GEO Explained: Generative Engine Optimization Without the Buzzwords

GEO — Generative Engine Optimization — is the practice of making your brand and pages easy for a generative system to retrieve, compress, and name when it writes an answer. If SEO is about ranking documents and AEO is about winning inclusion inside answers, GEO is the label most teams use when the engine in question synthesizes prose: Google AI Overviews, AI Mode, ChatGPT with search, Perplexity, Copilot, and peers.

At Spurlock Studios we treat GEO as a subset of AEO, not a rival religion. This spoke defines the word, separates the 2024 research paper from vendor product scores, and lists the few content and measurement changes that actually matter. It does not rebuild the five-layer method or the 90-day sequence. Those live in the playbook. The rank-versus-citation scoreboard lives in AEO vs SEO.

The short answer

• GEO is a label for generative surfaces. The work is still: be retrievable, be compressable, be named accurately.
• Aggarwal et al. coined the term in 2023–2024 and measured share of the generated answer, not clicks. Evidence helped. Keyword stuffing did not.
• Google’s 2026 guidance: for Google Search, many AEO/GEO “hacks” are unnecessary. Believe them for Google. Do not export that sentence to ChatGPT Search.
• Semrush and Surfer sell GEO-flavored scores. Those scores are theirs. They are not a citation.
• Keep doing SEO. Layer AEO. Say “GEO” when you mean synthesis-heavy products. Do not fund three retainers.

What does GEO actually mean in 2026?

Three different things get called GEO in the same kickoff. Mixing them is how you buy a dashboard and still cannot answer “were we in the answer?”

Meaning	Who uses it	What it actually is
Academic GEO	The 2024 paper and people citing it	A black-box rewrite test: change a page, measure how much of the generated answer that page occupies
Operator GEO	In-house SEO / content / PR	AEO work scoped to engines that write prose (Overviews, chat with search)
Vendor GEO	Tool marketing pages	A product SKU: visibility score, prompt tracker, “AI Search” content score

The academic meaning is the only one with a public method. Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan, and Deshpande — “GEO: Generative Engine Optimization” (arXiv:2311.09735, Nov 2023; KDD 2024) — formalized generative engines as systems that retrieve sources and then write a grounded answer with inline citations. Their claim was not “SEO is dead.” It was: visibility inside that written answer is a different metric than rank on a list, and you can test page edits against it.

Operator GEO is the useful meeting word. When a CMO says “we need GEO,” they usually mean “ChatGPT and Overviews do not name us.” That is an AEO problem on generative surfaces. Call it GEO if it keeps the room moving. Do not staff it as a third department.

Vendor GEO is a label on a report. Treat the report as a log. Do not treat the label as a strategy.

• In the brief, write which of the three meanings you mean
• If a vendor says “GEO score,” ask what corpus, which products, and what counts as a hit
• If an agency says “GEO retainer,” ask which prompts, which products, and what they will ship in 30 days

If you cannot get those three answers, you are buying a noun.

What did the GEO paper measure — and what did it not?

Cite the paper when you use the term. Do not cite a LinkedIn carousel that turned “up to 40%” into a traffic forecast.

What they built, from the HTML preprint and the KDD version:

Piece	What the paper reports	How to use it in 2026
GEO-bench	~10,000 queries (8k / 1k / 1k), 25 domains, top-5 Google result text as sources	Directional, not your category forecast
Lab engine	Retrieve top-5, then a then-current chat model writes a cited answer	Engines have moved. The shape of the test still holds
Win metric	Position-Adjusted Word Count (PAWC): share of answer words, weighted toward earlier sentences	Answer-share, not sessions
Second metric	Subjective Impression via an LLM judge (relevance, influence, uniqueness, and related facets)	Even more setup-bound. Do not put it on a board slide
Best methods	Cite Sources, Quotation Addition, Statistics Addition: ~30–40% relative PAWC lift vs unoptimized baseline; best method +41% PAWC / +28% Subjective Impression in the main table	Put real numbers, quotes, and sources on the page
Live check	They also ran methods on a commercial generative engine (Perplexity.ai) and reported visibility lifts up to ~37%	Same hedge: their sample, their year
Control	Keyword stuffing: little to no lift on the bench; worse than baseline on the live slice	Stop stuffing. Start attributing

