Product data for shops, marketplaces and partners
Good product data is infrastructure for growth.
We structure, clean, migrate and distribute product data so that shops, marketplaces, dealers and internal systems can use it reliably – from variations and attributes to content, media and channel-specific requirements.
From need to solution
Where product data causes problems
01Multiple versions of the truth
The ERP, PIM, shop and supplier files contain different values, with unclear ownership.
02Variation chaos
Products, variations, EANs, attributes and product families are not modelled consistently.
03Incomplete content
Technical master data alone is not enough for discoverability, buying decisions and marketplace requirements.
04Manual maintenance
Changes are copied channel by channel, making updates slow, error-prone and expensive.
05New channels take too long
Every marketplace or dealer needs its own formats, triggering another one-off process.
06Data quality stays invisible
Errors are only discovered during import, in the shop or by the customer.
Our commitment
From raw data to a usable product record
We define data ownership, models and quality rules. Sources are then consolidated, normalised, enriched, validated and prepared for each target system.
A good data model does more than reduce errors. It makes every subsequent channel integration faster.
From need to solution
What we deliver
01Data analysis & mapping
Identify sources, fields, identifiers and responsibilities.
02Cleaning & migration
Consolidate existing data and transfer it into new systems in a controlled way.
Explore the solution03Data enrichment
Add missing content, attributes, structure and media from reliable sources.
04Validation
Establish rules for required fields, formats, variations and channel-specific requirements.
05Distribution
Deliver data to the shop, Amazon, other marketplaces, dealers and partners.
06Automation
Turn recurring updates and checks into robust data flows.
Explore the solutionOur approach
From raw data to usable product information.
- 01
Assess the data
Analyse sources, variations, media, quality gaps and target-channel requirements.
- 02
Develop the model and rules
Define attributes, units, identifiers, variation relationships and data ownership.
- 03
Clean and enrich
Check and standardise information, then supplement it with reliable sources. Uncertain values are never invented.
- 04
Distribute with control
Convert data into the structures required by shops, Amazon, dealers or PIM systems and check the results.
- 05
Maintain quality over time
Clear responsibilities, checks and traceable processes prevent new data from recreating old problems.
Seeing the connections
AI can help. A sound factual basis remains essential.
AI can support tasks such as classification and drafting. Product identity, technical specifications, ingredients and assignments must not become guesswork as a result. We combine automation with sources, validation rules and deliberate approvals.
Connected where it counts