How to adapt your ecommerce SEO strategies for GEO

Is it just us, or has the SEO world officially settled on the term GEO (over AIO, AEO, or whatever acronym-of-the-week was trending)?

Over the past few months, the conversation has shifted. It’s no longer just about how to rank on search engines. It’s about how brands can get referenced by AI, how SEO is (allegedly) dead, and how to adapt through Generative Engine Optimization (GEO).

But here’s the thing: SEO doesn’t need to be scrapped. In fact, most of what you’re already doing for SEO still matters. The difference now is knowing what to double down on, and where to bring in new tactics to stay visible in AI-powered search.

This article focuses specifically on ecommerce brands — how GEO differs from SEO, and how you can combine both strategies to stay discoverable in this new AI-driven landscape.

How AI Search Differs from Traditional Search

From 10 blue links to one direct answer

Remember when you had to click through a bunch of links, skim past fluff articles, do follow-up searches, maybe even take notes before finally finding the answer to a single question?

Later, Google introduced featured snippets. And while they directly answered some questions or provided definitions, they usually pulled from just one source.

Now, AI search does the entire research process for you. It scans multiple sources, pulls what it needs, and gives users one well-rounded answer upfront.

In this new setup, AI shapes the narrative. And brands need to earn their way into that answer.

Citations vs clicks

Click-throughs are dropping, for two big reasons:

1. People are shifting away from traditional search engines like Google and Bing.
2. Even on Google, AI Overviews are dominating the space above the fold, and “I Mode is changing how results appear entirely.

With AI-generated responses, users often don’t need to click. The only way your brand gets visibility is if the AI cites your content or recommends your product.

That’s the new battleground. But it’s winnable.

If your content is clear, structured, and directly answers the kinds of questions people are asking, you stand a chance of being featured.

That means your product data needs to be complete and enriched, your descriptions should highlight real use cases and target audiences, and your brand should be mentioned positively across trusted sources.

GEO vs SEO: What are the differences?

AI doesn’t just rank pages, it assembles answers

Traditional SEO is about getting indexed, matching keywords, and hoping users click your link. With GEO, that’s not enough.

Large Language Models (LLMs) don’t simply rank pages. They pull bits of content from across the web and build an answer. That answer might reference your content, your competitor’s, or a mix of both — depending on what the AI finds most useful, trustworthy, and relevant.

The focus shifts from “how do I rank” to “how do I make my content the most useful source to draw from.”

GEO is about intent, not just keywords

SEO has always been tied to intent, but GEO leans into it even more.

When someone asks “What’s the best laptop for photo editing?”, GEO doesn’t just scan for pages that repeat that phrase. It looks for content that actually explains what makes a laptop good for editing, like GPU strength, screen resolution, RAM.

For ecommerce, keywords still matter. But they work best when combined with answers to the real underlying questions, like:

• “Will this work for travel?”
• “Is it good for cold weather?”
• “Can this replace my DSLR?”

Products are entities, not just text on a page

LLMs understand products as entities. They don’t just scan for keywords—they connect the dots between product names, attributes, and use cases.

If you sell a shoe called the “UltraBoost 3000,” make sure your content connects it to relevant concepts:

• Running
• Marathons
• Arch support
• Cushioning
• Lightweight design

The more context you give around your product, the easier it is for AI to recognize when it’s relevant to a query.

So, cover the ecosystem around your product. Not just what it is, but who it’s for and when it’s useful.

Structure and language matter more than ever

Since AI models are trained on natural human writing, clear and well-structured content works better.

So content that’s clear, conversational, and well-organized is more likely to be pulled in.

On ecommerce pages, use structure to your advantage. Break information into readable sections like:

• “Common questions”
• “Best for…”
• “How it compares”
• “Tech specs at a glance”

This helps both humans and machines quickly understand what your product offers and who it’s for.

One page, multiple questions

AI search often mimics a real conversation. Users ask follow-up questions, and the AI stays in context.

