Ranking in AI search comes down to 5 things: existing rankings, entity clarity, third-party mentions, liftable content, and freshness. Work them in that order.
"Ranking" in AI search means being the business an AI assistant names when someone asks who to hire, or the source it cites when someone asks a question. There is no blue-link list. The assistant answers, and either you are in the answer or your competitor is.
The 5 factors that decide AI recommendations
1. Classic rankings still feed the machine. ChatGPT search, Gemini and AI Overviews all retrieve from search indexes. If you rank top 10 for "hvac repair boise", you are in the retrieval pool. If you are on page 5, no AI layer can save you. SEO first.
If you are on page 5 of Google, no AI layer can save you. SEO first.
2. Entity clarity. Models need to know exactly who you are: same business name, address, phone and services everywhere: your site, Google Business Profile, directories, social profiles. Conflicting facts make models hedge, and hedging models skip you.
3. Third-party mentions. Assistants weigh what others say about you: reviews, local news, directories, community threads. A brand that only talks about itself on its own site is a weak signal. This is the layer most local businesses have never built.
4. Liftable content. Direct answers under question-style headings, real numbers, FAQ schema. Engines quote passages: give them passages worth quoting.
5. Freshness and consistency. Updated pages, active GBP, recent reviews. Stale sites read as closed businesses to a model deciding what to recommend.
The 90-day plan
Days 1-30: fix the foundation. Rank audit, entity cleanup (NAP consistency everywhere), schema on every page, llms.txt, unblock AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended).
Days 31-60: restructure your top 10 money pages for liftability: question H2s, first-sentence answers, FAQs with schema. Start the review engine.
Days 61-90: build mentions: local directories, trade associations, guest content, local press. Then benchmark: ask each engine your money questions and log who gets named.
What this looks like when it works
We track AI citations for clients the way we track rankings. One client sits at 740+ brand mentions across ChatGPT and Gemini with 2,400 AI-cited pages, built on exactly this sequence: rankings, entity, mentions, liftable content.
The three service layers behind it: AI SEO for the full program, answer engine optimization for citations, and generative engine optimization for the model-learning layer. Or start with the free audit and see where you stand today.
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