IP Library Granted Patent US 11,869,062
Granted Patent B2
US 11,869,062 · App. 17/333,128 · Granted Jan 9, 2024

Cross-entity recommendation services

Inventors: Christopher John Costello (Suwanee, GA); Matthew Robert Burris (Atlanta, GA); Itamar David Laserson (Givat Shmuel, IL); Norman Leonard Trujillo (Frisco, TX)
Assignee: NCR Voyix Corporation
G06Q30/0631G06Q20/20
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Quick Facts
Patent No.
US 11,869,062
App. No.
17/333,128
Granted
Jan 9, 2024
Kind
B2
Abstract

A cross-entity and cross-retailer platform is provided that captures transaction data, indexes, and stores the data in a cloud-accessible data store. A service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service also generates and maintains correlations between items, the transactions, geographical locations, retailers, and stores of the retailers. The correlations are provided as timely retail recommendations to the retailers and entities for suggested changes that are likely to optimize purchase transactions. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item.

Claims (21)

1. A method, comprising:

receiving, by a processor of a server, transaction data associated with a purchase transaction from a retailer;

identifying, by the processor, an entity other than the retailer from the transaction data;

updating or generating, by the processor, a correlation based on items included in the purchase transaction data and based on other transaction data associated with other purchase transactions of the retailer and of other retailers, wherein updating or generating further includes updating an existing correlation as the correlation based on a deviation determined from the transaction data with the other transaction data; and

providing, by the processor, a recommendation to a system of the entity via an application programming interface (API) based on the correlation and providing data graphs corresponding to relevant data that supports the recommendation through an interface accessible to the entity based on the correlation, wherein the recommendation relevant to increasing sales of at least one of the items by the entity through the retailer.

2. The method of claim 1 further comprising:

obtaining, by the processor, a purchase transaction workflow for the entity; and

processing, by the processor, the purchase transaction workflow using the transaction data and the other transaction data.

3. The method of claim 2 further comprising:

providing, by the processor, select data produced from the processing to an internal system of the entity using the API.

4. The method of claim 2 further comprising:

obtaining, by the processor, a retailer purchase transaction workflow for the retailer;

processing, by the processor, the retailer purchase transaction workflow using the transaction data and the other transaction data.

5. The method of claim 4 further comprising:

providing, by the processor, select data produced from the processing of the retailer purchase transaction workflow to an internal system of the retailer using the API.

6. The method of claim 1 , wherein updating or generating further includes generating the correlation based on entity-specific criteria associated with the entity.

7. The method of claim 1 , wherein updating or generating further includes deriving the correlation based on a basket analysis of the items and other items associated with each of the other purchase transactions.

8. The method of claim 7 , wherein deriving further includes processing the basket analysis based on calculated frequencies with which each of the items and each of the other items are purchased in combinations with one another within a single purchase transaction.

9. The method of claim 7 , wherein deriving further includes processing the basket analysis based on calculated frequencies with which each of the items and each of the other items are purchased in combinations with one another during a time of year or a season of the year that is associated with the purchase transaction.

10. The method of claim 7 , wherein deriving further includes processing the basket analysis based on calculated frequencies with which each of the items and each of the other items are purchased in combinations with one another at a geographic location or at a store location for a store associated with where the purchase transaction is being performed.

11. The method of claim 1 , wherein providing further includes providing the recommendation as a suggestion to request changes in items' placements within a store where the purchase transaction is being performed, to change or add a promotion for a combination of the items and other items associated with each of the other purchase transactions, to vary assortments of the items and the other items based on a current time of year or a current season of the year associated with the purchase transaction, or to change an existing marketing strategy for the store or a geographical region associated with the store.

Assignments (3)
CHANGE OF NAME Recorded Nov 9, 2023
From: NCR CORPORATION
To: NCR VOYIX CORPORATION
Reel/Frame 065532/0893 →
SECURITY INTEREST Recorded Oct 25, 2023
From: NCR VOYIX CORPORATION
To: BANK OF AMERICA, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 065346/0168 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 28, 2021
From: COSTELLO, CHRISTOPHER JOHN; BURRIS, MATTHEW ROBERT; LASERSON, ITAMAR DAVID; TRUJILLO, NORMAN LEONARD
To: NCR CORPORATION
Reel/Frame 056380/0462 →
Continuity (1)
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