI Mode. Nothing on that list is exotic, and nothing on it requires a purchase. We do not publish a ranked vendor list on this page on purpose: this software category is barely a year old, the products change every quarter, and a ranking written today would be wrong before it was useful to you.

They are separate user agents. Allowing your content to be found and cited does not oblige you to allow it to be used for training, and the reverse is also true.

Decide on each one deliberately in your robots.txt rather than pasting a template from a blog post. And a reminder that gets skipped: robots.txt is a crawling instruction, not a security control. It protects nothing. If something must not be public, it needs authentication.

FAQPage structured data still earns its place, because it makes a question and its answer a clean, machine-readable pair that is easy for a retrieval system to lift. That is extractability, and it is worth having.

It is not a rich snippet any more, and anyone still selling it as one is working from a deck they have not updated in over a year.

Entity and structured data corrections propagate fastest, because they only need a recrawl to take effect. Cleaning up a domain that is carrying old junk pages or a confused identity often produces the first visible change.

Earning citations in competitive commercial categories takes longer, because it depends on third-party sources the engines already trust, and that trust cannot be bought outright. Any timeline shorter than this that comes with a guarantee is a sales device.

Gmail's sender guidelines set the baseline for any marketing automation program that emails consumers. Since 1 February 2024, anyone sending 5,000 or more messages a day to personal Gmail accounts must authenticate with SPF, DKIM and DMARC, align the From domain with SPF or DKIM, support one-click unsubscribe on marketing mail and keep the spam rate reported in Postmaster Tools below 0.30%, according to Google's own sender guidelines help page. Microsoft applied similar rules to Outlook.com: from 5 May 2025, high-volume domains without SPF, DKIM and a DMARC policy of at least p=none are routed to Junk, as announced on the Microsoft Defender for Office 365 blog. No automation platform can fix missing DNS records, so sender authentication is the first item to audit before a new sequence goes live.

Apple's Mail Privacy Protection changed what an email open means for automation triggers. Apple's support documentation says the feature hides the recipient's IP address, downloads remote content privately in the background when a message arrives rather than when it is viewed, and prevents senders from seeing whether the message was opened. A tracking pixel can therefore fire for an Apple Mail user who never read the email. Any automation that branches on an open, such as a follow-up email, a lead score increase or a sales alert, inherits that noise. Clicks, replies, form submissions, booked meetings and CRM stage changes are actions a person actually took, which makes them the more reliable triggers to build workflows on in 2026.

AI inside a marketing automation stack mostly handles drafting, classification and routing: writing message variants, tagging inbound replies by intent and summarizing a lead's history before a sales call. Those AI steps are cheap to run and easy to check against the source data. The decisions that still need a person are what is true about the business, which offer goes to which segment, and when a sequence should stop contacting someone. Results depend on list quality, offer and sending history, so any benchmark quoted without those three details says little about a specific account. A practical walkthrough of how these workflows fit together is in our marketing automation guide for 2026.

Most of the work in AI creative production happens before any frame is generated. A strategist writes the brief from a positioning decision and an audience insight, then a script and a shot list fix what each frame has to communicate. The next stage locks references: character sheets for faces and wardrobe, product renders, locations and a lighting look. Shots are then produced image-to-video from those references, because keeping the same face, logo or product across shots is the hardest thing to get from a text prompt alone. Selection is where the hours go: every generation is checked against the shot list, and many are discarded for artifacts, off-brand details or broken hands and text. The surviving clips are cut, graded, scored and captioned like any conventional spot, which is how our AI creative production process runs.

Ownership is the part of AI creative production most brands skip. The US Copyright Office concluded in Part 2 of its Copyright and Artificial Intelligence report, published January 29, 2025, that the mere provision of prompts does not make an AI output copyrightable, and that protection depends on a human determining sufficient expressive elements, for example through creative arrangement or modification of the output. The Office also said that using AI to assist creation, or including AI material inside a larger human work, does not by itself bar protection. In practice, the human-directed stages of script, selection, edit, compositing and sound are where that authorship sits, so the brief, reference sheets and edit files are worth keeping as a record. Anything that will run as paid media should still get a rights review from counsel.

Disclosure rules also shape what gets produced. YouTube requires creators to disclose realistic altered or synthetic content, such as footage that makes a real person appear to say or do something they did not, alters footage of a real event or place, or generates a realistic scene that did not occur. YouTube exempts clearly unrealistic content and minor edits such as color adjustment, beauty filters or upscaling, and treats AI help with scripts or thumbnails as production assistance that needs no label. Other platforms apply their own labeling rules, so the delivery checklist for an AI spot needs a disclosure decision per platform, made before launch rather than after a takedown notice. A production that plans for disclosure can use generated footage freely; what it cannot do is present a synthetic scene as a record of something that happened.

Google's Ads Help page on ads and AI Overviews says text and Shopping ads from existing Search, Shopping and Performance Max campaigns can show above, below or within AI Overviews, provided the ad is relevant to both the query and the Overview. Placement within AI Overviews is limited to English in 12 countries including the US, sensitive verticals such as finance and healthcare are excluded, advertisers cannot target a position inside the Overview, and there is no segmented reporting for these placements. Google's Search Central guidance on AI features is a separate document and states that there are no additional requirements to appear in AI Overviews or AI Mode beyond being indexed and eligible to show in Search with a snippet.

OpenAI's help center describes ChatGPT Ads as a separate paid format: ads appear below the end of a response, labelled as sponsored and visually separate from the answer. Ads are being rolled out gradually to eligible Free and Go users in select regions, and are not shown on Plus, Pro or Business plans. Advertiser context hints guide matching but are not exact-match keywords and do not guarantee delivery in specific conversations, and buying is by views, clicks or conversions. We read this in OpenAI's help center excerpts on 29 September 2026, and rollout details change often, so check the current pages before budgeting.

The practical split for a brand is simple. Ads are paid media, judged on clicks and conversions, and they can be switched on or off. Citation is earned: pages that are indexed, useful and clear about who the business is, plus crawler access that matches your goals. Any vendor selling a guaranteed citation in ChatGPT or AI Overviews is describing something neither platform documents. The GEO audit checklist covers the earned side, and no plan can promise a result there either.

Cipion prices per engagement rather than from a public rate card, because the honest number depends on the size of the site, the state of its structured data and how contested the category is. Quoting before seeing those is guessing with extra steps.

The first conversation and the AI Visibility Snapshot are free, and you get the findings whether or not you hire us. The full breakdown of what drives the cost is here.

The last one is the most revealing. Any agency guaranteeing a position in AI answers is selling something no engine currently offers. There is no paid placement in an AI Overview, no submission form for ChatGPT, and no mechanism to buy a citation.

The baseline question matters nearly as much. If nobody measured your citation share before starting, nobody can prove the work did anything afterwards. More on evaluating agencies here.

Evidence you can check starts with the agency's own website, because an agency selling AI visibility is running the same experiment on itself. Read its robots.txt. OpenAI documents OAI-SearchBot as the crawler behind ChatGPT search and GPTBot as a separate crawler for model training, so an agency that blocks the first, or treats the two as one, has not applied the documentation it sells. Then check whether its structured data parses and whether its claims carry dates and named sources. Our GEO audit checklist lists what to look at.

Ownership is the criterion most often skipped. Before signing, confirm in writing that prompt logs, dashboards, analytics properties, ad accounts, content files and any automations are created under your accounts, or handed over when the engagement ends. Work you cannot take with you is rented, and it makes switching agencies later far more expensive than it needs to be.

The two answers above cover what the work tends to cost and what to ask once you are on a call. These criteria are the filter that decides who gets that call.