Hedge hard. Those percentages are relative visibility inside GEO-bench and a smaller live slice (the paper describes 200 test samples with sources provided as files for the commercial-engine check). They are not “+40% organic.” They are not “+40% pipeline.” Engines, crawlers, and citation UX have moved since 2023–2024. Treat the direction as durable: evidence-bearing passages occupy more of a synthesized answer than keyword-padded ones. Treat the number as historical.

What the paper did not measure:

• Click-through from an Overview
• Lead quality
• Your domain in 2026 against a live, changing index
• Whether a vendor’s 0–100 “GEO score” predicts any of the above

I have been SEO-certified since 2021. The useful inheritance from that paper is the metric shift — share of the written answer — not a tactic pack you can paste into every CMS. For the operating system around entities, corroboration, and a 90-day loop, use the AEO playbook. This page stays on the label.

How do GEO, AEO, and SEO differ without three religions?

They are not three agencies. They are three questions you ask about the same site.

Question	SEO	AEO	GEO (as we use it)
What did the engine do?	Ranked a list of documents	Wrote or assembled an answer with sources	Same as AEO, on a generative product
What does “win” mean?	Position, impressions, clicks	Citation, accurate naming, share of voice	Inclusion inside generated text, with or without a chip
What do you ship?	Crawlable pages, links, intent coverage	Entities, fact packets, citeable passages, corroboration	The AEO stack, plus a log per generative product
What do you measure?	Rank, GSC, analytics	Prompt-panel citations and accuracy	Overview / chat inclusion on that same panel
What fails first?	You are not in the candidate set	You are retrieved and then skipped, or named wrong	Same failure, on a surface that writes prose

Practical rule: keep doing SEO. Layer AEO. Use “GEO” when the meeting is about Overviews, AI Mode, or chat-with-search. Do not rebuild the org chart around three logos that sell the same rewrite.

The AEO vs SEO spoke owns the scoreboard change (rank/CTR vs citation/accuracy) and Google’s “same crawl” line. This spoke owns the third acronym so it does not become a third budget line.

Decision list for the next planning doc:

1. One strategy narrative (AEO on top of SEO).
2. Three KPI columns (classic search / answer inclusion / generative-surface notes).
3. One roadmap. One owner.
4. Vendor tools sit under measurement, not under “new department.”

If a slide needs a Venn diagram, draw SEO as the crawl-and-authority circle, AEO as the inclusion circle, and GEO as a shaded slice of AEO. That picture is boring. Boring is the point.

What does Google say you can ignore?

Google named AEO and GEO in public and then told site owners not to build a second religion for Google Search.

The May 2026 page Optimizing your website for generative AI features on Google Search says terms like AEO and GEO are common online, and that many suggested “hacks” are not how Google Search works. For Google Search, the same guide says you can ignore:

Tactic vendors still sell	Google’s line (Google Search only)	What we do anyway
llms.txt and other “AI text files”	Google Search does not use them as a special door	Optional for other products; never a Google ranking lever
Artificial “chunking” into tiny pages	No requirement. Write for the audience	Keep sections stand-alone; do not explode one article into twelve stubs
Rewriting only for AI phrasing	Systems understand synonyms; do not chase every fan-out variant	Answer first for humans. That also compresses
Inauthentic mentions	Spam systems still apply; generative features depend on them	Earn real corroboration. Do not buy comment spam
Special schema.org for AI	Structured data is not required for generative AI search	Keep schema that matches visible text for rich results

Eligibility is still ordinary Search eligibility. Google’s AI features doc: to show as a supporting link in AI Overviews or AI Mode, the page must be indexed and snippet-eligible. No extra technical door. Overviews and AI Mode may use query fan-out — related searches in parallel — so a page can be pulled for a sub-question you never wrote as a title. That is a retrieval detail, not a license to publish a near-duplicate for every variant. The same optimization guide flags that pattern as scaled-content abuse when you do it to manipulate responses.

