Point-of-sale and retail transaction feeds

Point-of-sale data is a direct read on what sells, where and when. This guide covers POS and retail transaction feeds and how to source them responsibly.

Why POS data matters

Aggregated sales data reveals demand, pricing effects and market share faster than surveys. It powers category management, demand sensing and market analysis.

The data landscape

• Sales by product: volumes and value.
• By location and time: where and when.
• Pricing and promotion: effects on sales.
• Market share: across retailers.

Privacy boundary

POS data can be linked to individuals via loyalty or payment data, so used externally it is aggregated and anonymised. The GDPR applies where individuals are identifiable.

Common use cases

Demand sensing and forecasting, category and pricing management, market and competitor analysis, and supply planning.

Sourcing considerations

Panel coverage and representativeness vary, and licensing can be restrictive. Aggregation thresholds and provenance are central.

In a managed model

A managed partner can source aggregated POS and sales data with verified methodology and provenance.

Aggregated and representative

Aggregated POS data is a fast, direct read on demand, but it can be linked to individuals via loyalty or payment data, so external use requires aggregation and anonymisation under the GDPR. Panel coverage and representativeness vary, so check methodology.

Licensing and provenance

Licensing can be restrictive, and aggregation thresholds and provenance are central to credible demand, pricing and market analysis.

Sources & further reading

• Retail-measurement and panel providers.
• Eurostat: retail statistics.
• EUR-Lex: Regulation (EU) 2016/679 (GDPR).
• Industry codes for transaction data.