Numerator: Household Purchase Information
Detailed transaction-level data across 1 Million+ US Households and all channels
Numerator OmniPanel data is a collection of millions of US Households and their detailed transaction-level data. The data has been anonymized for usage across a number of different marketing and market research applications, such as, demand forecasting modeling, consumer behavior research, localized elasticities, and media modeling.
The data included is the raw, disaggregated panel data sourced from over a billion receipts that Numerator has collected from households in addition to e-receipts collected electronically. It is one of the only sources of data where a full omnichannel picture can be seen for each individual household.
This data set has a standard format, however, the scope can be personalized based on time periods, product category, and retail outlet scopes. Please contact us at firstname.lastname@example.org for more information.
Sample Tables Included:
- Daily Transaction data for households 2016-Present
- All retail & non-retail channels (Grocery Stores, Mass, Club, Drug, Dollar, Online, QSR/Fast Casual, Apparel, Electronics, Craft, and 30 more!)
- All product categories (Grocery, Household goods, Health & Beauty, Pet, Baby, Electronics, Durable goods, Soft goods, etc)
Sample Fields Included (Data Dictionary provided upon request):
- Date – Retail Outlet Categorization (Retail Channel, Retail Corporate, Retail Banner Name)
- Product Categorization (Sector, Department, Major Category, Category)
- Brand Categorization (Parent Brand, Brand)
- Product Metrics (Units, Unit Price, Total Spent)
- Basket Metrics (Basket Total)
Example Use Case:
Use information from a category you compete in to understand general sales trends across channels and link to demand forecast models or marketing plans. Especially in channels and outlets that are blind spots for your point-of-sale data like Online, Club, Convenience stores, Regional Food, Private Label Grocery stores like Aldi, etc.
About the Provider:
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