Catalog Enrichment

Turn messy catalogs into conversion-ready data

Missing attributes, inconsistent taxonomy, duplicate SKUs, weak descriptions — the silent killers of catalog conversion. We enrich 1,000 to 10M+ SKUs with structured attributes, brand-voice descriptions, and dedupe — at 95-99% accuracy.

30-200 fields  ·  Google + GS1  ·  Resize + BG removal
before · after · sku enrichmentLIVE
Title quality
Generic 9 words → SEO 18 words
+200%
Attribute fields
4 of 30 → 28 of 30
+93%
Images
1 low-res → 5 HD + alt
Std
GTIN matched
Missing → Verified
100%
qa-reviewed enrichment · sample sku
Attribute backfill
30-200 fields
Per category schema
Taxonomy mapping
Google + GS1
Hierarchical
Image standardization
Resize + BG removal
HD output
Multi-language
9 languages
Brand-voice
What we capture

Structured data, ready for your team.

01

Attribute completion

Color, size, material, dimensions, weight — 30-200 fields filled.

02

Taxonomy mapping

Map products to your category tree, Google Product Taxonomy, GS1.

03

Title standardization

Brand → Product → Key attribute pattern across catalog.

04

Description rewrite

SEO-friendly, brand-voice-consistent descriptions.

05

Image standardization

Resize, background removal, quality flagging, brand sourcing.

06

Identifier matching

GTIN, UPC, EAN, MPN, ASIN cross-mapping with dedupe.

07

Duplicate detection

SKU-level dedupe across variants and listings.

08

Multi-language localization

EN, HI, AR, DE, FR, ES, PT, ZH translations.

09

Compliance attributes

EU energy labels, CE marks, recycle codes — structured.

Why this matters

The market signals driving demand for this data.

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Missing data = lost sales

50% of search filters fail when material/size/color is missing. Filter exit = lost conversion.

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Marketplace listing scores

Amazon, Walmart, Flipkart rank listings on completeness. Better data = better placement.

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AI search needs structure

Google AI Overviews, ChatGPT shopping rely on structured attributes. Unenriched = invisible.

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M&A catalog merges

When brands acquire other brands, catalog merge is a 6-month problem. We do it in 3-6 weeks.

Use cases

What teams do with this data.

New marketplace launch

Adapt catalog to Amazon / Walmart / Flipkart schema.

PIM migration

Backfill missing attributes during PIM platform switch.

Catalog merger (M&A)

Combine acquired brand catalogs — dedupe, normalize.

International expansion

Translate & localize for UAE, KSA, EU, LATAM.

AI search readiness

Structure data for AI Overviews, ChatGPT shopping.

Filter coverage

Backfill fields driving site search filters.

Image library standardize

Unify image sizes, backgrounds, watermarks.

Schema.org compliance

Generate Product markup for SEO rich-results.

Compliance audit fill

EU CSRD / EPR / energy-label compliance.

How it works

From request to first dataset in 24 hours.

STEP 01

Define scope

Categories, geos, refresh frequency.

STEP 02

Free sample

Sample dataset within 24 hours.

STEP 03

Production pipeline

Refresh at your chosen cadence.

STEP 04

Iterate & scale

Expand coverage as needs grow.

Questions, answered

FAQs

Attribute fill, taxonomy mapping, identifier matching (GTIN/UPC/EAN), description rewrite, image standardization, dedupe.

95-99% on GTIN-matched SKUs, 88-94% on title+brand+image matching for SKUs without identifiers. Manual QA on edge cases.

Yes — English, Hindi, Arabic, German, French, Spanish, Portuguese, Mandarin and more. Brand-voice consistent.

Resize, background removal, duplicate detection, quality scoring, sourcing additional images from brand DTC sites.

1,000 to 10M+ SKUs. Standard: 5-15 business days for 100K SKUs. Weekly batch delivery for ongoing.

Get a free sample dataset

See the exact fields, accuracy and format — for your products, on your target sites — before you spend a rupee or a dollar.

  • Sample delivered within 24 hours
  • Scoped to your real use case, not a generic demo
  • No obligation, no long contract

Tell us what you need

A specialist replies within one business day.