AnthologyAI - US Equities

**Overview**
This near-real-time information provides a detailed view of consumer spending, primary checking account activity, location data, and retail transaction across 20+ demographics, ensuring a representative sample as well as accurate and reliable analysis.

**Use case 1**

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.

*Caden Data Inputs*

- Spend Pack (Credit Card and Bank Account Data)
- Retail Pack (Amazon.com, Walmart, Target)
- Location Pack

*Caden Metrics*

- Average Price by Item [Including History]
- Average Total Transaction Value (Retailer)
- Average Total Transaction Value (FMCG)
- Loyalty Index by Brand (Retailer)
- Average Transaction Value (Retailer) [Average Ticket]
- Share of Wallet by Retailer against competitive set (by GMV)
- Share of Wallet by Retailer against competitive set (by # of Transactions)

*Data Overlays*

- Retailer FMCG Promotions
- Retailer Shelf Placement

*Analyses*

- Two Way Analysis of Variance for Average Order Size / Transaction Frequency with or without Promotions
- By Geography
- By Demo
- Seasonally adjusted Demand Forecast with Price Sensitivity Overlay
- Brick and Mortar Bounce/Conversion Rate Metrics (with and without promotions, and by % value discount for promotion)

**Use case 2**

A new neobank / fintech launch which is a subsidiary of a US regional lender is trying to create a holistic marketing and customer segmentation strategy that aligns with current investment trends. They’ve heard that online retail brokerages like Robinhood and e-Trade are suffering from periodic and sustained withdrawals and lagging earnings and want to know if there’s an opportunity to capture investments moving out of them towards more conservative asset managers like T Rowe Price, Fidelity, Fisher Investments etc.

*Caden Data Inputs:*

Spend Pack (Credit Card and Bank Account Data)

*Caden Metrics:*

- Total Spend Per Investment Platform
- Number of Transactions Per Investment Platform
- Avg Transaction Amount Per Investment Platform
- Min Transaction Amount Per Investment Platform
- Max Transaction Amount Per Investment Platform
- Median Transaction Amount Per Investment Platform
- Variance of Transaction Amount Per Investment Platform
- Number of Transactions Per Online Brokerage
- Avg Transaction Amount Per Online Brokerage
- Min Transaction Amount Per Online Brokerage
- Max Transaction Amount Per Online Brokerage
- Median Transaction Amount Per Online Brokerage
- Variance of Transaction Amount Per Online Brokerage
- Share of Wallet (Every Investment Platform vs. the Field)
- Share of Wallet (Every Investment Platform vs. Total FinServ transfers)

*Caden Data Overlay:*

Product Assortment by Investment Platform, Asset Manager, and Online Brokerage

*Analyses:*

- Consumer Segmentation and Profiling for Various in and outflows to Online Brokerages, Asset Managers and (multi-service) Neobanks
- Propensity model for likelihood to open a new Alternative Asset Management product
- Descriptive statistics on average deposit size, deposit frequency and number of platforms used
- MBA (Market Basket) for various AM/Brokerages used.
- CBLRM (Category Based Recommendation) for Product Assortment

**Product details**

For more implementation details, refer to the embedded notebooks.