How AI Decides Who to Recommend: The Ranking Factors Behind Every AI Answer

Someone asks ChatGPT: "What's a good moisturizer for dry skin?"

ChatGPT recommends three brands. Yours isn't one of them.

Why? Not because your product is worse. Not because you have fewer customers. But because AI evaluated dozens of signals about your brand and your competitors, and they scored higher.

The thing is, this isn't random. It's not a popularity contest. There's an actual process. And once you understand it, you can reverse-engineer exactly what needs to change to get your brand into those recommendations.

Let's break down how AI actually decides.

The Two-Phase Process

Every AI recommendation happens in two phases. Understanding both is critical.

Phase 1: Retrieval

Before AI can recommend anything, it needs to find relevant content. This is the RAG (Retrieval-Augmented Generation) process we've covered before, but let's look at it specifically through the lens of ranking.

When someone asks "best moisturizer for dry skin," AI doesn't search its memory for an answer. It actively searches the web (or its indexed content) for pages that match this query.

What determines if YOUR page gets retrieved?

Topic relevance. Does your page actually discuss moisturizers for dry skin? Not just moisturizers in general, but specifically for dry skin? The more precisely your content matches the query, the more likely it gets pulled.

Content quality signals. Is the page comprehensive? Well-structured? Recently updated? AI filters out thin, outdated, or poorly organized content at this stage.

Crawl accessibility. Can AI actually read your page? If your content is behind JavaScript rendering that crawlers can't execute, paywalled, or blocked by your robots.txt, you're invisible. Can't rank if you can't be found.

Think of Phase 1 as the audition. You either make it to the callback or you don't. Most websites fail here. They simply never get retrieved because their content doesn't match what AI is looking for, or AI can't access it.

Phase 2: Ranking and Selection

This is where it gets interesting. AI has retrieved maybe 10-20 relevant pages. Now it needs to decide: which ones to cite? Which brands to recommend? In what order?

This is where the real ranking factors come in.

The 8 Ranking Factors AI Uses

Based on how current AI systems work, ChatGPT, Perplexity, Google AI Overviews, Claude, here are the factors that determine who gets recommended and who gets skipped.

1. Direct Answer Quality

Weight: Very High

The single most important factor. Does your content directly, clearly answer the user's question?

AI is looking for content that it can extract a clean, useful answer from. If someone asks "what's the best moisturizer for dry skin?", AI wants to find a page that says something like:

"For dry skin, look for moisturizers with hyaluronic acid and ceramides. CeraVe Moisturizing Cream is a dermatologist-recommended option that contains both, works for sensitive skin, and costs around $16 for 19oz."

That's a direct, specific, useful answer. AI can grab that, cite it, and the user is happy.

Compare to: "Our moisturizer is amazing and perfect for all skin types! Experience the luxury of our premium formula. Click to learn more about why thousands love our products."

AI can't extract a useful answer from that. It's marketing copy, not information. Skip.

How to win: Write content that answers questions with specific, factual, useful information. Lead with the answer, then elaborate. Structure your product data clearly.

2. Entity Authority

Weight: High

AI doesn't just evaluate content. It evaluates the source. Who are you? What's your track record? Are you a credible authority on this topic?

This is the entity profile concept. AI builds a model of who your brand is, what you're known for, and how trustworthy you are.

Factors that build entity authority:

• Consistent brand information across the web (same name, description, details everywhere)
• Third-party mentions (press, industry sites, directories mentioning your brand)
• Complete Organization schema telling AI who you are
• Author credentials for content (real people with real expertise)
• Business history (how long you've been around, customer base)

A no-name store with no web presence outside its own website has weak entity authority. AI isn't confident recommending it. A brand that's mentioned across industry publications, has complete business information, and has been around for years scores much higher.

How to win: Build your entity presence. Complete your About page, add Organization schema, get listed in industry directories, ensure consistent brand information across all platforms.

3. Social Proof and Reviews

Weight: High

AI weighs what other people say about you heavily. This is the digital equivalent of "word of mouth."

