Systems and methods for service location optimization

A system for optimizing an operational characteristic of a service location, the system comprising:

• a data storage device storing instructions for optimizing an operational characteristic of a service location in an electronic storage medium;
• and
• a processor configured to execute the instructions to perform a method including:
• receiving past performance data for one or more operational characteristics for one or more reference service locations, wherein the past performance data comprises customer transactions from a plurality of operational POS terminals;
• receiving, from a user, a target value for an additional operational characteristic of a target service location;
• receiving operational data for one or more operational point of sale (POS) terminals for the target service location and/or from the reference service locations;
• training a machine learning model using the received past performance data and the received operational data for the operational POS terminals;
• calculating an average value of the additional operational characteristic for each of the operational POS terminals;
• determining a representative POS terminal as a POS terminal among the one or more operational POS terminals with the calculated average value of the additional operational characteristic that matches the target value for the additional operational characteristic;
• setting operational characteristics of a target POS terminal of the target service location to be equal to the operational characteristics of the representative POS terminal;
• receiving, from the target POS terminal, updated operational performance data representing completed transactions after the setting operational characteristics for the one or more operational characteristics;
• and
• retraining the machine learning model using the received operation characteristics and the received updated performance data for the operational POS terminals.

A non-transitory machine-readable medium storing instructions that, when executed by a computing system, causes the computing system to perform a method for optimizing an operational characteristic of a service location, the method including:

• receiving past performance data for one or more operational characteristics for one or more reference service locations, wherein the past performance data comprises customer transactions from a plurality of operational POS terminals;
• receiving, from a user, a target value for an additional operational characteristic of a target service location;
• receiving operational data for one or more operational point of sale (POS) terminals for the target service location and/or from the reference service locations;
• training a machine learning model using the received past performance data and the received operational data for the operational POS terminals;
• calculating an average value of the additional operational characteristic for each of the operational POS terminals;
• determining a representative POS terminal as a POS terminal among the one or more operational POS terminals with the calculated average value of the additional operational characteristic that matches the target value for the additional operational characteristic;
• setting operational characteristics of a target POS terminal of the target service location to be equal to the operational characteristics of the representative POS terminal;
• receiving, from the target POS terminal, updated operational performance data representing completed transactions after the setting operational characteristics for the one or more operational characteristics;
• and
• retraining the machine learning model using the received operation characteristics and the received updated performance data for the operational POS terminals.