That means your content needs to go beyond answering just one narrow question. For ecommerce, that might look like addressing:

• “Is this backpack waterproof?”
• “How heavy is it when empty?”
• “Can it fit a 15-inch laptop?”

This gives your page depth and makes it more useful across different moments in the search journey.

Look beyond rankings, clicks, and traffic

In SEO, success is usually measured in rankings, clicks, and traffic. With GEO, it’s less straightforward.

You might not always get a click, but you might still be part of the answer that the shopper sees. That counts as visibility—even if it doesn’t show up in your analytics dashboard (yet).

It’s worth expanding how you think about performance. Consider tracking things like:

• How often your products are mentioned in AI-generated answers
• Whether your content is being summarized or quoted
• How visibility compares across different types of queries

SEO used to be solo, GEO is a full-cast play

Traditional SEO teams could often operate independently — focusing on keywords, technical audits, and link-building in isolation. But GEO changes that.

Because AI pulls from product data, content, structured markup, customer reviews, and even off-site mentions, visibility now depends on how well your entire team works together.

• Your product team needs to ensure specs and attributes are complete and accurate.
• Your social media team publishes content that reinforces brand signals across the web
• Your brand and community teams help build trust through off-site visibility and reviews.

GEO is a concerted team effort that breaks down silos. It's not just about optimizing your site — it's about aligning your entire digital presence so that AI models recognize and reflect your brand accurately.

GEO is multimodal and goes beyond text

GEO isn’t just about optimizing text. People now search using images, voice, and video.

At the same time, generative engines interpret multiple types of content together — combining text, visuals, tables, and even reviews to form an answer.

Someone might upload a photo and ask, “Where can I buy this chair?” or say, “Show me shoes like this, but waterproof.” To respond, the AI needs to connect the image with product data, descriptions, and off-site content.

Your product images, filenames, alt text, and even what’s shown in the image all matter. If a product is shown being worn or used in the right context, that becomes part of how the AI understands when it’s relevant.

How to adapt your SEO ecommerce strategies for GEO (with examples)

On-page optimization: Content and site elements

GEO doesn’t replace SEO — it builds on it. Many best practices from modern SEO already overlap with what works in generative search: clear structure, semantic relevance, content depth. But GEO takes it a step further.

It’s not just about optimizing for keywords or rankings anymore. It’s about making your content the most useful, structured, and context-rich source an AI can draw from.

Here's how to evolve your on-page game accordingly:

Make product pages more useful (not just optimized)

• Create product descriptions that reflect real use cases, who the product is for, what its functionalities are, much better (e.g., instead of just “water-resistant down jacket with fleece lining”, describe it as “warm, water-resistant jacket for daily city commutes — fits comfortably over workwear and keeps you cozy down to -10°C.”)
• Add FAQs or Q&A sections directly on the page to address specific shopper questions (e.g., can this carry-on luggage fit in budget airlines?)
• Use a spec table for quick scanning and easy AI extraction (e.g., dimensions, materials, battery life).
• Feature multiple product images with different angles or lifestyle backgrounds
• Highlight recent trends or seasonality in the description, especially for fast-moving categories like fashion or wellness.

Strengthen your product data and structure

• Ensure product attributes are complete, specific, and accurate
• Tag products clearly (e.g. “breathable,” “vegan,” “carry-on size”) to improve relevance in AI results.
• Ensure categories are accurate and up-to-date, especially if you’ve launched new product lines.
• Add concise category descriptions to support internal linking and give LLMs extra context.

Go beyond translation — localize meaningfully

• Localize content based on region and audience needs, not just language — e.g. winter coats for Canada vs the UK.
• Mention regional use cases or conditions where appropriate (e.g. voltage compatibility, sizing differences).
• Translate metadata and structured data too, not just the visible text.

Create content beyond the PDP

• Start a blog or resource center to answer broader queries your PDP can’t — like comparisons or care guides.
• Link out from product pages to relevant blog posts (“How to choose the right size”).
• Encourage on-site reviews and make them visible, especially for common use cases (“Perfect for hiking with dogs!”).

