Square, Inc.

Block, Inc.

Gian Perrone

Abhay Raj Kumar

Mai Leduc

Rong Yan

Dan Hipschman

John Berian James

Mason Ng

Berian James

John Coughlin

Transaction modification based on modeled profiles is described. In an example, transaction data can be received from merchant computing devices associated with merchants associated with a payment processing system. A model can be trained to generate profiles using, as training data, one or more of merchant data, buyer data, or the transaction data. Upon receiving an indication of a particular transaction between a buyer and a merchant, it can be determined that a characteristic of the transaction corresponds to a profile of the generated profiles. Based on the determination that the characteristic corresponds to the profile and the transaction data, a recommendation can be generated for a modification of the transaction to add an item or replace an item.

Transaction modification based on modeled profiles

A service provider may receive item price information and/or point of sale (POS) transaction information from a plurality of merchant devices associated with a plurality of merchants. The service provider may categorize the plurality of merchants according to the types of items offered by the respective merchants, and may further categorize the merchants according to the locations at which they conduct business. The service provider may subsequently determine a price recommendation or other pricing information for a particular item offered by a particular merchant. A merchant device of the particular merchant may present the pricing information in a user interface that enables the merchant to view projected sales at various different price points. Further, the merchant may be able to specify one or more factors used for determining the recommend price, such as a desired business model, a desired clientele, a desired profit margin, or the like.

Determining pricing information from merchant data

Transaction modification based on modeled profiles is described. In an example, transaction data can be received by a payment processing system. The payment processing system can generate, using a trained model, profiles. Based at least in part on (i) receiving an indication that a buyer and a merchant are engaged in, or likely to be engaged in, a transaction and (ii) determining that a characteristic of the transaction corresponds to a profile, generating a communication to enable the buyer or the merchant to modify the transaction in association with processing of the transaction.

Buyer profile management is described herein. In an example, a payment processing service can store, in a database, buyer profiles associated with buyers involved in transactions with one or more merchants of the payment processing service. The payment processing service can receive transaction data associated with a new transaction between a buyer and a merchant and can determine whether the transaction data corresponds to any of the buyer profiles. Based at least in part on determining that the transaction data corresponds to one of the buyer profiles, the payment processing service can update the database storing the buyer profiles, wherein updating the database comprises merging two or more buyer profiles. A recommendation can be made based on the merged buyer profile prior to completion of the new transaction.

Buyer profile management

Techniques for providing items recommendations based on a state of a merchant device are described. For example, a determination of whether or not a merchant device is in an online mode or an offline mode may be made. When it is determined that the merchant device is in the online mode, a recommendation that is received for the current transaction may be presented. When it is determined that the merchant device is in the offline mode, a recommendation that is previously received may be presented. In other examples, other types of recommendations may be presented.

Determining item recommendations from merchant data

A service provider may receive transaction information from a plurality of merchant devices for a plurality of point of sale transactions conducted between buyers and merchants. The service provider can associate the transaction information with respective buyer profiles of a plurality of buyer profiles. In some examples, the service provider may determine a subset of the buyer profiles based on at least a portion of the buyer profiles in the subset including transaction information that is related to a particular one of the merchants. The service provider may further determine at least one characteristic associated with at least some of the buyer profiles in the subset, and may send a recommendation to the particular merchant related to the at least one characteristic. As an example, the recommendation may be for improving or optimizing the business of the particular merchant.

Determining recommendations from buyer information

A service provider may receive transaction information from a plurality of merchant devices for a plurality of point of sale (POS) transactions conducted between buyers and merchants. The service provider associates the transaction information with respective buyer profiles. The service provider may subsequently receive an indication of a first item selected by a particular buyer for a current POS transaction being conducted with a particular merchant. The service provider may determine a particular buyer profile to associate with the current transaction. Based at least in part on the particular buyer profile or the other buyer profiles, the service provider may determine a second item that has been purchased frequently together with the first item. The service provider sends a communication to the particular merchant to indicate that the particular merchant may wish to offer the second item to the particular buyer for inclusion in the current transaction.

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San Francisco, CA, United States of America

Gian Perrone