AI discoverability for brands and online stores (GEO and AEO)

Who it is for

E-commerce brands and store owners (merchants), often the marketing team, who want their products to come up when shoppers ask AI assistants what to buy, and want those assistants to describe their brand correctly. Most of this work is on Shopify; the same checks apply to other stores.

Problems I solve

• “ChatGPT does not recommend my products,” even when they are a good match for what the shopper asked.
• Product descriptions are missing the details shoppers ask AI assistants about, such as sizing, materials or what is included.
• Common questions about the product are not answered anywhere an AI assistant can read them.
• The structured data on product pages is missing or incomplete.
• AI assistants describe your brand inaccurately, leave it out, or name competitors instead.
• You do not know where your products and brand stand today, or which fixes matter most.

What you get

1. An audit of the products you choose:
   • Product content: how complete the title, description, specifications, images and alt text, variants and SEO fields are.
   • FAQ coverage: whether a store FAQ page and product-level FAQs answer the questions buyers actually ask.
   • Structured data: Product and FAQPage schema.org data (JSON-LD) on the live product page.
   • Catalog data quality: product feed and catalog fields, where relevant to your store.
   • AI search tests: a defined set of shopper questions asked to selected AI assistants, recording whether each product is found, cited or recommended.
2. A brand AI visibility check:
   • How AI assistants describe your brand: whether they mention it, which facts they state, which sources they cite, and which competitors they name instead.
   • Brand facts and structured data: a consistent name, description and details across your website, profiles and listings, with Organization structured data that links them as one brand.
   • Monitoring over time: brand mentions and citations across AI assistants, tracked with an AI visibility monitoring tool such as Promptwatch, so you can see whether changes make a difference.
3. A written report with a score per product, the brand findings, and the gaps listed by impact.
4. The fixes, in order of impact: product content, brand information, FAQ content and structured data.
5. A follow-up assessment: the same audit and the same questions again, so you can see what changed.

An audit improves the information AI assistants read. It cannot guarantee a citation or a recommendation, because each assistant decides those on its own.

The same practices on this website

I use the same approach on this site, as brand visibility work applied to a person. When I tested how AI assistants describe me, one mixed me up with another engineer with a similar name. To fix that, this site now uses:

• Structured data (JSON-LD) for who I am, my services, projects and FAQs, checked with Google’s Rich Results Test.
• Consistent facts everywhere: the same name, role, location, education and past employers on this site and my GitHub profile, with my profiles linked to each other as the same person.
• Answer-first content: FAQs and service pages that answer real questions directly, without claims I cannot back up.
• An llms.txt file: a plain-text summary written for AI tools, generated from the same data as the site.
• Clear technical basics: descriptive titles and descriptions, a sitemap, canonical URLs, and Google Search Console.

I am re-testing how AI assistants describe me after these changes, and I will publish the before and after results here.

Evidence

• product_geo_agent: an AI agent I built that runs these checks on a Shopify product and scores it from 0 to 100. On a sandbox store it scored a complete product at 70 and a product with an empty description at 10, and named the gaps in each.
• Structured data (JSON-LD) apps for Shopify and BigCommerce, which I contributed to as part of a team.
• This website: the same structured data, FAQ and consistency practices applied to my own site, with the source code public on GitHub.

How a project runs

1. Pick the products. Usually best sellers or one category, so the first results come quickly.
2. Audit. The checks above, on your live store.
3. Report. What is missing, what to fix first, and why.
4. Fix. Changes in your store admin, metafields and structured data, with your approval.
5. Re-check. The same audit again, to show the result of the fixes.

Frequently asked questions

How long will it take for AI assistants to show my products?

There is no guaranteed timeline. Different AI assistants discover and update product information in different ways, and changes to your store may not appear immediately. I can identify and fix technical and content gaps, but I cannot control when a particular assistant updates its information.

Do you need access to my Shopify theme code?

Not always. Many improvements can be made through the Shopify admin, product content, FAQs or structured data. Theme changes are needed when the issue comes from how your storefront renders content or exposes product information.

Can you guarantee that AI assistants will recommend my products?

No. AI recommendations depend on each platform’s systems, the information available, the shopper’s question and other factors outside a store owner’s control. I can audit and improve your product information and test defined queries, but I cannot guarantee recommendations or rankings.

Can you check how AI assistants describe our brand, not just our products?

Yes. I test how assistants such as ChatGPT, Gemini and Perplexity describe your brand, which sources they rely on, and where they get facts wrong. Then I make your brand information consistent across your site and profiles, and track mentions and citations over time with an AI visibility monitoring tool such as Promptwatch. As with products, no one can guarantee what an AI assistant says, but missing or inconsistent information can be fixed.

Are GEO and AEO the same as SEO?

They overlap, but they are not the same. SEO helps pages appear in search results. Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) make information easier for AI-powered search and answer systems to discover, understand and use. None of these approaches guarantees a particular result.

Contact

Available now, and I usually reply within a few hours. Email me at mohammadalijaisar@gmail.com. Tell me whether you want a full-time hire, a contract, or a project, and your store address and which products matter most. Rates are in the pricing table.