CPG Retail and Distributor Data Samples

Crisp facilitates the integration, access, and exchange of retail data between CPG brands, retailers, and distributors – providing unprecedented visibility to optimize retail sales and supply chains.

Crisp's platform offers organizations a clean, real-time feed of sales and inventory intelligence in one place, transforming disparate retail data into a competitive advantage.

Types of data provided via Crisp:

- **Supply chain.** DC fill rates, DC inventory, DC to store shipments, store inventory and more.
Point of Sales, pricing and promotions. POS data at store, product, date granularity. In most cases updated daily with the latest information available.
- **Category sales data.** For category captains, Crisp will provide the full depth and breadth of category data the retailers provide.
- **Much more.** Crisp also provides many other datasets, depending on source availability. For example, age of inventory and spoilage risk, chargebacks and deductions.

Not only does Crisp automate the ingestion of retailer and distributor data, we also can take care of cleaning and organizing the data so you can spend less time on data prep and more time on actual analysis.

The Crisp Platform provides three different types of data, with different levels of pre-processing:

- **Source data.** For when you are developing a replacement for existing data pipelines and / or want to do your own data modeling. The source data schemata closely resembles what the upstream data source provides, so you can leverage any pre-existing modeling experience with this data.
- **Normalized data.** For when you are developing retailer or distributor specific solutions and want to leverage source-specific attributes. The data model is a fully normalized schema and naming conventions are consistent across all data sources, making it easy to mix and match retailers in analyses.
- **Harmonized data.** For when you are developing cross-retailer solutions, and it’s acceptable to use a narrower subset of data that is common across multiple data sources. The data model is built on the normalized model and combines common data elements, such as POS and inventory into a harmonized model across multiple retailers and distributors.

With Crisp, you can easily mix and match data from the models as you see fit.

The applications of the data are vast, but some common use cases are:

- **Reduce out of stock.** Use retailer inventory and sales data to easily detect out of stock and availability issues. Use daily DC order and inventory data to optimize DC replenishment and maximize fill rates.
- **Increase distribution.** Use sales performance across retailers and perfect store location information to analyze historical performance and identify new regions and retailers to break into.
- **Increase velocity.** Use retailer sales data to plan, execute and measure successful price promotions and store demos.
- **Improve Digital Marketing.** Combine retailer inventory and sales with digital marketing data to measure sales lift and inform future media campaigns.

The sample data sets provided in this free offering include the following data models:
- Harmonized Retailer Sales
- Harmonized Retailer Store Inventory
- Harmonized Retailer Distribution Center Inventory

The data attributes contained within the above models include but are not limited to:
- Product Name
- Product UPC
- Store
- Store Latitude and Longitude
- Sales Amount
- Sales Quantity
- Distribution Center
- Distribution Center Latitude and Longitude
- On Hand Quantity

More information about our sample data set can be found at https://support.gocrisp.com/hc/en-us/articles/15796965033751.