Product AI visibility · The wedge
Product-level tracking: every SKU, every engine.
A brand mention in ChatGPT is a soft signal. A specific product in the answer, with a price and a link, is the sale. eCommerce Insights tracks product AI visibility where revenue actually lives: per SKU, per engine, per query, across ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, and Copilot.
Resolution
Brand-level tracking answers one question. SKU-level AEO answers four.
Most AI visibility tools — Profound, Peec AI, Otterly — report whether your brand appeared in AI answers. That is genuinely useful, and they do it well. It just stops one layer above where the money is.
| The question you actually have | Brand-level trackers | Product-level (SKU) tracking |
|---|---|---|
| Is my brand mentioned in AI answers? | Yes | Yes |
| Which product is in the answer — the best-seller or the clearance SKU? | — | Yes |
| Which PDP do I fix first, and what exactly do I change? | — | Yes — diff attached |
| Is an out-of-stock variant still being recommended? | — | Yes — variant-aware |
| How much revenue is exposed when a SKU drops out of the answer? | Inferred at best | Per-SKU exposure |
The distinction is structural, not a feature gap a brand tracker can patch. If the unit of record is the brand, the data cannot tell a merchandiser what to do with their Tuesday morning. If the unit of record is the SKU, every row in the report is an action. That choice of unit is what SKU-level AEO means in practice.
How tracking works
AI search tracking in four steps: catalog connect to scored ledger.
Connect the catalog
Shopify connects from the admin in minutes; Amazon, Adobe Commerce, BigCommerce, WooCommerce, and headless stores connect by catalog feed. Every variant resolves as a distinct SKU. Collections, metafields, and tags feed the scoring model.
Build the query bank
eCommerce Insights generates buyer-shaped queries from your collections, best-sellers, and category intents — "best merino base layer for cold-weather running," not "merino shirt." Rotated each scan, editable if you have opinions.
Scan six engines
Every scan covers ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, and Copilot. Each SKU gets a citation record per engine per query: appeared or absent, how the recommendation was phrased, which sources sat alongside it.
Score and queue
Each SKU gets two scores with deltas per refresh — weekly on Starter, daily on Growth and Agency & Enterprise. Sort by revenue exposure, then open the failing SKUs in the PDP optimization diff queue.
| SKU | Query it competes on | Citations this refresh | Citation | Agent-read. |
|---|---|---|---|---|
| MERINO-BL-MD | best merino base layer, men's medium | ChatGPT 3× Perplexity 1× | 84 | 78 |
| ENAML-MUG-12OZ | durable enamel camping mug | AI Overviews 2× Gemini 1× | 73 | 64 |
| TRAIL-SOCK-3PK | best trail running socks under $30 | Perplexity 2× | 67 | 71 |
| WAX-JKT-OLV-L | waxed canvas jacket men's large | ChatGPT 1× Copilot 1× | 58 | 80 |
| CANVAS-TOTE-NAT | heavy canvas tote bag everyday | 6 engines 0× | 41 | 52 |
Illustrative ledger entries for a hypothetical catalog, not customer data. Real scores come from live scans on your query bank.
The two-score model
Every product is scored twice: is it cited, and can an agent read it.
The citation score measures today's outcome on the answer surface. The agent-readability score measures whether a shopping agent could parse the PDP well enough to recommend it or draft it into a cart. Both improve with the same fixes. Full methodology in the PDP Score docs.
Why two scores instead of one composite: a PDP can be cited today and still be unreadable to the cart-drafting agents arriving behind the answer engines — and the reverse. Tracking them separately tells you whether your problem is content, plumbing, or both. The stakes of the second score are laid out on the agentic commerce page.
Rollups exist. They're the dashboard, not the product.
Brand-level share of answer, engine-by-engine trend lines, and competitor share roll up automatically — the view a VP of Ecommerce takes into the channel review. Every number in the rollup drills down to the SKUs that produced it.
The SKU queue is where the work happens.
The operator's view is a prioritized queue: failing SKUs sorted by revenue exposure, each with its citation record and a reviewable diff ready in PDP optimization. Reports describe the problem; queues retire it.
Brand-level AI tracking is a report. SKU-level tracking is a plan.
Keep going
Tracking is the first third of the product.
PDP optimization
Every failing SKU gets a reviewable diff: title, description, bullets, schema, metafields. A human approves; Shopify push is Early access.
THE STAKESAgentic commerce
Agents already draft carts; checkout protocols are in pilot as of mid-2026. The same PDP groundwork serves all three stages.
THE PLATFORMProduct tour
Track, score, fix — the full loop, with pricing from $99/mo and a 14-day trial. Wedge-term primers: SKU-level AEO and product AI visibility.
Questions buyers ask
How many prompts does eCommerce Insights run per SKU?
It varies with the catalog. eCommerce Insights generates a buyer-shaped query bank from your collections, best-sellers, and category intents, then rotates it each scan so scores reflect a spread of phrasings rather than one lucky prompt. Each SKU is checked against the queries where it plausibly competes, on all six engines, at your plan's refresh cadence.
Do you track competitors' SKUs too?
Yes. Every citation record includes the other products the engine recommended in the same answer, so you can see which competitor SKU is taking the slot your product lost. Competitor share per query is part of the per-SKU ledger, not a separate add-on.
How is this different from Profound or Peec?
Profound and Peec track brand mentions across AI engines, and do it well. Neither resolves an answer to a specific product, so neither can tell you which PDP to fix. eCommerce Insights records citations per SKU, per engine, per query, and attaches a reviewable diff to every failing page. Full comparison with Profound.
What counts as a citation?
A citation is recorded when an engine names the product, links its PDP, or shows it in a shopping card in response to a query from your bank. Each record stores the engine, the query, the phrasing of the recommendation, and the other sources cited alongside it.
How fresh is the data?
Weekly on the Starter plan, daily on Growth and Agency & Enterprise. A manual rescan is available on every plan, so when a PDP fix ships you can re-score the SKU the same day instead of waiting for the next scheduled refresh.
What counts as a SKU on the Starter plan?
A tracked product variant. A product with five sizes in three colors counts as 15 SKUs, because AI engines cite specific variants and stock status differs per variant. Starter covers 500 SKUs, Growth covers 2,500, and Agency & Enterprise is sized to your catalog. Archived and draft products are excluded automatically.
Ready when you are
See every product the AI engines skip.
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6 engines · per-SKU ledger · weekly or daily refresh