From SEO to AEO: The Evolution of Ecommerce Discovery

Discover how AI search is changing ecommerce. Learn the key differences between SEO and AEO, and get a 5-point checklist to audit your Adobe Commerce store for AI visibility.

February 8, 2026

Search engine optimization changed ecommerce. For two decades, merchants optimized for Google’s algorithm—keywords, backlinks, meta descriptions, site speed. The playbook was clear, even if the execution was complex.

That playbook is becoming obsolete.

AI assistants are replacing traditional search for product discovery. The journey that started with “best industrial suppliers” in Google now starts with “I need a supplier who can handle custom hydraulic fittings with 48-hour turnaround” in ChatGPT. The mechanics of discovery have fundamentally changed.

The Shift: From Search Results to Synthesized Answers

Traditional SEO operates in a simple loop:

1. User searches a keyword
2. Google returns ten blue links
3. User clicks one or more results
4. Merchant tracks traffic and conversions

AI assistants break this loop. When a user asks Perplexity for product recommendations, they get a synthesized answer—not a list of links to explore. The AI pulls from multiple sources, combines them, and presents a conclusion.

This creates a visibility problem. If your brand isn’t part of the AI’s synthesis, you don’t exist in that user’s journey. There’s no click to track. No bounce rate to measure. You simply weren’t part of the conversation.

Why AI Search Is Different

Three characteristics make AI search fundamentally different from traditional search:

1. Conversational Intent

Traditional search is transactional. Users type fragmented keywords: “hydraulic fittings distributor Texas.”

AI search is conversational. Users ask complete questions: “What’s the best hydraulic fitting distributor in Texas for B2B orders with custom specifications?”

This changes optimization. Keywords with high search volume matter less than questions with high commercial intent. Content that answers specific questions wins over content that targets broad terms.

2. Multi-Turn Discovery

Traditional search is single-session. Users search, click, convert or leave.

AI search is multi-turn. Users engage in extended conversations, refining their needs as they learn:

• “What are the top B2B ecommerce platforms?”
• “How does Adobe Commerce compare to Shopify Plus for distributors?”
• “What’s the implementation timeline for Adobe Commerce with ERP integration?”

Each turn is an opportunity to appear—or disappear. AI assistants remember context across the conversation. If you appear in turn one but not turn three, the user may forget you exist by the time they’re ready to buy.

3. Citation-Focused Authority

Traditional search relies on backlinks as authority signals. More links from reputable sites = higher rankings.

AI search relies on citation quality. When an AI assistant mentions your brand, does it get the details right? Does it recommend you for the right use cases? Does it understand your product capabilities?

Wrong information in AI responses is worse than no information. An AI that says you don’t offer custom manufacturing when you do is actively damaging your business.

What This Means for Adobe Commerce Merchants

Adobe Commerce merchants face a specific challenge. You’re often selling complex B2B products with long sales cycles, technical specifications, and nuanced use cases. Your buyers are exactly the type of users who benefit most from AI-assisted research—and exactly the type of products that AI assistants struggle to understand.

If your product data is incomplete, unstructured, or buried behind gated pages, AI assistants can’t cite you accurately. They’ll recommend competitors with clearer public information instead.

This isn’t hypothetical. We’re already seeing B2B buyers skip traditional research entirely. They start with AI assistants, trust the synthesized answers, and contact the recommended vendors directly. The RFP process is being replaced by AI curation.

How to Prepare: 5 Things to Audit Today

You don’t need to abandon SEO to start optimizing for AEO. But you do need to understand where you stand. Here’s a checklist to audit your Adobe Commerce store for AI visibility:

1. Product Schema Coverage

What to check: Run your top 100 product pages through Google’s Rich Results Test.

What to look for: Do you have complete Product schema? Does it include SKU, price, availability, dimensions, materials, and specifications? Are there errors or warnings?

Why it matters: Product schema is how AI assistants understand what you sell. Without it, they can’t cite your products accurately—or at all.

Action: Fix schema errors on your highest-revenue products first. Then expand to your full catalog.

2. Content Answerability

What to check: Review your top 10 blog posts and product category pages.

What to look for: Can you extract a clear answer to a specific question from each page in under 30 seconds? Or is the content meandering, keyword-stuffed, and unclear?

Why it matters: AI assistants cite content that directly answers user queries. If your content doesn’t have clear takeaways, it won’t be included in AI responses.

Action: Restructure existing content with clear H2 headers that signal answers. Add FAQ sections to key pages. Create new content that answers the top 20 questions your sales team hears.

3. Brand Mention Accuracy

What to check: Ask ChatGPT, Perplexity, and Gemini five questions where your brand should appear.

What to look for: Does the AI know you exist? Does it describe your products accurately? Does it recommend you for the right use cases?

Why it matters: Wrong information in AI responses is worse than no information. If an AI says you don’t serve a particular industry when you do, you’re losing that business.

Action: Document inaccuracies. Create content that corrects them. If the AI says you don’t offer a service you do offer, publish a clear page explaining that service.

4. Technical Accessibility

What to check: Test your key pages with JavaScript disabled. Check your robots.txt for unexpected blocks. Run a crawl with a tool like Screaming Frog.

What to look for: Can AI crawlers access your content? Is critical information loaded via JavaScript that might not render? Are important pages blocked?

Why it matters: AI assistants can’t cite content they can’t access. Technical barriers that don’t affect human users can eliminate your AI visibility.

Action: Ensure your key pages render without JavaScript. Fix robots.txt issues. Implement server-side rendering for critical product information.

5. Competitive AI Presence

What to check: Run the same brand mention test for your top three competitors.

What to look for: Do they appear in AI responses where you don’t? What content is being cited? Are they mentioned more frequently or more favorably?

Why it matters: AI visibility is competitive. If your competitors are optimizing for AEO and you’re not, they’ll capture the research phase of your shared buyers.

Action: Analyze the content that’s earning your competitors AI citations. Create better versions. Target the gaps where they don’t appear.

The Integration Challenge

Here’s the reality: you need both SEO and AEO. Traditional search isn’t dead—it’s still the primary discovery channel for most buyers. But AI-powered discovery is growing fast, and the optimization requirements overlap but aren’t identical.

The good news is that AEO improvements generally help SEO too. Structured data, clear content structure, and comprehensive product information benefit both channels. The work you do for AI visibility will improve your traditional search performance.

The bad news is that AEO requires new thinking. You can’t just extend your existing SEO strategy. You need to understand how AI assistants work, what they prioritize, and how they cite content. This is a new discipline, not an add-on.

The Timeline

If you’re wondering when to start taking AEO seriously, the answer is now.

• 2023-2024: Early adopters experimenting with AI visibility
• 2025: Mainstream awareness; early case studies emerge
• 2026: Competitive necessity; laggards start losing significant traffic
• 2027+: AI-powered discovery dominates B2B research

We’re in the 2025-2026 window. The merchants who build AEO capabilities now will have a 12-24 month head start. The merchants who wait will play catch-up in an increasingly crowded space.

Bottom Line

SEO optimized for search engines. AEO optimizes for AI assistants. The shift is happening whether you’re ready or not.

The merchants who understand this transition—and act on it—will capture the next generation of ecommerce buyers. The merchants who don’t will wonder why their traffic is declining while their competitors grow.

Audit your store. Fix your schema. Create answer-focused content. Monitor your AI presence. The fundamentals of commerce haven’t changed—be visible where your buyers are looking. But where they’re looking is changing fast.

Want to understand your AI visibility? Our AEO services for Adobe Commerce include comprehensive audits, strategy development, and implementation support. Contact us to learn more.