The signals:

• Aggregate rating (4.5 stars from 500 reviews >> 4.9 stars from 3 reviews)
• Review volume (more reviews = more confidence)
• Review recency (recent reviews matter more)
• Review specificity (detailed reviews provide more data)
• Third-party reviews (Trustpilot, Google Reviews, independent review sites)

When AI is choosing between two similar products, reviews often break the tie. The product with 2,000 detailed reviews that mention specific use cases gives AI much more confidence than the product with 15 generic reviews.

How to win: Build your review ecosystem. Encourage detailed reviews, respond to them, maintain profiles on third-party platforms, and implement proper review schema markup.

4. Content Freshness

Weight: Medium-High

AI notices dates. Content that was last updated in 2023 raises a flag. Is this still accurate? Are these products still available? Have prices changed?

Freshness signals include:

• dateModified in schema markup (the most direct signal)
• References to current dates/events in the content
• Recent reviews and user-generated content
• Active sitemap with recent lastmod dates

This doesn't mean you need to rewrite everything monthly. But your important pages should be reviewed and updated regularly. Even small updates (refreshing a date, adding a new data point, updating a price) signal that the content is maintained.

How to win: Set a quarterly review schedule for your top pages. Update dateModified in your schema. Keep product information current. Update your blog posts with fresh data.

5. Structured Data Completeness

Weight: Medium-High

Schema markup is how you give AI machine-readable data about your pages. The more complete your structured data, the easier it is for AI to understand and recommend you.

A product page with complete schema gives AI:

• Exact product name, description, category
• Price, currency, availability
• Brand, manufacturer, SKU
• Aggregate ratings and review counts
• Images with descriptions

A product page without schema forces AI to parse all of this from raw HTML. Sometimes it works, often it doesn't. Key details get missed.

Beyond Product schema, FAQ schema gives AI ready-made Q&A pairs to cite. Article schema helps with blog content. Organization schema builds entity authority.

How to win: Implement complete Product schema on all product pages, FAQ schema on key pages, Article schema on blog posts, Organization schema sitewide. Run a Recomaze audit to see exactly what's missing.

6. Content Depth and Coverage

Weight: Medium

AI prefers comprehensive sources over shallow ones. If you cover a topic in 200 words and a competitor covers it in 2,000 words with specifics, comparisons, and data, the competitor wins.

But this isn't about word count. It's about coverage. Does your content address the topic thoroughly? Does it cover different angles, use cases, edge cases?

Signals of depth:

• Multiple relevant headings covering different aspects
• Specific data points (numbers, measurements, comparisons)
• Tables and structured comparisons
• Addressing different user needs within the topic
• Original insights not just repeated from other sources

How to win: When you write about a topic, cover it properly. Include specifications, comparisons, use cases, and practical advice. Don't pad with fluff, but don't leave obvious gaps either.

7. Site Technical Health

Weight: Medium

AI crawlers have limits. If your site is slow, returns errors, has broken links, or is poorly structured, AI can't effectively crawl and index your content.

Technical factors:

• Page load speed (slow pages may get abandoned mid-crawl)
• Clean HTML structure (semantic elements, proper heading hierarchy)
• Working internal links (no 404s, logical structure)
• Mobile responsiveness (AI increasingly crawls mobile versions)
• Crawl accessibility (proper robots.txt, no accidental blocks)

You don't need a perfect PageSpeed score. But significant technical issues can prevent AI from fully understanding your site.

How to win: Fix broken links, ensure clean page structure, check that AI crawlers can access your important pages, maintain logical internal linking.

8. Topical Relevance Clustering

Weight: Medium

AI doesn't evaluate pages in isolation. It looks at your entire site to understand what you're an authority on.

If you sell running shoes and have:

• 50 product pages for running shoes
• 15 blog posts about running
• Comparison guides for different shoe types
• FAQ sections about running shoe selection

AI builds a strong "this site is an authority on running shoes" signal. Your running shoe recommendations carry more weight.

But if you sell running shoes, gardening tools, phone cases, and kitchen appliances with thin content across all categories, AI doesn't see you as an authority on anything specific.

