How Newell Brands Worked with It'sRapid.AI to Fill 68,000+ Missing Product Attributes
Newell Brands used It'sRapid's AI-powered data enrichment to fill 68,000+ missing product attributes across nearly 3,000 SKUs, dramatically reducing manual effort and increasing required attribute completeness from 8% to 92%.
Newell Brands, home to some of the world's most recognized consumer products — Sharpie, Rubbermaid, and Marmot among them — faced a challenge that quietly undermines digital shelf performance at scale: incomplete product data. Required attributes were missing across thousands of SKUs, and every gap meant weaker search placement, lower-quality product pages, and retailer readiness risk.
With It'sRapid, Newell turned incomplete source data into retailer-ready product data across ~3,000 SKUs, filling 68,000+ attributes and lifting required attribute completion from 8% to 92%.
"It'sRapid has significantly improved the completeness of our product data across thousands of SKUs. Their AI-powered approach makes it easier to enrich product data at scale, reducing manual effort and keeping our products retail-ready."
The Challenge
Retailers require a long list of product attributes before content can go live: dimensions, materials, specifications, claims, compliance details and more. For Newell, a portfolio spanning many categories and retailer requirements, the required-attribute gap was wide: on average, only 8% of required attributes were complete in the source data.
Filling that gap manually is slow, error-prone and impossible to sustain across thousands of SKUs, and every incomplete attribute delays listing, weakens search visibility, and puts the digital shelf at a disadvantage against better-prepared competitors.
Incomplete data also blocked item setup itself. Because items can only be set up with complete attribute data, Newell couldn't automatically publish content updates; every refresh was gated by manual work to fill in the gaps first.
The It'sRapid Solution
It'sRapid used a flexible, AI-powered enrichment approach to complete Newell's required attributes at scale:
Analyze source product data across ~3,000 SKUs to identify every required attribute gap
Fill attributes with a flexible AI-powered approach that adapts across categories and retailer requirements
Deliver retailer-ready product data at scale: 68,000+ attributes filled
Verify with confidence: attributes that could not be confidently verified (or were not applicable) were flagged, not guessed
The result is a repeatable enrichment engine: source data goes in, retailer-ready product data comes out, fast enough to keep pace with new SKUs, new categories and changing retailer requirements.
From 8% to 92%: Before and After It'sRapid
Average completion rate of required attributes across ~3,000 SKUs.
- ~3,000 SKUs processed
- 68,000+ attributes filled
Remaining gaps reflect attributes that could not be confidently verified or were not applicable. Accuracy over guesswork.
The Impact
By completing required attributes with an AI-powered, verification-first approach, Newell unlocked both operational and commercial value:
- —Only 8% of required attributes complete
- —Manual enrichment across thousands of SKUs
- —Item setup blocked: no automatic content publishing
- —Inconsistent data across categories
- —Listings delayed by missing attributes
- →92% required attribute completion
- →Item setup no longer blocked, so content updates publish automatically
- →Retailer-ready data across ~3,000 SKUs
- →68,000+ attributes filled at scale
- →Flexible approach across retailer requirements
- →Confidence-verified fills, gaps flagged transparently
The result: complete, retailer-ready product data that strengthens search placement and speeds up listings.
The Takeaway
Consumer brands face a hard truth: retailers keep raising required-attribute bars, and no team can manually enrich thousands of SKUs fast enough to keep up.
Newell's transformation shows what's possible with the right foundation. A flexible, AI-powered enrichment approach turned incomplete data into retailer-ready product data, with accuracy held to a higher standard than manual work: attributes were filled only when they could be confidently verified.
It's not about chasing attribute counts. It's about complete, retailer-ready product data that keeps pace with the shelf.
Frequently Asked Questions
- What did Newell Brands achieve with It'sRapid?
- It'sRapid filled 68,000+ required product attributes across ~3,000 Newell Brands SKUs, lifting required attribute completion from 8% to 92% and turning incomplete source data into retailer-ready product data.
- Why is required attribute completion important?
- Retailers require a long list of product attributes before content can go live. Missing attributes delay listings, weaken search placement, and block item setup, so incomplete data directly limits digital shelf performance.
- How were the missing attributes filled?
- With a flexible, AI-powered enrichment approach that adapts across categories and retailer requirements. Attributes were filled only when they could be confidently verified; gaps were flagged transparently rather than guessed.
- How did incomplete data affect item setup?
- Items can only be set up with complete attribute data, so Newell could not automatically publish content updates until the gaps were filled. Completing required attributes unblocked automatic publishing.