Scope the quote. “Still SEO” is a Google-Search sentence. ChatGPT Search is a different product. OpenAI’s ChatGPT Search help is the operator check: when search ran, you get inline citations and a Sources panel. No Sources control means the answer came from memory, not a live page. You cannot “GEO” your way into a training-weight hallucination the same way you GEO a retrieved URL.

• Quote Google only when the surface is Overviews or AI Mode
• Quote OpenAI only when the surface is ChatGPT Search
• Never paste a Google ignore-list into a ChatGPT statement of work

What do vendor GEO products actually measure?

This is where kickoffs go sideways. A tool ships a number. The slide titles it “GEO.” Finance treats it like rank.

Semrush. Semrush documents an AI Visibility Overview with an AI Visibility Score (0–100), mentions, citations, cited pages, and missing prompts. Their data explainer describes a prompt database they size at 317 million-plus prompts, covering ChatGPT, Gemini, Google AI Overviews, and AI Mode, with daily refresh on a rolling basis. They also describe the score as a mix of topic coverage and mention consistency. That is Semrush’s corpus and Semrush’s math. As of August 2026 it is a useful directional log if you already pay for the suite. It is not an industry standard. It is not your prompt panel unless you verify the prompts.

Surfer. Surfer publishes a GEO techniques guide and scores drafts inside the editor. Their Content Score docs split SEO Score (traditional on-page alignment) from AI Search Score (Facts Coverage + Upfront Intent Alignment). Hitting a high AI Search Score means the editor thinks you covered common facts and answered early. It does not mean ChatGPT cited you this week.

Search Console. Google’s Generative AI performance report tracks impressions in AI Overviews and AI Mode by page, country, device, and date. That is the official Google-surface column. It is not ChatGPT. It is not accuracy. It is not share of voice against a competitor set you chose. Rollout is still a subset of properties; if you do not see it, Google’s help page lists the usual reasons (not enough gen-AI impressions, or not in the rollout).

Tool	What it can tell you	What it cannot
Semrush AI Visibility	Directional mention/citation volume on their prompt set	That your buyer asked those prompts, or that the score is portable
Surfer AI Search Score	Whether a draft answers early and covers listed facts	Whether any engine will cite the URL
GSC Generative AI report	Official Overview / AI Mode impressions for your property	Other products, fact accuracy, or competitor SOV
Your frozen prompt panel	Whether your 25–40 questions name you this week	Statistical significance from one screenshot

Hedge every vendor claim that sounds like a guarantee. If a sales deck says “GEO tool #1” or “win AI mentions,” read the KB page for the metric definition. If the definition is missing, the number is decoration.

I will not put a Semrush or Surfer score in a client deck as proof of citation. I will put a dated prompt log with product, prompt, cited URL, and whether the brand was named. Tools can fill rows. They do not replace the log.

What changes on a page when the engine writes the answer?

Not the keyword tool. The unit of winning.

Generative systems retrieve, then compress. A page that ranks can still lose the sentence. The GEO-specific edits are the ones that survive that compression.

Answer in the first screen

Put the definition, recommendation, or decision in the first two paragraphs. Depth follows. Throat-clearing essays get summarized into nothing — or into a competitor’s sharper lead. Surfer calls this “upfront intent alignment.” You do not need Surfer to do it. Read the first 100 words out loud. If a colleague cannot repeat the take, rewrite.

