Train AI search engines to recommend your brand, not ignore it.
The AI Visibility Playbook shows you exactly how ChatGPT, Perplexity, Gemini, and Google AI Overviews decide who gets recommended, and the 6-phase system to make sure it's you.
- The 40 to 60 word citation block formula
- llms.txt + AI crawler access setup
- 30 to 40% lift in AI citations
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Brands getting found with 1stContact.ai
The currency shift
Old SEO is failing. GEO and AEO are the new currency.
Keywords and backlinks got you ranked on a page of blue links. AI engines don't show pages, they show answers. Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) build the undeniable digital entity AI models need to identify, validate, and recommend you.
Old SEO
- Stuff keywords and chase backlinks
- Optimize for blue-link rankings
- Hope crawlers infer what you do
- Measure clicks, not recommendations
New GEO / AEO
- Build an undeniable digital entity
- Optimize for AI answer extraction
- Hand AI a canonical anchor statement
- Measure AI share of voice and citations
How AI engines choose who to recommend: the 3-step process
Entity Identification
AI models match your brand against training weights and their live retrieval index. No clear entity, no recommendation.
Fact Validation & Verification
They cross-check your claims against third-party consensus: reviews, listicles, and Reddit. No consensus, no trust.
Passage Extraction & Recommendation
They lift a structured, direct-answer passage and recommend it. No clean passage, no citation.
What's inside
The 6-phase system to get recommended by AI
14 pages of practical, no-fluff strategy you can apply this week, built on the exact framework 1stContact.ai uses to make brands visible inside ChatGPT, Perplexity, Gemini, and Google AI Overviews.
Establish Your Canonical Digital Entity
Craft a one-sentence anchor statement and deploy Schema.org JSON-LD so every AI model reads the same, unambiguous definition of who you are and what you do.
Technical Accessibility & Crawl Optimization
Open your site to GPTBot, PerplexityBot, ClaudeBot, and Google-Extended in robots.txt, and publish an llms.txt file so AI crawlers can reach and trust your content.
Direct-Answer On-Page Architecture
Structure pages around the 40 to 60 word citation block strategy, using BLUF (Bottom Line Up Front) passages that AI engines extract verbatim and recommend.
High-Trust Third-Party Authority Signals
Earn consensus across Top 10 listicles, Reddit and community sentiment, and consistent G2 and Capterra reviews so AI models can validate your claims independently.
Prompt Intent Mapping
Map your content to the Awareness, Consideration, and Decision prompt funnel so you get cited at every stage of a buyer's AI-assisted research journey.
Auditing & Tracking AI Share of Voice
Run a monthly visibility audit log, measure your AI share of voice, and correct hallucinations so your brand stays accurate and recommended over time.
- Write the exact 40 to 60 word passages AI engines lift verbatim
- Configure robots.txt and llms.txt so AI crawlers trust your site
- Map your content to the prompts buyers actually ask ChatGPT
- Run a monthly audit that proves your AI share of voice is growing
Feature deep dive
Two breakthrough frameworks that move the needle
These are the tactics most brands miss entirely. Master them and you give AI engines exactly what they need to cite you over a competitor.
The 40 to 60 Word Citation Block
AI engines don't paraphrase, they extract. The playbook teaches you the BLUF (Bottom Line Up Front) formula: a self-contained 40 to 60 word passage that answers a prompt directly, with your brand and key facts baked in.
The result
Brands using this formula see a 30 to 40% lift in AI search citations within 30 days.
The llms.txt Strategy
robots.txt tells crawlers where they can go. llms.txt tells large language models what to read, how to describe you, and what to cite. It's the difference between AI guessing and AI knowing.
The result
A controlled, accurate brand summary that ChatGPT, Perplexity, and Claude pull verbatim instead of scraping random pages.
lift in AI citations with the citation block formula
to a fully AI-recommendable digital entity
to score your AI readiness with the included checklist
Bonus access
More than a playbook. A head start.
Every download ships with the tools you need to move this week, not next quarter.
The 10-Minute AI Readiness Action Checklist
A fast, no-jargon scorecard that tells you exactly where your brand stands with AI search today and the first three moves to fix it.
Free AEO Scanner
Audit any website for Answer Engine Optimization readiness. See how AI search engines read your site right now and what to fix first.
Try the AEO ScannerPowered by 1stContact.ai
The all-in-one AI CRM that helps you act on everything in the playbook, from follow-up to closing the leads AI sends you.
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Frequently asked
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is the practice of structuring your brand's digital presence so AI search engines like ChatGPT, Perplexity, and Google AI Overviews can identify, validate, and recommend your business. GEO replaces keyword chasing with entity authority, structured data, and direct-answer passages that AI models extract and cite.
How do I get ChatGPT and Perplexity to recommend my business?
To get ChatGPT and Perplexity to recommend your business, build a canonical digital entity with a one-sentence anchor statement and Schema.org markup, allow AI crawlers in robots.txt, publish 40 to 60 word direct-answer blocks, and earn third-party consensus through reviews, listicles, and community sentiment that AI models can verify independently.
What is an llms.txt file and why does my website need one?
An llms.txt file is a standardized markdown document that tells large language models which pages to read, how to describe your brand, and what facts to cite. Your website needs one because it gives ChatGPT, Perplexity, and Claude a controlled, accurate summary of your business instead of letting them guess from random pages across your site.