AI agents are already recommending your products to shoppers. Some of those shoppers buy. Many don't. The gap between the recommendation and the purchase is almost always a listing problem — the agent didn't have enough confidence in the product data to push the recommendation over the line. This playbook shows you how to find those products and fix them.
Goal: Conversion rate improves on targeted products within two to three weeks of APL creation.
Time to complete: 30–45 minutes to identify and set up; ongoing as you apply APLs.
Features used: AgentIQ Overview → Analytics Dashboard · Prompt Library · My Store → Agentic Product Listing (APL)
Step 1: Find Products Where Agents Are Recommending but Not Converting
AgentIQ Overview — Agent Traffic Analytics showing sessions, conversion rate and attributed revenue by product
The Analytics Dashboard shows you which products agents are already recommending — and which aren't converting after the recommendation. High sessions with low conversion is the signal you're looking for.
Go to AgentIQ Overview.
Scroll to the Best Attributed Products section.
Sort by Sessions to find the products getting the most agentic traffic.
Cross-reference with Conversion Rate. Products with high sessions and low conversion are agents recommending you — but something in the listing is stopping shoppers from completing the purchase.
Note the top three to five products in this pattern. These are your targets for this playbook.
📌 Tip: Also check the AI Agents Distribution section. If most of your traffic is coming from one specific agent (e.g., ChatGPT) and conversion is low specifically there, the issue may be a listing gap that matters more to that agent's ranking logic.
Step 2: Build a Purchase-Intent Prompt Library for Each Target Product
Prompt Library preview — showing prompts with User Prompt, Category and Sub-intent columns
A product that converts well in agentic channels has an Agentic Product Listing optimized for high-intent prompts — the ones where a shopper has already decided to buy, not just browse. The Prompt Library is where you find those prompts.
Go to Prompt Library and create a new library for your first target product. In the description, brief the agent on the product, the buyer and the type of purchase-intent conversations you want to surface.
Use Discover Subreddits to find communities where your buyers discuss this product before buying — not just after. Buying advice and product review communities tend to generate higher-intent prompts than enthusiast communities.
Once the library is Ready, open it and look at the prompts. Filter by Sub-intent and look for language that signals a decision stage: "best X for Y", "which X should I buy", "X vs Y", "X under $[price]".
Note two or three prompts that best capture purchase intent. You'll use these in the next step.
Step 3: Create Agentic Product Listings Optimized for High-Intent Prompts
The Agentic Product Listing is the agent-optimized version of your product, stored as Shopify metafields. It increases agent confidence at the final recommendation step — the moment when the agent decides whether to include your product in its response or skip it.
In My Store, find your first target product in the Product Optimization Opportunities table and click Create APL (or View APL → Edit prompts if one exists).
Select two or three high-intent prompts from your library. Using prompts that signal buying intent — not research — ensures the generated listing is optimized for the moments when shoppers are most likely to convert.
Click Run agentic listing. AgentIQ pulls in competitor data and generates a more competitive Agentic Product Listing. The run takes a few minutes — click Run in background if you don't want to wait.
Review the generated Unique Selling Point, Agentic Title, Agentic Description and Top Features, and edit inline if anything needs adjustment.
Repeat for each product on your shortlist.
One-time setup: AI agents only see your APLs after the AgentIQ fields are mapped into your Shopify Catalog. If you haven't done this yet, follow Mapping Agentic Product Listings to Your Shopify Catalog.
📌 Note: The APL structures data in a way that increases agent confidence at the final recommendation step. A product with a well-structured APL is more likely to be recommended with confidence — and a confident recommendation converts at a higher rate than a hedged one.
Step 4: Measure the Impact
Wait two to three weeks after applying the APLs.
Return to AgentIQ Overview and check the conversion rate on your target products.
Compare the Attributed Revenue before and after for the same products. If conversion rate improved, the APL is working.
For any product that still isn't converting, go back to My Store, open the product and check the Prompts Analysis panel with your target prompt. The Analysis Results panel will show exactly which listing gaps are still breaking the handoff.
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