Evidence the paper actually rewarded

The GEO methods that moved PAWC were not “more keywords.” They were statistics, quotations, and source citations. Practically:

Edit	Do this	Do not do this
Statistics	Number + unit + date + who measured it	“Fast,” “trusted,” “industry-leading”
Quotations	A named person or spec, in marks, with a source	Invented customer praise
Cite sources	Link the primary doc next to the claim	A bibliography nobody reads, unconnected to sentences

If you do not have a number, do not fake one. A dated “as of August 2026, we have not published a public benchmark” is cleaner than a decorative statistic. Fabricated stats get frozen into answers and then you spend a quarter unsticking them.

Stable, dated claims

Generated answers freeze sentences. If pricing, SLAs, or service areas change weekly with no date, you invite stale synthesis. Timestamp material claim changes on the page. Keep a fact sheet the CMS and the sales deck both read.

Stand-alone sections

Many systems retrieve chunks, not whole essays. Test: copy a random H2 block into a blank doc. If it cannot name the brand and the claim without the intro, rewrite.

• Put the answer next to a heading that restates the question
• Repeat the entity name near the commercial claim (“Spurlock Studios’ visibility audit includes…”)
• Keep tables simple — merged cells travel poorly
• Prefer “How GEO differs from AEO” over “The acronym problem”

Corroboration is still AEO

When two independent sources agree, synthesis gets bolder. That is not a GEO-only trick and it is not a Google “hack” if the mentions are real. Partner pages, docs, and earned coverage matter. Buying fake Wikipedia or comment spam is the inauthentic-mentions pattern Google already told you to skip.

Which generative surfaces deserve their own log?

Not every brand needs equal investment everywhere. Pick from the products your buyers actually open. Then log them separately. A page can win Overviews and lose chat (or the reverse). That is information, not failure.

Surface	Why it is a GEO surface	What you log	What you do not pretend
Google AI Overviews / AI Mode	Generated block on a SERP; citations are supporting links	GSC gen-AI impressions + manual Overview checks	That GSC is a ChatGPT report
ChatGPT Search	Inline citations + Sources panel when search ran	Prompt, date, named?, cited URL, Sources present?	That a memory answer is a page win
Perplexity	Citation-forward research UX	Same prompt row, separate product column	That their cite set equals Google’s
Copilot / Gemini	Depends on your ICP’s daily tools	Only if the ICP lives there	That one chat log covers all
Vertical assistants	Industry RAG over the web or partner docs	If a buyer-facing tool in your category exists	That a consumer chat panel substitutes

Build a prompt panel per surface you care about. Twenty-five to forty frozen questions beats a hundred rotating ones. Re-run weekly. One screenshot is an anecdote.

AI Overviews still live next to classic results. Technical SEO, snippet eligibility, and clear headings matter more. Semrush-style SERP features help here as a Google watch, not as a chat watch.

Chat products lean on multi-source synthesis and may cite niche docs Google underweights. Digital PR and docs-style pages punch above domain rating. That is why “we rank #1” is a weak GEO argument.

If you only have time for two products, pick the one your buyers use plus Google. I have watched teams burn a quarter instrumenting five chat apps their ICP has never opened. Measure the room you are already in.

How do you score a URL for generative readiness?

Before publish, score 0–2 on each row. This is a gate, not a vendor score.

Check	0	1	2
Answer in first 100 words	Buried or missing	Partial	A colleague can repeat it
Table or numbered method	Prose only	One list	One table or procedure a model can lift
Named entities	“We” / “the platform”	Brand once	Brand + product + category near the claim
Dated claims	Timeless adjectives	A year	Date + what changed
Evidence	No number, quote, or source	One, unsourced	Number or quote with a primary link
FAQ with real questions	None	Bolted-on fluff	Questions people ask, answers that stand alone
Internal link to the hub	Orphan	Footer only	In-body link to the pillar or comparison
Off-site corroboration plan	“Hope”	“Later”	Named targets or an explicit “none yet”

Below 10/16, revise. Surfer can flag topical gaps. It will not catch a missing ICP sentence or a fact that contradicts the About page.

