Mastercard International Incorporated

Prashanna S Tiwaree

Manash Bhattacharjee

Rohit Chauhan

Pablo Fourez

Gerardo Cardone

A gratuity analytics computing system, for generating gratuity analytics for a plurality of transactions of a customer at a service provider within a date range, is in communication with an electronic device of the service provider over an electronic network. The system includes a gratuity analytics computing device, a database including a memory in operable electronic communication with the gratuity analytics computing device, and a processor configured to: receive transaction data for the plurality of customer transactions occurring within the date range, match a plurality of authorization messages with a respective plurality of clearing messages, generate gratuity analytics for the plurality of customer transactions over the date range based on average tip data from the customer, and calculate a customer satisfaction score for one customer transaction of the plurality of customer transactions based on the generated gratuity analytics.

Systems and methods for generating customer satisfaction score

A message is generated, with the message including a URL (uniform resource locator). The URL points to a web location. The web location is for facilitating a payment to a payment recipient. The message is transmitted to a mobile device owned by the payment recipient.

Systems and methods for performing payment transactions using messaging service

A gratuity analytics computing device for generating gratuity analytics for one or more restaurants is provided. The gratuity analytics computing device includes a memory in communication with a processor. The processor programmed to receive a date range from a client computing device. The processor is further configured to receive transaction data for transactions occurring within the date range at a restaurant. The transaction data including a manager identifier, a time stamp, and an employee identifier associated with the transactions, the transaction data including authorization messages and clearing messages. The processor is further configured to match a plurality of authorization messages with a respective plurality of clearing messages. The processor is further configured to calculate tip data for the restaurant based on the plurality of matched messages, generate gratuity analytics for the restaurant over the date range based on the tip data, and display on a user interface of the client computing device the gratuity analytics.

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New York, NY, United States of America

Prashanna S Tiwaree