Fix the PDPs AI engines are writing out of the answer.

Title and taxonomy

eCommerce Insights rewrites each product title so it resolves as an entity an AI engine can cite: brand, then model or series, then category, then primary differentiator. "Merino Base Layer — Forest" becomes "Brand X Merino 200 Base Layer, Men's, Forest Green." The diff view shows before and after for Shopify's default product.title field. Bulk-apply by collection and write the canonical form into a metafield so your theme, search, and JSON-LD all read from one source.

Description and bullets

Answer-surface engines skim for facts before they read prose. eCommerce Insights extracts what matters for the category — use-case, size or fit, material, compatibility, care — and moves it to the top of the description. Marketing fluff, recycled tagline prose, and adjective chains that AI engines ignore get deprioritized, not deleted. Every change lands as a diff you approve, so brand voice stays yours.

Structured data (Product schema)

eCommerce Insights generates complete, valid Product JSON-LD for every SKU: name, brand, sku, gtin where available, offers with price and availability, image, and aggregateRating when real review data exists. The JSON-LD is written into a product metafield so your theme renders it without a developer ticket. See the schema for AI search guide for the per-field scoring rubric.

Metafields and attributes

eCommerce Insights populates the Shopify metafields AI engines correlate with product identity: material, weight, dimensions, care instructions, size chart, compatibility, GTIN, MPN, country of origin. Those attributes feed AI engines through your llms.txt and JSON-LD — and they improve internal Shopify search and collection filtering at the same time. Standard metafield definitions so PIM round-trips and theme reads stay intact.

Image alt text and captions

Alt text still feeds the LLMs that index text around images, and it's still the cheapest accessibility win on most stores. eCommerce Insights reviews every product image alt across the catalog, flags duplicates and generics ("product image," "photo 2"), and proposes alts that name the SKU, the variant attribute in-frame, and the use context. One field, every image, whole catalog.

writes and uploads your catalog content for you, end to end, across Amazon, Walmart, and the AI engines. Their done-for-you model and marketplace depth work well for enterprise CPG teams with procurement cycles and ticket queues. eCommerce Insights is self-serve: recommendations, not ghostwriting. Your team stays in the approval loop, and the target is your Shopify catalog, not a retail marketplace.

built a six-stage ingest → evaluate → enrich → distribute → sync → monitor loop for large, complex catalogs spanning PIM, ERP, and multiple storefronts. They coined Agentic Commerce Optimization (ACO) and serve it well at that scale. eCommerce Insights is narrower by design: Shopify-first, recommendations-first, no required distribution layer. If your catalog lives in Shopify admin, eCommerce Insights skips the integration complexity.

Prompt-rewrite PDPs

Pasting a PDP into ChatGPT and asking for a rewrite is doable. It's not repeatable. The model doesn't know which SKUs are underperforming on which engines, which edits compound across a collection, or what your brand guidelines enforce. eCommerce Insights scores first, prescribes second, and applies changes at catalog scale with versioning and rollback.

How to rank products in ChatGPT