AI agents are already sending shoppers to your store. Some of those shoppers are buying. Many are not. This playbook shows you how to find the products where something in the listing is breaking the handoff — and give you a ranked shortlist to act on.
Goal: A ranked shortlist of three to five products with clear, actionable reasons why they're underperforming on agentic conversion.
Time to complete: 20–30 minutes.
Features used: AgentIQ Overview → Analytics Dashboard · My Store → Catalog Health Tracker · My Store → Important Warnings
Step 1: Find Your High-Traffic, Low-Conversion Products
AgentIQ Overview — Agent Traffic Analytics showing sessions and conversion rate by product
The Analytics Dashboard shows you which products AI agents are already recommending — and which ones aren't converting after the recommendation. That gap is where agentic revenue is leaking.
Go to AgentIQ Overview in the left navigation.
Scroll to the Agent Traffic Analytics section.
Look at the Best Attributed Products list. Sorted by Sessions to see which products are getting the most agentic traffic.
Cross-reference with Conversion Rate. Products with high sessions and low conversion are your targets — agents are recommending them, but something on the listing is stopping shoppers from completing the purchase.
Note the top three to five products in this pattern. These are your shortlist.
📌 Tip: Also check the AI Agents Distribution section. If most of your traffic is coming from one agent source (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: Check the Catalog Health Score for Each Target Product
My Store — Catalog Health Tracker dashboard showing health scores across the catalog
A low Catalog Health score correlates directly with low agent confidence. When an agent evaluates a product with incomplete or weak listing data, it's less likely to recommend it — and even less likely to communicate the right information to close the sale.
Go to My Store.
In the Product Optimization Opportunities table, find each of your shortlisted products.
Check the Health badge next to each one: Excellent (green), Mediocre (amber), Poor (red), or Bad.
Click Fix Now (in the Product Schema column) on any product with a Mediocre, Poor, or Bad score to open its Product Listing page and see the full breakdown.
On the Product Listing page, review the AI Suggestions panel — each card shows the specific gap, why it matters, and a ready-to-apply fix.
📌 Note: A high score in one dimension (e.g., Product Score: 98%) does not offset a low score in another. AI agents evaluate all signals simultaneously — a weak description can cause a miss even when category and tags are perfect.
Step 3: Identify the Specific Gaps Driving Poor Performance
My Store — Important Warnings panel showing catalog-wide issues ranked by impact
The Important Warnings panel surfaces the highest-impact issues across your entire catalog. Use it to find the pattern — often a single warning type explains poor conversion across multiple products.
In My Store, look for the Important Warnings Detected section and expand it.
Review the warning cards. Each one shows how many products are affected and why it matters for AI agent performance.
Filter by the warning types most likely to break conversion:
Missing image alt text — agents use alt text as a visual signal. Missing alt text means the agent can't fully understand what the product looks like.
Poor categorization / low category depth — a shallow taxonomy path reduces match precision for intent-driven queries.
Incomplete metafields — missing structured data means agents have less to work with when evaluating fit against a shopper's prompt.
Description too short or too generic — agents rely on descriptions to match products to conversational queries. Thin descriptions produce weak matches.
For each warning type, click through to the affected products and cross-reference with your shortlist from Step 1.
Step 4: Prioritize and Act
You now have a shortlist with specific, named gaps. Work through them in this order:
Missing image alt text first — highest agent impact, fastest to fix. Open each product's listing editor, click Apply on the AI Suggestion for alt text, and move on.
Poor categorization second — in the Product Listing Editor, use the Search Shopify taxonomy categories tool or click Suggest a better category to get an AI-generated recommendation. Aim for at least four taxonomy levels — deeper, more specific categories improve match precision.
Incomplete metafields third — the metafields section shows the gap count. Fill any missing fields flagged as required for agentic discoverability.
Thin descriptions last — these take the most time but have significant impact. Use the Prompts Analysis panel on the product (My Store → open product → Prompts Analysis) to run your target prompt and see exactly how to rewrite the description for that query context.
📌 Note: After making changes, click Refresh Scores on the Catalog Health Tracker to re-evaluate your catalog against the updated listings. Check back in 24–48 hours to see the impact in your Analytics Dashboard.
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