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By Abhilash Babbili · Last updated 19 May 2026

Acquire Pillar · GEO · AEO · LLMO

Your buyer asked ChatGPT a question. Your brand was not in the answer.

Generative Engine Optimization gets you cited inside ChatGPT, Claude, Perplexity, and Gemini. Answer Engine Optimization puts you in Google AI Overviews and featured snippets. LLM Optimization gets you into the seed corpus those engines pull from. Three layers, one job: be the brand named when someone prompts the question your customer is already asking.

5 engines
ChatGPT, Claude, Perplexity, Gemini, AI Overviews
30-50
Queries tracked monthly
4-8 wks
First citations on niche queries
Entity + Schema
Foundation layer fixed first
[ 01 / What is included ]

Six pieces of the AI visibility stack, built in order.

You cannot prompt your way into ChatGPT citations. The work is concrete: entity layer, schema, citable writing, presence in the corners of the web LLMs read from.

1

Citation audit

30-50 buyer prompts run across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Baseline report: where you are cited, where competitors are, what is missing. The starting line.

2

Entity disambiguation

Wikidata entry, Google Knowledge Panel, Organization and Person schema, sameAs links across LinkedIn, Crunchbase, GitHub, Wikipedia (where eligible). LLMs need to know who you are before they cite you.

3

Citable content rewrite

Top 20-30 pages rewritten for LLM citation. Short factual answer up top, deeper section below, comparison tables, named-entity coverage, source links. Different from SEO content, on purpose.

4

Seed-corpus presence

Reddit, Quora, GitHub, Hacker News, niche subreddits, industry forums - the corners LLMs hoover up. Real contributions on your topic, not spam, in places where your customer asks questions.

5

Structured data layer

FAQ, HowTo, Product, Service, Article, Organization, Author schema on every key page. Validated with Schema.org and Google Rich Results tester. The machine-readable layer matters more for AI than for Google now.

6

Monthly engine tracking

Same 30-50 queries run each month, delta logged: gained citations, lost citations, new competitors named, which engine surfaces which page. Friday WhatsApp summary with the screenshots and the trend.

[ 02 / Process ]

How AI visibility actually gets built.

01 · MAP

Define the prompts that matter

The 30-50 queries your customer types into ChatGPT before they pay. Run each across 5 engines, log who is cited, who is not, with which source link. The baseline document is the brief.

02 · FIX FOUNDATIONS

Entity, schema, sources

Wikidata, Knowledge Panel, schema layer, sameAs network, factual brand pages. The plumbing. Boring, but every citation rests on this.

03 · SEED

Place citable content where LLMs read

Long-form on your domain (rewritten for citation), genuine contributions on Reddit, Quora, GitHub, niche forums. PR placements on sites the LLMs trust. No spam, no AI-generated junk - that gets discounted fast.

04 · TRACK + ITERATE

Monthly engine sweep

Same query set re-run every month. The delta tells you what is working. Double down on the queries you are starting to win, ignore the ones that are not moving.

[ 03 / Comparison ]

SEO vs. AEO vs. GEO / LLMO vs. paid ads.

What mattersSEOAEOGEO + LLMOPaid ads
Where the buyer is searchingGoogle results pageGoogle AI Overviews, snippets, PAAChatGPT, Claude, Perplexity, GeminiGoogle + Meta paid placements
Click or zero-clickClick-drivenMostly zero-click, brand mentionZero-click, brand and link citedClick-driven
Time to first result3-6 months2-3 months4-8 weeks on niche queriesSame day
Compounds when you stopYesYesYesStops with budget
What it growsTrafficBrand mentionsBrand mentions + authority signalTraffic
Ongoing costContent + tech debtSchema + content polishContent + corpus seedingMonthly bleed
[ 05 / Engagement ]

Three ways to start.

Citation audit

~1 week

30-50 buyer prompts run across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Written baseline showing where you are cited, who is cited instead, and the 5 highest-ROI fixes you can ship yourself.

Foundation sprint

6-8 weeks

Entity layer fixed, schema across all key pages, top 20-30 pages rewritten for citation, first round of seed-corpus contributions placed. Re-audit at the end to show what moved.

Retainer

ongoing

Monthly engine sweep with a delta report. New citable content shipped each month. Ongoing seed-corpus presence. Response to algorithm shifts (Google AI Overviews changes, OpenAI's web index updates, Perplexity ranking tweaks).

[ 06 / FAQ ]

The questions every founder asks before paying for this.

GEO (Generative Engine Optimization) is getting your brand cited inside generative answers from ChatGPT, Claude, Perplexity, Gemini, Copilot. AEO (Answer Engine Optimization) is appearing in answer boxes like Google AI Overviews, featured snippets, and People Also Ask. LLMO (Large Language Model Optimization) is the long game of being part of the training and retrieval corpus LLMs draw from: Wikipedia, Common Crawl, Reddit, high-authority publications. They overlap, and a real engagement covers all three.
Because more B2B research, product comparison, and high-intent purchase prep now starts with an AI prompt instead of a Google search. Gartner predicts 25% of search traffic moves to AI by 2026. If your competitor is named and you are not, the buyer never reaches your site. The cost of zero presence here compounds quickly.
A defined query set of 30-50 prompts your customer would realistically type, run across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews monthly. Each run logs: was your brand mentioned, in what position, with what source link, against which competitors. Tools like Profound, Otterly, and SE Ranking AI Trackers help, plus manual checks. The delta month over month is what I ship to you.
Real, but young. The fundamentals - entity disambiguation, schema, citable content, seed corpus - are not new. What is new is that the same fundamentals now drive LLM citation, not only Google ranking. Agencies selling Rs. 5L sprints on it are mostly running hype playbooks. The underlying work is concrete and measurable.
Partially. Good SEO foundations help: clean content, schema, fast pages, real backlinks. But LLMs cite differently than Google ranks. They prefer clear factual claims, comparison tables, named-entity coverage, source-cited paragraphs, and presence on Reddit, Quora, Wikipedia, and news sites. Your SEO content often needs a rewrite layer for citation, not a replacement.
First citations on niche, low-competition queries within 4-8 weeks of foundation work. Broader category queries take 3-6 months because LLMs refresh their retrieval indexes on a delay. Perplexity and Google AI Overviews update fastest (live retrieval). ChatGPT and Claude with web search update within days, without it on a months-long delay tied to model retraining.

Send me 10 prompts your buyer would type into ChatGPT.

I will run them across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews and reply within 24 hours with a short report: which ones cite you, which cite competitors, and the three highest-ROI fixes for your domain. No sales call needed.