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Services / Product data enrichment

Product data enrichment

We fill and fix product data so your catalog is complete and consistent. The team works in your store admin, PIM or spreadsheet. They follow your taxonomy and style rules, and they flag what the source data cannot answer instead of guessing.

Request a pilot plan →See pricing

Supported tasks

  • ·Fill missing attributes from supplier sheets and manufacturer pages
  • ·Map new SKUs to your category tree and fix wrong categories
  • ·Standardize titles, units and sizes to your style guide
  • ·Check titles and images against your listing rules
  • ·Find and merge duplicate or incomplete listings
  • ·Review AI-written product descriptions before they go live

Sample input and output

Illustrative example. Invented data, not from a customer.

Sample input

  • Current listing: title "trail runner x2 mens blk 10" · category "Shoes" · color (blank) · size (blank) · upper material (blank) · weight (blank)
  • Supplier sheet: Trail Runner X2, men's, black, US 10, mesh upper, rubber sole
  • Your title rule: Product name + gender + product type + color

Sample output

  • Title: Trail Runner X2 Men's Running Shoe, Black
  • Category: Shoes > Men's > Running
  • Color: Black
  • Size: US 10
  • Upper material: Mesh
  • Weight: left blank and flagged: the supplier sheet does not list it

How it works

  1. 1

    You share the catalog rules. Send your taxonomy, style guide, a sample of listings and access to the tool.

  2. 2

    We train and build a gold set. The team trains on your rules. We build a set of listings with known-correct values and confirm it with you.

  3. 3

    The team enriches live listings. They work in your tool. Unclear category or attribute calls go to the team lead.

  4. 4

    You get a weekly report. Listings done, QA sample results, error types and open questions.

Quality checks

The team lead checks: category and attribute questions, and keeps a list of decisions. The team lead also tracks each person's QA results.

QA reviewers sample: a share of finished listings, re-checked against the source data and your style rules. The report shows error types, such as wrong category, missing attribute or style break.

What this means: every listing is handled by one trained person. QA re-checks a sample, not every listing. The weekly report shows the sample size and the acceptance rate.

How we check quality →

Pricing scope

  • $5 per person-hour (standard tasks): attribute filling, categorization, title and style fixes, and duplicate cleanup, in English.
  • Quoted after our ops team reviews the task: languages other than English, technical products that need specialist knowledge (for example electrical specifications), or building a new taxonomy.

FAQ

Which tools do you work in?

Your store admin, PIM, marketplace seller portal or spreadsheet, on accounts you create for us.

Do you guess missing values?

No. If the source does not say, we leave the field blank and flag it. The weekly report lists what is missing, so you can ask the supplier.

Can you review AI-written product descriptions?

Yes. We check them against your source data and style rules, and correct them before they go live. See AI output review.

How many listings can a team do each week?

It depends on the task and the data. Our ops team reviews a sample and sizes the team in your pilot plan. The weekly report shows the real numbers.

Try it on your own catalog for two weeks.

Send your style rules and a sample of listings. We email a pilot plan with a quote.

Request a pilot plan →