Five-minute QA after the score:

1. Read only the first 120 words. Do they answer the query?
2. Delete the intro mentally. Does the first H2 block still name the brand and the claim?
3. Check every number against the fact sheet.
4. Confirm the primary CTA points at a real offer path — for this lane, /visibility.
5. Ask one AI product the target question after deploy. You are checking for disasters (wrong price, dead product name), not final KPIs. Expect delay.

Add a sixth step for comparison pages: would a skeptical buyer trust the criteria if your logo were removed? If the page only works as a brochure, it will not earn citations against a neutral roundup.

What does a four-week GEO sprint actually ship?

A sprint is a diagnostic, not a finished AEO program. Use it when you need to know whether generative inclusion is a content problem, an entity problem, or a corroboration problem.

Week	Ship	Exit test
1	Freeze 25 prompts across two generative products. Log who gets cited and whether you are named	You can show a table, not a vibe
2	Fix About / offer facts. Align Organization schema with visible text. Decide llms.txt as optional, not as a Google lever	One fact sheet; zero contradictions on money pages
3	Rewrite or ship 3 answer-first pages (definition, comparison, how-to) with evidence in the lead	Each page scores ≥10/16 on the gate above
4	Place or update 2 real corroborating mentions or document why you cannot. Re-run the same 25 prompts	Deltas written down. Next month’s owner named

That sprint will not finish AEO. It will tell you where to spend the next quarter. If week 1 already shows you named correctly on the prompts that matter, stop writing “GEO strategy” decks and go fix the two pages that lose.

Checklist you can paste into the ticket:

• Prompt list frozen (no silent swaps mid-sprint)
• Two products, not five
• Money-page facts match the fact sheet
• Three pages shipped, not twelve outlines
• Re-run on the same prompts
• Write the failure type: content / entity / corroboration / crawl

What breaks when GEO becomes a third agency?

The failure mode is organizational, not technical.

Three retainers, one rewrite. An SEO shop, an “AEO shop,” and a “GEO shop” produce three content calendars that collide on the same URLs. The About page gets three voices. Models retrieve the mess and pick the oldest clean sentence — often a competitor’s.

Dashboard theater. A vendor GEO score goes up because their prompt mix shifted, or because they added a product to the corpus. The board celebrates. Your frozen panel did not move. You now have two truths and no owner.

Google-only dogma. Someone pastes the ignore-list into a ChatGPT statement of work and refuses llms.txt, answer-first leads, and prompt logging because “Google said it is still SEO.” Google said that about Google Search. You just declined to measure the product your buyer uses.

Chat-only dogma. The inverse: the team abandons technical SEO because “GEO replaced it.” Then the page is not snippet-eligible, and Overviews cannot use it as a supporting link. You optimized for a chat screenshot and lost the SERP you still need.

Fake evidence. A writer adds “73% of operators” with no source because the paper said statistics help. The model repeats the fake number. You now own a hallucination you authored.

What it costs: a quarter of production, a contradictory entity story, and a measurement system nobody trusts. What you do instead: one program, three KPI columns, one prompt panel, vendor scores as optional rows.

Org myths to kill in week one:

• “GEO is a separate agency retainer forever.” — Usually it is an AEO program with generative KPIs.
• “We need to rewrite the whole blog.” — You need the missing question pages and cleanup of contradictions.
• “Citations are random.” — They vary. Gaps still cluster around weak entities and weak formats.
• “Only huge brands win.” — Niche operators with clear packets win niche prompts constantly.
• “A 90 on Surfer is a citation.” — It is a draft score.

When should you pause GEO work?

Pause net-new generative-targeted content if any of these are true:

Pause if	Because	Do this first
Fact packet still conflicts	Synthesis will pick a side, often the worst one	One fact sheet. Fix About, pricing, schema
Legal is mid-rebrand	You will stamp the old name into answers	Freeze publishes that assert identity
You cannot measure for 30 days	You will ship hope	Stand up the 25-prompt log
Key templates block crawlers	You are not in the candidate set	Robots, noindex, JS rendering, snippet eligibility
Nobody owns the prompt panel	Scores will rot in a slide	Name a human, not a tool

Fix foundations first. Generative optimization on a broken entity story accelerates the wrong narrative. I would rather a client spend two weeks on NAP and offer facts than eight weeks producing “GEO articles” that teach models the old price.