How to win: Build content clusters around your core topics. Multiple pages covering related aspects of the same topic reinforce each other. A well-linked content hub with supporting pages is more powerful than scattered, unrelated content.

How These Factors Interact

These factors don't work in isolation. They multiply each other.

Strong content + weak entity = okay. AI might cite your content but not recommend your brand specifically.

Strong entity + weak content = missed opportunity. AI knows who you are but can't find good content to cite.

Strong content + strong entity + good reviews = winner. AI has everything it needs to confidently recommend you.

Think of it as a scoring system where each factor contributes to an overall confidence score. AI recommends the sources it's most confident about. Every weak factor pulls your score down.

The Competitor Gap Analysis

Here's a practical exercise. Pick the top 3 queries you want AI to recommend you for.

Ask ChatGPT, Perplexity, and Google AI Overviews each query. Note who gets recommended.

Now evaluate the recommended brands against the 8 factors:

• Is their content more directly answering the question?
• Do they have a stronger brand presence online?
• More and better reviews?
• Fresher content?
• Better structured data?
• Deeper topic coverage?
• Better technical setup?
• Stronger topical authority?

This tells you exactly where the gap is. Usually it's 2-3 specific factors, not everything. Fix those and you close the gap.

What AI CAN'T See (But People Think It Can)

Let's clear up some myths:

AI can't see your ad spend. Spending more on Google Ads doesn't influence AI recommendations. Zero correlation.

AI can't see your social media followers. Having 100K Instagram followers doesn't directly make AI recommend you. (Though the content you create there can be indexed.)

AI can't see your revenue or sales volume. A bigger company doesn't automatically rank higher. Small brands with better content and data absolutely can outrank large ones.

AI doesn't care about your domain age. A 2-year-old site with excellent content beats a 15-year-old site with outdated pages.

AI doesn't count backlinks like Google does. Traditional link building is less relevant. What matters is overall web presence and authority signals.

This is actually great news for smaller businesses. The playing field is more level than traditional SEO. You don't need a massive budget or decades of domain authority. You need great content, complete data, and strong signals.

The Priority Matrix

Not sure where to start? Here's how to prioritize based on impact and effort:

High Impact, Low Effort (Do First):

• Add FAQ schema to your top pages
• Complete your Product schema (price, availability, reviews)
• Update stale content with current dates and info
• Fix broken internal links

High Impact, Medium Effort (Do Next):

• Rewrite product descriptions to be factual and specific
• Build out your About page with verifiable facts
• Set up review collection and response system
• Create comparison content for your top products

High Impact, High Effort (Plan For):

• Build comprehensive content hubs around core topics
• Develop a regular content update schedule
• Build external entity signals (directories, press, mentions)
• Create detailed buying guides for each product category

Low Impact (Skip For Now):

• Obsessing over exact keyword placement
• Building backlinks specifically for AI
• Creating content on topics outside your expertise
• Technical micro-optimizations (beyond the basics)

Testing and Iteration

GEO isn't a one-time project. It's an ongoing process. Here's how to track progress:

Monthly: Ask AI your target queries. Document who gets recommended. Track changes over time.

Quarterly: Run a Recomaze audit to measure your technical AI readiness. Compare scores.

After major changes: Wait 2-4 weeks for AI to recrawl and reindex, then test again.

Track the pattern: You'll likely see incremental improvement. First, you might get mentioned in longer responses. Then you start appearing in direct recommendations. Then you become the first recommendation.

The Compound Advantage

Every factor you improve makes every other factor more effective.

Better content gets more reviews. More reviews build entity authority. Stronger entity authority makes content more trustworthy. More trustworthy content gets cited more. More citations build more authority.

This is why the brands that dominate AI recommendations seem to dominate completely. They've built a flywheel where each factor reinforces the others.

The good news: this flywheel works for you too, once you start spinning it. The brands currently winning didn't always win. They just started optimizing earlier.

Start now. Every improvement compounds.

See how you score across all 8 factors - free Recomaze audit checks your structured data, content quality, entity signals, and overall AI readiness. Takes 2 minutes.