Shoppers increasingly ask AI assistants and AI-powered search features for product recommendations, comparisons and advice. For ecommerce brands that have invested in traditional SEO, the obvious question is whether any of that work carries over — and what else is needed.
The honest answer starts with what you cannot do. You cannot guarantee that an assistant will mention your brand, and anyone promising a set number of AI recommendations is overselling. These systems change frequently and draw on many sources. What you can do is improve the inputs they rely on.
What AI systems draw on
Generative answers are assembled from information the system can access and trust. For product questions, that typically includes your own website, product data supplied to shopping platforms, and what other sites say about you. Each of those is something you can work on.
Five areas within your control
1. Clear, consistent brand and product information
Make sure your brand name, what you sell, who it is for and what makes it different are stated plainly and consistently — on your site, in product feeds, on marketplaces and on your social profiles. Contradictory or vague information makes it harder for any system to describe you accurately.
2. Content that answers real buying questions
Shoppers ask questions such as which product suits a particular skin type, how two options differ, or how long a supply lasts. Pages that answer those questions directly and specifically — on product pages, collection pages and guides — are useful to people and easier for AI systems to draw on. Generic copy written mainly to include keywords helps neither.
3. Technical accessibility
If important content is only rendered by JavaScript after interaction, hidden behind tabs that do not load until clicked, or blocked from crawlers, it may never be seen. Check that your key product and collection information is present in the rendered HTML and that your robots rules reflect deliberate decisions about which crawlers you allow.
4. Accurate structured data and product feeds
Structured data and product feeds describe your products in a machine-readable form: name, brand, price, availability, variants, identifiers. Keep them accurate and complete. In Google Merchant Center in particular, product data quality affects free listings and shopping experiences, and it is often owned by no one once the paid media setup is done.
5. A reputation that exists beyond your own site
Independent reviews, editorial coverage, expert mentions and community discussion all shape how a brand is described. This is not something to manufacture; it is something to earn and to make easy to find.
How to measure it
Start with a benchmark. Define a set of realistic prompts your customers might use — category questions, comparisons, problem-led questions — and record whether and how your brand appears across the assistants that matter to your audience. Repeat on a regular schedule. The results will vary between runs, so look for patterns over time rather than reacting to a single answer.
Alongside that, keep measuring what you already can: organic traffic and revenue, Merchant Center performance, and referral traffic from AI tools where it is identifiable in your analytics.
Where to begin
For most established brands, the first steps are unglamorous: fix product data quality, make sure key pages are crawlable and clearly written, and resolve inconsistencies in how the brand is described. These improvements support traditional search and generative search at the same time, which makes them a sensible investment whatever happens next.
If you would like help setting up an AI visibility benchmark or reviewing your product data, start a conversation.