Unrealistic outcomes to take off the kickoff slide:

• Dominating every head-term recommendation nationally in 30 days
• Guaranteed Overview placement on competitive SERPs
• One viral post replacing entity hygiene
• A vendor score that substitutes for a prompt panel

Realistic for a focused brand that ships:

• Cleaner brand descriptions in chat
• Inclusion on a subset of category prompts where you are a true fit
• Fewer factual errors after truth-layer work
• A living prompt panel someone actually opens

How do you brief stakeholders without buying a new religion?

Finance will ask whether GEO is a new budget line. Treat it as a reallocation inside content, SEO, and PR with new KPIs — not a mystery vendor category. Show the three-column table. Show the prompt panel. Show one lost prompt and the URL that should have won.

Brand will fear “writing for robots.” Show an answer-first lead that a human would rather read. The GEO paper’s winning edits — numbers, quotes, sources — are the same edits a skeptical buyer wants. You are not translating into machine dialect. You are removing fog.

Sales will want inclusion on every head term tomorrow. Pick the ten prompts tied to open opportunities. Win those before you argue about national category queries you do not deserve yet.

Legal will ask about llms.txt and training opt-out. Separate the decisions. Training opt-out is not citation eligibility. Google says llms.txt is not a Search door. Other products may still read a well-made file. Do not sell it as a ranking lever. Do not refuse it as heresy. Decide per product, in writing.

Alignment in week one prevents a month of producing content nobody measures. If the room cannot agree which meaning of GEO they bought, stop the kickoff and write the sentence on a whiteboard.

I run visibility work this way because I have watched the acronym tax eat more calendar than the pages did. SEO certified since 2021; the crawl work did not get less important. The acceptance test on generative surfaces is inclusion in the written answer. Call that GEO if you want. Measure it like AEO. Keep shipping pages that can stand alone when a model keeps 60 words.

Do the paper’s tactics change by topic?

Yes — and that is the part vendor “GEO playbooks” flatten. Aggarwal et al. tagged queries and reported which methods helped which categories (their Table 3 in the preprint):

Method	Categories they reported as strongest	Operator translation
Cite Sources	Statement, facts, law and government	Put the primary next to the claim on spec and policy pages
Statistics Addition	Law and government, debate, opinion	A dated number beats another adjective on contested topics
Quotation Addition	People and society, explanation, history	Named voices help narrative and explainer queries
Authoritative tone	Debate, history, science	Tone helped some argumentative queries; it was not a general win
Fluency	Business, science, health	Cleaner prose helped. It is not a substitute for evidence

They also reported that lower-ranked sources in the retrieved set gained more from evidence-adding edits than the already-first result. That is interesting. It is not a promise that your page-four URL will leapfrog a category leader in ChatGPT Search in 2026. Their retrieved set was top-5 Google text in a 2024 harness.

Use the table as a bias, not a recipe:

• Factual / regulatory pages: cite the primary in the same paragraph as the number
• Opinion / comparison pages: criteria plus a dated statistic, or say you do not have one
• Founder / history pages: a real quote with a name beats a vibe paragraph
• Do not “authoritative-wash” a thin page and call it GEO

If your category is not in their tag list, run the four-week sprint and keep the method that moved your panel. Domain variation was one of the paper’s own conclusions. A cross-industry GEO checklist that ignores that sentence is marketing.

How do you log a GEO experiment without fooling yourself?

One change, one cluster, one log. Parallel “GEO experiments” on the same URLs make attribution theater.

