GEO Examples: 7 Before-and-After Rewrites (With Evidence)

A GEO example is a before-and-after rewrite: the same passage, edited so a generative engine can lift a correct, attributable answer from it. Below are seven patterns with the evidence we could verify for each. The best-supported moves add sourced statistics, citations and quotations, and write plainly.

Every before-and-after box is an illustrative rewrite we wrote for a made-up invoicing app, "Northwind Invoicing." The brand and prices are invented. They are not client results, and we claim no rewrite "got cited," because we have no controlled test showing that. The Pew figures in pattern 2 are the only real data in the boxes.

What counts as a GEO example, and what doesn't?

A real GEO example changes what a page says or how it is presented, and also helps a human skimming it. If an edit only suits a model, skip it. Google's July 2026 guide says you don't need to write in a specific way just for generative AI search.

Generative engine optimization (GEO) is the practice of editing content so generative search engines include and cite it. The term comes from Aggarwal et al.'s 2023 paper, which found keyword stuffing, the classic SEO tactic, gave little or no improvement, and scored below the unmodified page on Perplexity.ai.

We agree: every pattern below is plain good editing, and what the paper rewarded was content, not tricks.

What are the 7 before-and-after patterns?

Each pattern swaps a vague or buried passage for one an engine can quote. Our GEO guide covers the theory.

1. How does an answer-first rewrite look?

It leads with the conclusion and the condition that makes it true, so the answer arrives before the caveats.

Before: "Choosing invoicing software can feel overwhelming, and there are many factors to weigh, including budget and team size."

After: "Freelancers sending under 20 invoices a month should pick a flat-fee tool with recurring invoices; per-seat suites only pay off once several people send invoices."

The paper found readability and fluency edits alone lifted visibility by 15–30% on its test engine.

2. What does a sourced statistic add?

It turns an unverifiable claim into a fact an engine can attribute. On GEO-bench, a 10,000-query benchmark, adding statistics, citations or quotations each lifted visibility by 30–40% on the paper's main metric.

Before: "AI summaries are costing publishers a lot of clicks."

After: "In Pew Research Center's March 2025 browsing data from 900 U.S. adults, people clicked a traditional result in 8% of visits with a Google AI summary versus 15% without one."

One limit: gains skewed to lower-ranked pages. Cite Sources raised rank-5 sources by 115% but cut rank-1 sources by 30%. And the statistic must be real, dated and linked.

3. When does a comparison table beat prose?

When the reader is comparing the same attributes across options. Each cell becomes a self-contained fact, and people scan it faster.

Before: a 200-word paragraph describing three plans, their prices and their support.

Plan	Price	Invoices per month	Support
Starter	$12	20	Email
Studio	$29	200	Email and chat
Agency	$79	Unlimited	Phone

The evidence is thin: no engine documents a preference for tables, and Google says there is no requirement to break content into tiny pieces. Use tables because readers compare.

4. How do you clarify who the entity is?

State what the product is, who makes it and who it is for, using one name everywhere, then mark up the same facts. Entity linking is the task of assigning a unique identity to a named thing, and an ambiguous name makes it harder.

Before: "Northwind helps teams get paid faster." (Elsewhere: "Northwind Co.")

After: "Northwind Invoicing is an invoicing app for freelancers and small studios, made by Northwind Software Ltd."

{ "@context": "https://schema.org", "@type": "Organization",
  "name": "Northwind Software Ltd", "url": "https://northwind.example",
  "sameAs": ["https://www.linkedin.com/company/northwind-example"] }

Google says Organization markup on your home page can help disambiguate your organization; schema.org defines sameAs as a page that unambiguously indicates identity. In AEOeye's crawler access study (October 2026), 219 of 312 readable homepages (70.2%) already had Organization schema, so the usual gap is inconsistent naming.

5. How should FAQ pairs be written?

As questions a buyer would type, each answered completely in 40–60 words, with the number inside.

Before: "Pricing: contact us for details."

After: "How much does Northwind Invoicing cost? Plans start at $12 per month for up to 20 invoices, as of October 2026."

