AnthologyAI - Row Level Retail Data

**Overview**
Basket-of-goods level data of retail purchases at major big box retailers and e-commerce sites captured in near real time. SKUs, pricing, fees, quantity, discounts, returns and many more data fields enable granular analysis of shopping behavior. Items map to brands, and when applicable brands are mapped to parent companies.

Included tables represent row-level retail transactions and the selection of one demographic attribute. (Income, age, state, education, etc)

**Use cases**

A US Long/Short Fundamental Hedge Fund is considering taking a position in Acme (ACME). The investment team wants to better understand the retailer’s pricing and promotions strategy/ philosophy as it is trying to grow and expand its national footprint. The investor wants to understand which types of pricing strategies or promotions will excel this retailer beyond its competitors. The options they are exploring are Everyday Low Prices (i.e. like Walmart), Dynamic / Cohort Based Pricing (i.e. Amazon) or High-Low Pricing / Event-driven Discounting (i.e. Target). To make that decision, they seek to compare pricing strategies of respective retailers and their impact on Brick and Mortar response rates, BOPIS (Buy Online, Pick-up in Store) and E-commerce value by frequency, efficacy and ROI impact.

**Product details**

Example table name: retail_income_row_level

Included fields:

- Alias
- Demographic*
- Order ID
- Order Date
- Order Status
- Order Broker
- Order Type
- Is Fuel Purchase
- Is Exchange
- Order Price
- Order Currency
- Order Subtotal
- Payment Card Type
- Ordered Item ID
- Item ID
- Item Name
- Ordered Quantity
- Item Adjustments
- Store ID
- Item Price
- Item Currency
- Item Discounts
- Unit Price
- Unit
- Item Brand
- Item Category
- Item Color
- Item Size
- Item Description
- Item Variants
- Store Zip Code
- Ticker

*elegibility dependent

**Additional Insights**

Please refer to the links in the product menu for additional documentation including samples & data dictionaries.