/Insights/eCommerce SEO: Future-proof strategies for AI & LLM search

eCommerceSEOintheAgeofAIandLLMSearch

Sep 22, 2025

8 min. read

eCommerce SEO visualization showing keyword analysis, AI insights, and organic traffic growth with structured data for improved search visibility.

For years, eCommerce SEO was all about keywords. Then it was all about entities. Now, we’re entering into a new era: AI and large language model (LLM)-powered discovery.

LLMs are an artificial intelligence system, often built on deep learning architectures called transformers, trained on vast amounts of text data to understand, summarize, translate, and generate human-like text and content. Some of the most popular LLMs include GPT-4 (OpenAI), Gemini (Google), Claude 3 (Anthropic), and LLaMA 3 (Meta).

So, what do LLMs have to do with eCommerce SEO? Well, these models aren’t just for summarizing web pages or generating content. They’re increasingly acting as discovery engines and are significantly changing the way people discover new products or services. LLMs are pulling structured data, product feeds, and site architecture to recommend products, answer buyer questions, and shape purchasing decisions.

That’s why the industry took notice when OpenAI announced its Shopify integration, enabling product feeds to flow directly into ChatGPT, or when Shopify unveiled its Storefront MCP initiative to break down “text walls” and make storefront data more machine-readable. Together, these signals point to the future. SEO isn’t disappearing, it’s expanding into new surfaces like feeds, conversational queries, and AI assistants.

Here’s what you need to remember, though: all of this doesn’t equal the death of eCommerce SEO. It’s stress-testing it, and the fundamentals of SEO have never been more important for success.

From rankings to data feeds

Traditionally, SEO success was measured by impressions, rankings, and click-through rates. But AI-powered search engines and assistants operate differently. Instead of only crawling pages and ranking them, they increasingly consume structured data feeds and APIs to power their answers.

This shift means SEOs must broaden their skillsets. Optimizing title tags and meta descriptions isn’t enough anymore. Now, SEO requires thinking like a data architect, ensuring product catalogs are complete, structured, and machine-readable.

Product catalogs as the core of AI SEO

At the foundation of this new SEO landscape is the product catalog. For both search engine results pages (SERPs), like Google or Bing, and AI-driven discovery engines, the catalog is at the heart of visibility.

Gaps in product data lead directly to missed opportunities in both search rankings and AI assistant recommendations.
Enriched, structured catalogs help AI systems surface products with confidence.

Simply put, your catalog isn’t just for your storefront. It’s your eCommerce SEO backbone across every discovery surface.

Conversational enrichment for buyer intent

Product specs alone aren’t cutting it anymore, either. Both buyers and AI assistants need natural, decision-oriented language to understand what a product offers and why it matters.

Forward-thinking brands are mining customer reviews, support tickets, and sales conversations to identify buyer phrases and intent-driven language. Feeding this enriched content into catalogs and structured data ensures that AI assistants can recommend products in the natural language of customers, and not just technical specs.

Structured data as the bridge between search and AI

Structured data are organized pieces of information in the form of code snippets that help search engines better understand what a website’s content is all about. Schema is the vocabulary, or the specific “language,” used to define the types and properties of data.

And while the two have always been essential for SEO success, in this new age of AI, it’s connective tissue between a website and discovery engines. Beyond basic markup, advanced schema types like ProductGroup, MerchantReturnPolicy, HowTo, and Comparison expand visibility across both search engines and AI systems.

Implementing structured data/schema ensures AI can parse, trust, and recommend your content with accuracy. And no this isn’t some hack. It’s infrastructure and the foundation for SEO success. Without it, products risk invisibility in the next generation of search.

Technical SEO foundations still matter

Even as AI reshapes discovery, traditional technical SEO fundamentals remain non-negotiable:

Crawlability, speed, and clean indexation still impact rankings.
APIs, JSON-LD, and structured feeds are now part of “technical readiness.”

A simple test: Can a machine easily parse, understand, and trust your product data? If not, your visibility will suffer in both SERPs and AI-powered assistants.

Full-funnel content for AI visibility

AI assistants do more than just recommend product pages. They surface answers, which means full-funnel content is more important than ever before.

Buyer’s guides, how-to articles, and product comparisons play a crucial role in attracting mid- and top-funnel visibility. Structured content formats like FAQs pages, how-to’s, and article schema help ensure that assistants recognize and elevate your expertise.

This approach expands reach beyond the bottom of the funnel, making your brand discoverable wherever users are asking questions.

Metrics: From vanity to value

The rise of AI, and using it as a discovery tool, has reduced reliance on traditional “vanity metrics” like impressions or rankings. Now, SEO measurement is evolving to capture the true business impact.

While impressions and rankings are definitely still useful, they’re no longer the end goal.
AI-driven search introduces new performance signals, such as assistant-driven visibility, engagement, and direct revenue impact.
How SEO contributes to commercial outcomes is a critical KPI — it’s no longer just about clicks.

A practical framework for AI-ready SEO

To succeed in this new era, brands need a structured approach to SEO:

Build a strong catalog foundation.
Add conversational enrichment.
Implement a robust structured SEO layer.
Ensure technical readiness with feeds, APIs, and JSON-LD.
Develop full-funnel content that serves both users and AI.
Align SEO efforts to revenue and business outcomes.
Commit to continuous iteration as the AI landscape evolves.

The expansion of SEO

The rise of AI search does not signal the end of SEO — it signals its evolution. AI assistants, product feeds, and conversational queries are new discovery surfaces that demand a rethinking of SEO fundamentals.

The brands that thrive will be those that blend traditional technical excellence with enriched, structured, and AI-ready data. SEO is no longer just about ranking in SERPs; it’s about being visible wherever customers are searching, whether that’s on Google, ChatGPT, or the next generation of AI-powered assistants.

Ready to future-proof your SEO strategy?

AI and LLMs are rewriting the rules of digital discovery. With the right foundation, your brand can thrive online. Codal can help you turn product data, structured content, and technical excellence into visibility across every search avenue.

Talk to our SEO experts today and start preparing for the age of AI.

Topic

Unified commerce

Strategy

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