The platform is built. The UX is beautiful. The filters are there. But the product data that makes it all work — the specs, the attributes, the descriptions — wasn't part of the budget. It never is.
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Responsible for conversion — but blocked by product pages that don't have the data to convert
Running a team that can't keep up with incoming supplier data and growing enrichment backlog
Launching new ranges that go live 4–6 weeks after competitors because data isn't ready on day one
Missing structured data markup and filterable attributes that drive organic product search rankings
Retail digital transformation projects follow the same pattern: 18 months on the platform, 6 months on the UX, 3 months on integrations — and then someone asks "what about the product data?" at the end of phase one. The data was never scoped. The budget was never allocated. The suppliers were never briefed. Go-live day arrives and the product pages have a title, a price, and nothing else.
The conversion cost is invisible until you measure it. Customers who land on a product page without specs, without comparison attributes, without filterable facets — they don't buy. They leave. They go to a competitor who has the data. Your conversion rate tells you something is wrong but not what. It's the missing attributes. It's always the missing attributes.
And the supplier problem compounds everything. You need data from 200 suppliers. Each one uses a different format. Each one sends back something different. Your team spends weeks cleaning it. The range goes live late. The competitor who had better supplier processes was live two weeks ago. Their products are ranking. Their products have reviews. You're still importing.
Each one has a different budget owner, a different urgency, and a different ROI. Most retailers have all four.
Brand, voltage, colour, and size filters show nothing — not because your site is broken, but because the product records don't have the values. AI extracts and structures every attribute from your existing content. Filters start working. Conversion improves.
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Replace the spreadsheet chase with an AI-powered portal. Suppliers confirm pre-filled data instead of typing from scratch. Completion rates go from ~40% to 80%+. Data arrives in days, not weeks.
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Supplier portal, overnight enrichment, AI descriptions, quality gates. The pipeline that turns raw supplier data into a publish-ready product record — without your team touching a spreadsheet.
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AI enriches 50,000 SKUs overnight. Your team reviews the 4% it wasn't confident about. The backlog clears. It doesn't grow back.
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Six platform capabilities — used together, or started with the one that fixes your biggest problem first.
AI-powered portal that pre-fills from supplier URLs. Suppliers confirm, not type. Completion 80%+.
Explore →AI fills every attribute gap at catalogue scale. Overnight. Confidence-scored. Reviewed by exception.
Explore →Extracts structured attributes from titles, descriptions, PDFs and URLs. The data that's already there, made filterable.
Explore →Descriptions grounded in real product attributes. Four tones. Approve before publish. No hallucinated specs.
Explore →AI builds your attribute schema for any category in minutes — not a 6-month discovery project.
Explore →Completeness scoring and publish gates. Products that meet your standard go through. Everything else doesn't.
Explore →You're here.
200 suppliers. 80,000 SKUs. A data team that's drowning. SKU Launch was built for your scale.
Read more →Seller listings rejected. Products downranked. Required attributes missing at scale. We fix the data problem that's costing you marketplace position.
Read more →Book 30 minutes. We'll run a completeness audit on a sample of your product pages — and show you exactly what's missing, what it's costing, and how fast AI can fix it.
Product data enrichment that actually gets done — so your product pages convert, your search works, and your team stops living in spreadsheets.
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