Don't do it for the markup. Google's changelog says the FAQ rich result stopped appearing in Google Search on May 7, 2026, and its generative AI guide says no special schema.org markup is needed. The visible answer is the asset. In our study only 34 of 312 homepages (10.9%) carried FAQPage schema; aeoeye.com does, because it is cheap, not because we have seen it earn citations.

6. Why should you date what can go stale?

A visible "as of" line and a matching modified date separate a current price from a leftover one.

Before: "Plans start at $12 a month."

After: "As of October 2026, plans start at $12 per month, billed monthly."

Dates do move models. In one study, adding artificial publication dates shifted a reranker's top-10 forward by up to 4.78 years across seven LLMs, using TREC passages rather than live engines. So never bump a date without changing the content. Google asks that dates match between visible text and structured data and reflect real publication or updates.

7. What makes a definition quotable?

One self-contained sentence that names the term, says what it is and is readable with no surrounding paragraph. See what makes content quotable by AI for the full anatomy.

Before: "GEO is a newish approach lots of people are talking about."

After: "Generative engine optimization (GEO) is the practice of editing content so generative search engines include and cite it in their answers. The term was introduced by Aggarwal et al. in 2023."

Expert quotes follow the same logic: in the paper, Quotation Addition scored highest. Quote only real, named people, and never invent one.

Which pattern helps which engine?

Nobody can honestly say. No engine publishes its selection logic, and the strongest experiment we found ran on a GPT-3.5-turbo research engine plus Perplexity.ai, not today's ChatGPT, Gemini or Claude. The table shows what each pattern rests on.

Pattern	Best evidence	What it does not show
1. Answer-first	GEO paper: readability edits (related) +15–30%	No per-engine result
2. Sourced statistic	GEO paper: +30–40%	Weak for top-ranked pages
3. Table	None direct	Untested
4. Entity clarity	Google Organization docs	No cross-engine test
5. FAQ pairs	Google: no special schema	AI-answer effect unproven
6. Dates	Recency-bias study	Lab rerankers, not live engines
7. Definition, quote	GEO paper: quotes strongest	Effect varies by domain

Fix access first: sites opted out of OAI-SearchBot are not shown in ChatGPT search answers, and a Google page must be indexed and snippet-eligible, with no additional technical requirements.

How do you apply the patterns to your site?

Start with the pages answering your ten key buyer questions, and change one pattern per page so you can tell what mattered. Our content optimization guide has the wider checklist.

1. Confirm access. Check robots.txt and CDN logs. In our study 1 of 193 SaaS sites blocked an AI retrieval bot, but 24 of 88 e-commerce homepages challenged our self-identified crawler.
2. Record a baseline for each question before you edit.
3. Apply patterns 1, 2 and 7 first, the cheapest and best supported.
4. Add 4 and 6 sitewide; use 3 and 5 only where content is tabular or Q&A.
5. Refuse shortcuts. No invented statistics, quotes or dates. Google advises a unique point of view, not recycled facts.

How do you test whether a rewrite worked?

Ask each buyer question several times before and after, and compare how often your brand is named, not where it ranks. One answer proves nothing; these systems vary run to run.

SparkToro's test (600 volunteers, 2,961 runs in late 2025, run with an AI-tracking vendor) found under a 1-in-100 chance of the same brand list twice and about 1-in-1,000 for the same order. In AEOeye's recommendation benchmark, a small, self-selected set of 127 audits, brands were named in 157 of 892 answers (17.6%), and 71.4% of 147 ranked mentions were first. Being named at all is the hard part; its per-engine rates are not comparable, so we don't rank engines.

A protocol you can run yourself:

• Use 10 unbranded buyer questions, each run at least 5 times per engine.
• Log named or not, and which competitors appear instead.
• Change one pattern, wait for engines to refetch, then repeat the identical runs.

For a baseline, AEOeye's free audit asks three unbranded buyer questions on ChatGPT and shows the full answers. Our measurement guide scales the same method.