5 Things AI Assistants Look For Before Recommending a Product

Every day, millions of consumers ask AI assistants to help them make purchase decisions.

"What's the best espresso machine under $500?"

"Which running shoes are best for plantar fasciitis?"

"Is the Casper mattress worth it?"

And every time, the AI has to make a choice. Out of thousands of possible products and retailers, which ones deserve a recommendation? Which ones get named in the response? Which ones get the citation — and the click?

It's not random. AI assistants follow patterns. After analyzing 30 retail product pages across 150 real shopping queries, we identified five things that consistently separate the brands AI recommends from the ones it ignores.

1. Structured Product Information That AI Can Actually Read

This is the foundation. If AI can't understand your product data, nothing else matters.

AI assistants don't see your product page the way a human does. They don't admire your hero image or feel the emotional pull of your brand story. They read the underlying data — the HTML, the metadata, and most importantly, the structured markup.

Schema markup (specifically JSON-LD) is the language that tells AI exactly what your product is, what it costs, what its specifications are, and how it relates to other products. Without it, AI is guessing. With it, AI has a structured, reliable data source it can cite with confidence.

What good looks like:

- JSON-LD Product schema with complete attributes (name, price, description, brand, availability, SKU)

- Detailed product specifications in organized formats

- Clear product categorization

- Complete and accurate pricing information

- Image alt text that describes the product, not just "product-photo-1.jpg"

What gets you ignored:

- No structured markup at all

- Incomplete schema with missing required fields

- Product descriptions that are just marketing fluff with no actual specifications

- Generic, duplicated content across multiple product pages

In our study, the sites with the strongest structured data were cited significantly more often by AI. This was one of the most reliable predictors of AI visibility.

2. Trust Signals That Make the Recommendation Safe

Here's something most brands don't consider: **AI assistants have reputations to protect.**

When ChatGPT or Perplexity recommends a product, they're putting their credibility on the line. If they send a consumer to a sketchy site with a terrible return policy and hidden fees, that consumer loses trust in the AI — not just in the retailer.

So AI assistants are cautious. They look for signals that make a recommendation "safe" — signals that reduce the risk of the consumer having a bad experience.

What builds AI trust:

-Clear return policy — Easy to find, easy to understand, reasonable terms

- Customer reviews — Visible, authentic, with a meaningful sample size

- Transparent pricing — No hidden fees, no bait-and-switch, total cost visible

- Contact information — Real phone number, email, physical address

- Security indicators — HTTPS, visible trust badges, secure checkout

- Brand consistency — Professional presentation, no red flags

What makes AI hesitate:

- Return policy buried in legal jargon three clicks deep

- No customer reviews or only a handful

- Pricing that requires clicking through to see the real cost

- No visible way to contact the company

- Outdated or unprofessional site design

In our validation study, trust signals were the single strongest predictor of whether AI would recommend a brand. Sites that made the recommendation feel safe got cited. Sites that introduced any doubt didn't.

3. Content That Directly Answers Shopping Questions

AI assistants are responding to questions. Not keywords — full, natural language questions. And the content they cite is the content that answers those questions most directly.

This is a fundamental shift from traditional SEO thinking. In SEO, you optimize for keyword phrases. In GEO, you optimize for question-and-answer pairs.

When a consumer asks "Is the Patagonia Nano Puff worth the price?" the AI is scanning the web for content that specifically addresses that question. A product page that includes a section about the jacket's value proposition, durability, and price comparison to alternatives is exactly what AI wants to cite.

What works:

- FAQ sections on product pages that address real customer questions

- Detailed product descriptions that go beyond basic specs into use cases, comparisons, and value propositions

- Buying guides that help consumers make decisions within your product category

- Comparison content that honestly positions your product against alternatives

- "Why this product" content that gives AI a clear, quotable reason to recommend you

What doesn't work:

- One-paragraph product descriptions that say nothing specific

- Pure marketing language with no substance ("Revolutionary! Game-changing! Best-in-class!")

