catalog intelligence platform

Your catalog isn't broken.
It's unmanaged.

Vendor feeds that break search on arrival. Attribute gaps that tank conversion. Cleanup projects that regress within months. CatalogIQ is the intelligence layer that scores, enriches, and governs your catalog — continuously.

75% organic traffic increase — 30 days, pet products retailer
1M+ SKUs scored and prioritized — enterprise industrial distributor
4x faster time to actionable catalog intelligence vs. manual audit
30 days from diagnostic to measurable improvement — across paid engagements
15–25%
Revenue lost to poor data quality
For distributors, it's vendor feeds that break search the day they arrive. For retailers, it's attribute gaps that silently kill conversion.
MIT Sloan Management Review
40%
Online returns from inaccurate product data
Inconsistent attributes across suppliers. Missing specs that left buyers guessing. The catalog was wrong — and your customers paid for it.
Akeneo / NRF Research
82%
AI/ML projects stall from data quality
AI shopping agents don't browse ten mediocre results. They parse structured data — and skip products with missing attributes entirely.
MIT Research
The Reframe

Projects decay. Systems compound.

Every distributor and retailer has tried to "fix the catalog." Many times. The pattern is always the same: audit, clean, celebrate, decay. Six months later, you're back where you started — except now you're fielding questions about why the last initiative didn't stick.

Distributors normalize a thousand vendor feeds, then watch them drift the next quarter. Retailers enrich product pages for a campaign, then ignore the other ten thousand SKUs. The effort is real. The model is wrong.

CatalogIQ replaces the cleanup-and-regress cycle with a continuous system that scores, enriches, benchmarks, and governs your catalog — permanently.

The Old WayThe CatalogIQ Way
Fix first, measure laterScore quality before fixing anything
Enrich everything equallyPrioritize by business impact
One-time cleanup projectsContinuous improvement loops
Generic AI content toolsPurpose-built for catalog complexity
Replace existing systemsIntelligence layer alongside your stack
Isolated deploymentsEvery deployment builds shared intelligence
The Continuous Catalog Cycle

Four stages. One continuous loop.

There is no "done." There is only current state and trajectory.

// 01
Score
Make catalog quality visible and measurable. For a distributor with 200 vendor feeds, scoring reveals which manufacturers are sending data that breaks your filters. For a retailer, it shows which categories have attribute gaps silently killing conversion.
// 02
Enrich
Fill gaps, normalize values, optimize content — prioritized by what drives discovery and conversion. For distributors, normalizing supplier taxonomy mismatches. For retailers, generating conversion-ready content with consistent brand voice.
// 03
Benchmark
Connect quality improvements to business outcomes. Learn which enrichment patterns actually move the needle on search conversion, zero-result rates, and return rates.
// 04
Govern
Validate new products at ingestion. Catch regressions before they compound. For distributors onboarding new suppliers every quarter, this is where catalog debt starts — or stops.
// Compounding Intelligence

CatalogIQ is architected so that every deployment contributes to a growing intelligence layer. The more catalogs we score and enrich across categories, verticals, and vendor types, the more precisely the system understands what good looks like — and where gaps carry the highest cost. That compounding knowledge becomes harder to replicate with every cycle.

Proof Points

From invisible gaps to measurable improvement.

Real results from organizations that stopped cleaning up and started building systems.

B2C Retailer · Pet Products
5,000-SKU Digital Retailer
Supplier-provided content was generic and inconsistent across brands. Nearly all products lacked structured metadata, with many categories showing 0% attribute coverage — killing search and conversion.
75%increase in organic traffic within 30 days
100%of catalog scored and enriched with structured metadata
B2B Industrial · Distribution
1M+ SKU Enterprise Distributor
Product data from hundreds of manufacturers — each with different formats, naming conventions, attribute structures. 75% of SKUs lacked coverage for digital discovery.
1M+SKUs scored and prioritized for phased enrichment
4xfaster time to actionable catalog intelligence
See All Results →
Who It's For

Your pain. Your language. Your catalog.

CatalogIQ serves organizations with complex catalogs — each with distinct pain points that trace back to the same upstream problem.

Primary

B2B Distributors

Every supplier sends data in a different format. Taxonomy mismatches break your filters. Duplicate listings erode buyer trust. Onboarding a new vendor means weeks of manual normalization.

CatalogIQ normalizes vendor feeds at ingestion, eliminates taxonomy mismatches, and establishes governance before bad data enters your catalog.
Primary

B2C Retailers

Thousands of SKUs from diverse suppliers with inconsistent attributes. Weak product content killing conversion. Brand voice fracturing across supplier-provided copy.

CatalogIQ scores your catalog across nine quality dimensions, enriches content for conversion and discovery, and maintains consistency at scale.

Manufacturers

Engineering-first product data that isn't commerce-ready. Channel-specific demands from Amazon, Walmart, and retail partners.

CatalogIQ transforms spec sheets into commerce-ready content and formats it for every downstream channel.

Marketplaces

Every new supplier brings catalog debt. Without upfront validation, poor-quality data compounds downstream.

CatalogIQ validates supplier catalogs at ingestion, establishing quality standards before bad data enters your marketplace.

Stop cleaning up.
Start compounding.

Get a free catalog quality assessment that shows you exactly where your catalog is leaking revenue — and what to fix first. No pitch. Just intelligence about your business you can't get anywhere else.