Stop losing auction impressions to cryptic supplier titles and disapproved items in Google Merchant Center. Structure high-CTR titles using proven [Brand + Product Type + Key Attributes + Model] formulas and populate every mandatory Shopping attribute at raw compute cost.
See how raw, incomplete supplier feeds are parsed, validated against physical specs, and transformed into enriched PIM-ready content.
Typical raw supplier spreadsheet or ERP export with missing attributes, abbreviations, and messy formatting:
| g:id: | RUN-SHOE-992 |
|---|---|
| g:title_raw: | Pegasus 41 blk/wht str 43 |
| g:gtin: | 196969204815 |
| raw_notes: | Men running shoe, ReactX foam, engineered mesh, road running, 297g |
| g:google_product_category: | [MISSING - Merchant Center Warning] |
PIMplify acts as a non-destructive transformation layer. We read your raw supplier specs and write verified, structured attributes directly back to your designated fields.
Universal system compatibility: Running a custom or niche shop, PIM, or ERP system? We build and tailor the integration or feed format for your setup.
Keep short, clean product titles on your website while feeding Google Merchant Center rich 150-character search titles and complete attributes.
Upload your existing product export from Shopify, WooCommerce, Channable, or your PIM. No developer work or changes to your primary checkout feed required.
PIMplify front-loads high-intent keywords in the first 70 characters of [g:title], resolves missing specs via GTIN web grounding + AI vision, and maps exact Google Product Category IDs.
Import the enriched file as a Supplemental Feed in Google Merchant Center (matched on [g:id]) or sync directly into Channable, DataFeedWatch, or Shopify.
In this 8-minute walkthrough, see step-by-step how to connect your catalog, configure prompt guardrails, and enrich thousands of SKUs in the background with Google Vertex AI.
Click to see how PIMplify enriches product catalogs in seconds
Front-loads high-intent search terms in the first 70 visible characters using category templates (Apparel: Brand + Type + Gender + Material + Color + Size | Electronics: Brand + Model + Type + Key Spec + MPN).
Extracts and populates mandatory attributes like [g:color], [g:gender], [g:age_group], [g:material], and [g:size] from unstructured text while stripping promotional jargon and ALL CAPS.
Deterministically assigns every SKU to the deepest matching Google Product Taxonomy leaf node (numeric ID and full path) for sharper Performance Max bidding and lower CPCs.
Generates structured product_highlight bullet points and product_detail specification pairs that populate rich Google Shopping product cards and Free Listings.
Rule-based feed managers cannot invent missing attributes. PIMplify enriches the underlying fields first, exporting a clean Supplemental Feed for GMC, Channable, or Shopify.
Optimize 10,000 to 100,000+ Shopping SKUs at raw Google Cloud Vertex AI compute rates (~$0.0003 per item) without expensive per-SKU feed agency retainers.
Whether you want to build and manage AI prompts yourself, get a complete one-time catalog overhaul, or outsource everything to our product data specialists - we offer clear plans with fair-use AI compute included.
For in-house e-commerce teams wanting complete control
Full access to the PIMplify web platform. Build your own prompts, connect spreadsheets or feeds, and enrich thousands of SKUs at your own pace with AI included.
For webshops needing an urgent cleanup and attribute boost
We optimize and clean your entire existing product catalog once and for all. Fix missing attributes, conversion leaks, and Google Shopping feed errors.
For ambitious brands seeking 100% turnkey catalog operations
PIMplify acts as your external product data department. Our specialists engineer custom prompts, manually review new products, and ensure continuous sync.
Unlike legacy PIM software charging a 5x-10x premium on AI generation, PIMplify routes all batch workloads directly through Google Cloud Vertex AI at wholesale token rates. Enrich 10,000 SKUs for dollars, not thousands.