Use a row like this:

hypothesis | URL | prompts affected | product | ship date | named before | cited before | named after 30d | cited after 30d | notes

Rules that keep the log honest:

Rule	Why
Freeze the prompt text	Silent rewrites create fake wins
One major on-page change per URL	You will not know whether the table or the PR mention moved it
Same product column	Overview ≠ ChatGPT Search ≠ Perplexity
30-day after, not next-day	Indexes and caches lag. Next-day is a disaster check, not a KPI
Record “named” and “cited” separately	A brand mention without a URL is a different win than a supporting link
Write the failure type	Content / entity / corroboration / crawl — or you will rerun the same sprint

Share the log with content and PR. If PR cannot see which mention was supposed to support which prompt, they will pitch vanity placements. If content cannot see which H2 got lifted, they will keep writing essays.

A vendor dashboard can sit next to this log. It cannot replace the before/after columns on your prompts. If the vendor score rose and your 25-prompt table did not, believe the table.

What should a comparison page do that a definition page should not?

Comparison prompts are where mid-market brands lose to content farms. A definition page can win with one clean lead and a table of criteria. A comparison page has to survive a model that will also retrieve the vendor docs on the other side.

Ship this structure, in this order:

1. Who each option is for (ICP, not slogans)
2. Mandatory capabilities (pass/fail, not vague adjectives)
3. Implementation burden (who has to operate it)
4. Cost posture you can defend (range or “ask,” never a fake average)
5. When to choose neither

Name competitors fairly when you must. Inventing strawmen backfires when retrieval also pulls their docs. If legal limits naming, compare approaches (“in-house scripts vs hosted automation”) with the same five rows.

Gate for comparison URLs:

• Criteria still make sense if your logo is removed
• Every numeric claim has a date and a source, or is marked as your opinion
• “When to choose us” is one section, not the whole page
• The first 100 words state the decision rule, not the brand story

Definition pages fail by burying the take. Comparison pages fail by being brochures. Generative engines are good at noticing the difference. So are buyers.

FAQ

What is GEO?

GEO means Generative Engine Optimization: improving how often and how accurately generative systems use your brand and content when they synthesize answers. The term comes from Aggarwal et al. (arXiv:2311.09735; KDD 2024). In our practice it is AEO scoped to generative products, not a third discipline.

How is GEO different from AEO?

AEO is the broader discipline of winning answer engines — citation, accurate naming, share of voice. GEO usually refers to the generative subset: Overviews, AI Mode, chat with search. Spurlock Studios plans them as one program. If a vendor treats them as separate retainers, ask what work would actually differ week to week.

GEO vs AEO vs SEO — which should we budget?

Budget SEO for crawl, indexation, authority, and classic discovery. Budget AEO/GEO for entities, citeable content, corroboration, and a prompt panel. Most teams underfund the second until competitors start showing up in ChatGPT. Do not budget a third line item that only buys a renamed dashboard.

Does GEO require different keywords?

It requires different questions and formats more than a new keyword tool. Map the questions buyers ask generative products, then build pages that answer them in compressable form with evidence in the lead. Keyword stuffing was the weak arm in the GEO paper. Do not revive it under a new logo.

Can we do GEO without schema and llms.txt?

You can start with content alone. Google’s AI-optimization guide says llms.txt and special AI schema are unnecessary for Google Search. Schema that matches visible text still helps rich results and entity clarity. llms.txt is cheap and may help non-Google products. Neither replaces answer-first pages or a prompt log.

How do Semrush and Surfer fit?

Semrush’s AI Visibility reports can watch mention and citation volume on Semrush’s prompt corpus. Surfer’s AI Search Score can pressure a draft to answer early and cover listed facts. Neither replaces a frozen multi-product prompt panel, and neither is a citation. Use them as optional rows under measurement.

CTA

GEO is not mystic. Generative engines retrieve, compress, and attribute. Make your facts clear, your passages quote-ready, and your corroboration boringly consistent — then measure the products your buyers actually use.

For the operating system, use the AEO playbook. To baseline generative visibility on your domain, see /visibility or book a visibility audit.