There are two primary types of sales data: POS (Point of Sale) and Wholesale data. This is an overview of POS data types, and the key metrics and common use cases that POS data supports.
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It is important to distinguish between POS (Point of Sale) sales data and Wholesale sales data to effectively manage and utilize the different types of sales data available for your retail and digital sales channels. Knowing the difference helps you determine when and how to use each.
Wholesale data tracks the sale of products to retailers or distributors, which makes them available for POS consumer sales. For more information, skip to the next page: .
POS (Point of Sale) data is the information collected when a customer completes a purchase, whether in a retail store or online. This data provides a detailed view of how products are performing by sales location and time period, focusing on the final consumer sale.
Daasity ingests three types of POS data: direct-to-consumer (D2C), retailer portals, and syndicated data providers. It provides dashboards specific to each data source and cross-channel analytical use cases. Additionally, Daasity integrates all POS data sources into its Omnichannel data model and reporting suite, enabling easy tracking of sales performance by product, date, and across all sales and reporting channels.
Daasity integrates with three main types of POS data sources, each offering distinct insights and serving unique use cases:
Retail Portals
Retail portals provide sales, inventory, and distribution data directly from retailers to brands and suppliers. This data is typically limited to company-owned data, with metrics by item, store (or retailer-defined market areas), and daily or weekly levels. Data dimensions and metrics vary by retailer.
Use Cases:
Sales Managers: Monitor product performance, identify low-performing items, detect out-of-stock issues, and spot store voids.
Sales Operations Teams: Track sell-through rates and manage inventory levels to optimize stock availability and maximize sales potential.
Data Access and Management:
Data is often delivered via CSV files, either downloaded from portals or through automated services like Daasity.
Some data may require automated EDI data exchange, necessitating an EDI provider to translate the EDI format into a readable spreadsheet.
Syndicated Data Providers
Syndicated data is aggregated and reported by third-party providers like SPINS, Nielsen, and Circana. This data includes competitive category information at the UPC and category levels.
Brands use syndicated data to monitor market trends, analyze category performance, and benchmark competitively across retailers and regions. This data informs product development, promotional strategies, pricing tactics, and brand positioning.
Note: A contractual relationship with a syndicated data provider is required. For assistance,
For more details on how to leverage syndicated data for market and strategic analysis, check out our guide, .
Direct-to-Consumer (D2C) and Owned Retail Data
This data comes from sales made directly to consumers through a brand’s own channels, such as Shopify websites or owned retail stores. It includes transaction-level data and customer details.
Brands use this data to gain insights into customer behavior, optimize customer experiences, and enhance acquisition strategies through targeted digital campaigns and retention efforts.
