60% of search queries now end without users ever clicking through to a website. It means that your potential customers are asking ChatGPT, Perplexity, and Claude for product recommendations and getting direct answers.
That’s a problem. Because if your products aren’t showing up in those AI answers, you don’t exist to those shoppers. And right now, most e-commerce brands are completely invisible or have very little presence in AI platforms.
In this blog, we’ll show you how an ecommerce seo strategy needs to evolve to get your products recommended by AI search engines, so shoppers discover your brand when they ask for buying advice.
Contents
2 Technical Blocks Preventing AI From Reading Your Site
Here are two issues that prevent AI from reading your site properly:
1. Robots.txt Blocking AI Crawlers
Most e-commerce stores accidentally block AI crawlers in their robots.txt file. This is a simple text file that tells search engines and bots which parts of your site they can or can’t access.
What to do: Check your robots.txt file by visiting yourdomain.com/robots.txt and look for entries like:
- User-agent: GPTBot
- User-agent: PerplexityBot
- User-agent: ClaudeBot
If any of these user agents are followed by “Disallow: /”, remove those lines. When they’re blocked, you’re preventing the bots that power ChatGPT, Perplexity, and Claude from crawling your product pages. This is a five-minute fix that opens up your entire site for AI discovery.
2. JavaScript-Rendered Content
Even when AI crawlers are allowed through robots.txt, most of them can’t execute JavaScript. If your e-commerce site relies on JavaScript to load product names, prices, variants, or reviews, AI bots only see empty HTML shells. To them, the product page has no content. This is why critical product data must be rendered server-side or pre-rendered, so the product information is already present in the page’s HTML before any JavaScript runs.
Why AI Can’t Tell What Your Product Actually Is (Without This One Thing)
AI engines don’t interpret product pages like humans. They rely on structured data (JSON-LD schema) to understand what a page is about and what’s being sold. Without a schema, your product data is just unlabelled text with no clear meaning for AI.
AI systems may read the text on your page, but without structured data, they cannot identify what each piece of content represents. They cannot clearly separate the product name from a heading, the price from marketing copy, or stock status from supporting text. When this clarity is missing, AI sees the page as unreliable information and is less likely to use or recommend it.
At a minimum, ecommerce product pages should include:
- Product schema: defines product identity, attributes, pricing, and availability for AI systems
- Offer schema: clarifies transaction details like price, currency, seller, and stock
- Review schema: signals credibility through ratings and review volume to AI engines
- FAQ schema: enables AI to extract and surface precise product answers
This structured data is what search engines and AI systems use to generate product cards and shopping recommendations. If it’s missing or incomplete, your products are harder to surface – even if the page content itself is good.
How to Implement Schema at Scale for Large E-commerce Stores
For stores with a large catalogue, manual schema implementation isn’t realistic. Managing JSON-LD for 100+ products leads to errors and outdated pricing. The practical solution is automated schema generation, where the schema is dynamically created from your product database:
- On Shopify, schema apps (for example, Schema Plus) automatically generate and update product, offer, and review schema using live product data.
- On WooCommerce, schema plugins handle the same process without manual coding.
- For larger or more complex setups, tools like Yoast SEO for WooCommerce or custom API-based solutions pull product data directly from the backend and keep schema synchronised.
When the schema is generated automatically, your product data stays consistent and reliable for both AI systems and search engines.
Where AI Actually Finds Your Products (Not Your Website)
AI just reads your website and figures out what you sell, right? Wrong. It scans the entire web to understand how your product is described, how often it’s mentioned, who recommends it, and whether people actually trust it. Most of that data comes from platforms like:
1. Reddit
AI uses Reddit to understand real user sentiment around products, brands, and buying decisions. It looks for unfiltered discussions where users share opinions without marketing language or brand control.
Specifically, AI systems analyse:
- Product comparisons between competing brands
- “Is this worth it?” and buying advice threads
- Honest pros and cons shared by real users
These discussions help AI assess credibility and real-world performance. You influence this by ensuring your product appears in user-led subreddit conversations.
2. YouTube
YouTube is a major source for product demonstrations and reviews. AI systems use these videos to understand how products are explained, shown, and evaluated in real-world use.
AI pulls signals from:
- Video titles and descriptions
- Video transcripts
- User engagement patterns
You can influence this signal by publishing clear product walkthroughs, real-use tutorials, and honest comparison videos that explain how your product actually works.
3. Editorial “Best Of” Lists
AI trusts editorial “Best Of” lists because they come from independent publishers, not brands. These lists help AI understand which products are recommended by credible third parties.
AI looks for signals such as:
- Explicit product recommendations based on editorial judgment
- Direct comparisons that show how products differ
- Clear use cases that define who each product is best for
You can influence this signal by pitching your product to niche-relevant publications and working with editors who already review and compare products in your category.
4. Product Comparison Pages
When comparisons are missing, AI fills the gap using Reddit threads, random blogs, and half-informed opinions. But when you publish clear comparison pages, you’re giving AI first-hand context straight from the source.
AI then understands:
- How your product actually differs from alternatives
- What problems does your product truly solves
- What buyers should realistically expect after choosing your product
Pro-Tip: Write comparison pages like a real buyer thinking out loud. Be clear about trade-offs, mention where alternatives fit better, and explain use cases honestly. And most importantly, don’t shy away from naming competitors – this signals credibility, helps AI take your comparison seriously, and increases your chances of ranking for comparison queries.
Conclusion
AI search works very differently from Google, and ecommerce seo strategy needs to evolve accordingly. It needs to access your site easily, understand your product data clearly, and see real proof that people trust your products. If any of that is missing, your website gets ignored by AI systems, even if your SEO looks fine.
The good news is this isn’t about chasing hacks or trends. It’s about fixing the basics so AI can read your site and trust the signals around your brand.
This is where most e-com teams slow down, because AI visibility touches site infrastructure, product data, and external platforms, and small mistakes here quietly prevent AI systems from understanding or recommending your products.
At Brandshark, a digital marketing agency in Bangalore, we help e-com brands get visible in AI-driven search by building an ecommerce seo strategy that makes products readable, trusted, and recommendable by AI systems. If you want your products to show up in AI answers and recommendations instead of being skipped, our team can help you – get in touch with us today.
Reference Links:
60% of searches end without a click
Frequently Asked Questions
1. Why aren’t my products showing up in ChatGPT or AI search results?
Your products usually don’t appear because AI systems can’t access your site, can’t read key product data, or don’t trust the signals around your brand. This happens when bots are blocked, content is JavaScript-heavy, or structured data and external mentions are missing.
2. Does blocking AI bots in robots.txt affect my AI search visibility?
Yes. When AI bots are blocked in your robots.txt file, they can’t crawl or understand your product pages. As a result, your products never enter AI systems at all, which means they can’t be referenced or recommended in AI-generated answers.
3. Is schema markup really necessary if my on-page content is good?
Yes, good content helps humans, but schema helps AI understand it. Without schema, AI can’t clearly identify your product details, which makes it far less likely to recommend or surface your pages
