If one of those three products is yours, the shopper arrives ready to buy. If not, they never learn your store exists.
The same scene plays out in Google’s AI results, Claude, Perplexity, and Copilot, thousands of times a day.
Ready to start? Book a 30-min strategy session.
Why good products lose recommendations they should win
Most catalogs break somewhere along that path. Quietly
The recommendation still goes to a competitor whose data told a cleaner story.
None of this shows up as an error. Every dashboard looks fine.
The recommendation still goes to a competitor whose data told a cleaner story.
The order of work matters, so we start with a strategy session
You leave with the sequence for your website
An AI Search Strategy session puts marketing, commerce, content, and engineering in one room. We walk through how AI search discovers pages and feeds, expands one question into dozens of searches, and forms a recommendation.
The session sets the priorities. The three services below do the audit and execution work.
Three services that move your products into the answer
Technical AI Search Optimization
First, we make the catalog reachable.
We trace every eligible product from Shopify, Salesforce Commerce Cloud, a PIM, or a custom catalog through templates, structured data, and merchant feeds. We find where products disappear, variants collapse, prices drift, and crawlers receive incomplete pages.
Then we work with your developers until the fixes are live and verified.
AI Search Relevance and Intent Matching
Once AI can see the catalog, the next question is whether it picks your product.
We map the situations buyers describe, the searches AI runs behind them, and the products it cites. Where a competitor wins, we show why, then sharpen the positioning, category copy, and buying guidance that swing the decision.
We keep monitoring those questions after the changes go live.
Content Strategy, Engineering, and Generative AI
Every new product and category has to follow the same rules we just fixed, or the catalog drifts back into invisibility.
So we build the production system: content models, prompts, review rules, and release workflows your team runs without us. The output is content tied to the buyer’s decision, not thousands of pages repeating the same description.
The hard part sits between your systems, which is where we work
Commerce platforms
Shopify, Salesforce Commerce Cloud, PIMs, seller data, and custom catalogs.
Site infrastructure
JavaScript rendering, redirects, canonicals, sitemaps, faceted navigation, and internal links.
Structured data
Product, offer, organization, location, review, and relationship markup.
Destinations
Google Merchant Center, OpenAI product feeds, Microsoft commerce surfaces, and crawler access for every major AI system.
Relevance
Buyer-question research, query fanout, citation analysis, and product positioning.
Production
Content models, prompts, factual controls, editorial QA, and refresh workflows.
You get one view of how a product moves from your database into an AI answer, with clear changes for each team that owns part of the path.
Built for catalogs that make ordinary audits fall apart
Websites where problems repeat across thousands of URLs
We trace repeated failures to the template, rule, mapping, or workflow that creates them. Your team fixes the system once instead of repairing pages one at a time.
Your AI search program should keep working after the audit
The catalog changes after launch. Search systems change how they read it. Buyers ask new questions. Competitors give AI better evidence.
We stay through implementation and check what changed after release. Ongoing monitoring tracks the questions, products, citations, and feeds that matter to your visibility.
You will know where visibility was lost, what caused it, and which change should happen next.
See where the path to your products breaks
Bring us the website, catalog, and questions you need to win. We will show you whether the first problem sits in technical access, product relevance, or the content system behind both.