Technical optimization

These aren’t new, but they’re more important than ever. For LLMs to understand and surface your content, your site needs to be machine-readable, structured, and fast.

Ensure structured data is in place

• Implement product schema markup: Use Product and ProductGroup/ProductVariant schema to highlight essential info like price, availability, ratings, and variants (e.g. size, color).
• Map product attributes to external standards: Align your attributes with formats recognized by Google Merchant Center, schema.org, and other retail data aggregators.

Optimize page structure and metadata

• Use semantic HTML and correct heading hierarchy (H1 > H2 > H3...): Make sure each page has one H1 and logically organized subheadings.
• Optimize meta titles and descriptions: While clicks are declining, these still influence how your content gets parsed, summarized, and potentially displayed by AI systems.
• Write descriptive image alt text and file names: Use real descriptions, not keyword stuffing — e.g. wool-winter-scarf-red.jpg instead of product123.jpg.

Prioritize crawlability and speed

• Ensure your pages are crawlable — check robots.txt and meta robots tags.
• Improve site speed by compressing images, minimizing scripts, and optimizing for Core Web Vitals.
• Consider llms.txt to guide AI crawlers (experimental but forward-looking).

Off-page optimization

While on-page and technical optimization works the same way for both ecommerce brands and distributors, there are clear differences for off-page optimization.

For brands (original product manufacturers)

You own the product and therefore need to own the conversation around it, wherever it happens.

Get reviewed by trusted publications: Pitch your products to relevant media outlets or B2B industry blogs (e.g. Wirecutter, Runner’s World, TechRadar).

Work with influencers to seed authentic mentions: Collaborate with creators to review or demo your product in real-life use cases.

Ensure consistency across your ecosystem: Your product descriptions, benefits, and positioning should match across your website, Amazon listings, press features, and distributor sites.

Optimize marketplace listings: If you’re listing products on third-party marketplaces (e.g. Amazon, Target Plus), enrich the listing with consistent descriptions, specs, and high-quality images.

Expand your presence across high-authority channels: Besides your own site, push content to platforms like Google Merchant Center, YouTube, Pinterest, and niche communities.

Encourage off-site reviews on marketplaces and aggregators: Even if you don’t sell DTC, product reviews on sites like Amazon or Walmart can signal credibility to generative engines.

Contribute to industry knowledge: Publish unique data, tips, or use cases in blogs and whitepapers, such as sustainability reports, user guides, or research-backed posts on ingredient effectiveness.

For distributors (multi-brand retailers like JD Sports, REI)

You may not own the product, but you do own how it's sold, reviewed, and discovered through your store.

Collect reviews for your retail experience: Encourage customers to review not just the product but their experience buying from you (shipping, returns, support). These reviews influence trust and brand signals.

Get featured in “where to buy” or “best retailer” lists: Reach out to shopping guides or editorial outlets to include your store as a recommended buying destination — especially for seasonal or niche products.

Maintain accurate and consistent messaging: Inject your brand voice, but make sure the product specs and features match those from the brand.

Participate in niche forums and Q&A sites: Join product-related threads on Reddit, Quora, or Discord where customers ask sizing, availability, or delivery questions — and answer as the retailer.

Final thoughts: GEO isn’t replacing SEO, it’s leveling it up

If SEO was about showing up on Google, GEO is about showing up in the answers themselves.

That means ecommerce teams can’t just optimize a product page and call it a day. Your content, product data, off-site presence, and even review quality all influence what AI models see and say about you.

The good news is most of what GEO asks for isn't new. The strategies you've used in SEO still apply, but now they need to work together across channels and teams.

Whether you're a ecommerce brand or distributor, what you put out into the world and how clearly and consistently you present it is what AI will draw from.

So polish your schema. Clean up your product descriptions. Answer real questions. Because in a world where AI is the new front door to discovery, the brands that communicate clearly and consistently are the ones that get seen.