Product data
Sorting out the product data that blocks multichannel sales
I clean, merge and analyse product data from wholesalers, marketplaces, stores, CSV/XML files and APIs. The goal: less chaos, less manual work and better decisions on prices, margins, categories and your offer.
Who it's for
- Stores with a large number of products and many data sources
- Distributors and wholesalers working from manufacturer files
- Companies selling on marketplaces, where data requirements differ per channel
- Teams struggling with EANs, brands, categories, attributes or feeds
- Managers needing price, margin and product-profitability analysis
Typical problems
- A supplier sends a file that can't be imported directly
- Brand and manufacturer names are written several different ways
- Supplier categories don't match the store or marketplace categories
- Missing EANs, composition, manufacturer data, GPSR, photos or attributes
- The same product appears in several sources with different prices and descriptions
- It's unclear which products actually earn and which only generate turnover
- The product feed for Google, Ceneo or a marketplace has errors or incomplete data
What I implement
- Cleaning and standardising CSV, XML, XLSX files
- Merging data from many sources by EAN, SKU, name or other keys
- Deduplicating brands, manufacturers and categories
- Mapping supplier categories onto the store or marketplace structure
- Analysis of purchase prices, sale prices, margins and problem products
- Preparing product feeds or import files
- Preparing and mapping data for a PIM (e.g. Ergonode)
- Simple dashboards and reports for data-quality control
Example scenarios
04Category mapping
Supplier data has a different structure than the store. I build a category map and a mechanism that prepares the import file.
Product profitability analysis
I combine purchase prices, sale prices and channel data to flag products below the minimum margin.
Brand deduplication
I clean up brand and manufacturer name variants - e.g. the same brand spelled differently across many files.
Marketplace data prep
I complete and transform data so it meets the requirements of Allegro, Ceneo, eMAG or other channels.
How we work together
- 01
Identifying data sources and the business goal
- 02
Auditing data quality and spotting errors
- 03
Defining merge, cleaning and mapping rules
- 04
Preparing the output file, script or report
- 05
Testing on real data and corrections
- 06
Documenting the rules and recommendations for further cleanup
What you get
- A clean file or data-processing pipeline
- Mapping and cleaning rules
- A list of errors and gaps in the product data
- A price, margin or data-quality report
- A foundation for automation, a PIM or better multichannel sales
Business outcomes
- A consistent catalogue ready for multiple channels
- Faster product onboarding and updates
- Fewer returns caused by wrong product data
Not included
- I don't write a full product-description content strategy from scratch
- I don't replace a large PIM system if you genuinely need one - but I can help judge that moment
- I don't guarantee supplier data quality, but I can surface the errors and build a process to control them
Send a sample CSV/XML file or describe your product-data problem. I'll check what can be cleaned up and automated.
Book a consultation