- Identical descriptions across similar products

- Content that only talks about features without addressing the questions consumers actually ask

Think about it from the AI's perspective: if someone asks "What's the best organic dog food?" and your product page has detailed information about ingredients, sourcing, nutritional philosophy, and how it compares to alternatives — that's a page worth citing. If your product page just says "Premium organic dog food for your furry friend" — there's nothing for AI to work with.

4. Accessibility for AI Crawlers and Agents

Your product page might be perfect — rich data, strong trust signals, great content. But if AI can't access it, none of that matters.

AI accessibility is the technical foundation that makes everything else possible. And it's where many brands unknowingly sabotage their own AI visibility.

The basics that matter:

- robots.txt — Are you accidentally blocking AI crawlers? Many sites block bots by default without realizing they're also blocking the AI assistants that would recommend their products. Check your robots.txt file and make sure you're not blocking user agents like GPTBot, ClaudeBot, or PerplexityBot.

- llms.txt — This is a newer standard, similar to robots.txt but specifically for AI language models. It tells AI agents what your site is about, how it's structured, and what content is most important. Few sites have implemented it yet, which makes it a competitive advantage for those that do.

- Sitemap — A current, complete XML sitemap helps AI understand your site structure and find your product pages.

- Rendering — If your product information is loaded dynamically via JavaScript and isn't present in the initial HTML, AI crawlers might never see it. Make sure your critical product data is in the page source, not just rendered client-side.

Common mistakes:

- Blocking all bots in robots.txt (including AI crawlers)

- No sitemap or an outdated sitemap

- Critical product data loaded only via JavaScript

- Content hidden behind login walls or age verification that AI can't navigate

- Aggressive rate limiting that blocks AI crawlers

This is often the easiest category to fix and the one with the most immediate impact. A single line in your robots.txt file could be the difference between AI seeing your products and AI never knowing they exist.

5. External Validation and Consensus

AI assistants don't just evaluate your product page in isolation. They cross-reference information across the web. And the more external validation your product has, the more confident AI is in recommending it.

Think of it as the AI's version of social proof. If multiple independent sources — review sites, industry publications, comparison articles, expert roundups — mention your product positively, AI has a stronger basis for its recommendation.

What builds consensus:

- Third-party reviews — Coverage on independent review sites, industry publications, and expert blogs

- Comparison inclusions — Being featured in "best of" lists and product comparison articles

- Social proof at scale — Significant volume of customer reviews across platforms

- Press coverage — Mentions in reputable media outlets

- Community presence — Active discussions about your product in forums, Reddit, and social media

What limits consensus:

- No external mentions beyond your own site

- Only appearing on your own blog and social channels

- Few or no customer reviews on third-party platforms

- No presence in comparison or "best of" content

- Negative external coverage without a response or resolution

This is the hardest category to improve quickly because it depends on factors outside your direct control. But it's also the category that creates lasting competitive advantages. A brand with strong external consensus doesn't just score well once — it maintains AI visibility over time because the web consistently validates its products.

The Compound Effect

These five factors don't work in isolation. They compound.

A product page with great structured data AND strong trust signals AND question-answering content AND AI accessibility AND external validation is dramatically more likely to be cited than a page that only excels in one or two areas.

In our study, the top-performing sites didn't just lead in one category — they were consistently strong across all five. And the lowest-performing sites typically had gaps in multiple areas simultaneously.

The good news: you don't have to be perfect. You just have to be better than the alternatives AI is evaluating. And for most product categories, the bar isn't as high as you might think. Many brands haven't started optimizing for AI at all, which means even modest improvements can create meaningful competitive separation.

Find Your Gaps

The hardest part of GEO isn't making improvements — it's knowing where to start. Which of these five areas is your biggest weakness? Where are you leaving AI visibility on the table?

That's why we built Cited. Our Chrome extension scans any product page in seconds and scores it across all five areas. You get an overall score, individual category grades, and a specific top recommendation for what to fix first.

No guessing. No auditing spreadsheets. Just a clear picture of where you stand and what to do next.

[Install Cited — Free on Chrome Web Store](https://chromewebstore.google.com/detail/cited-ai-optimization-sco/lkoocmdelhakbkefbeenbiogebdghhgl)**