Shopper valuation system and related methods

A shopper valuation server comprising:

• a processor and an associated memory configured to
• obtain historical purchase data associated with a plurality of shoppers at a given retailer,
• apply a machine learning algorithm to determine a corresponding shopper value for each of the plurality of shoppers at the given retailer, each shopper value being a dollar value representation of a value of the corresponding shopper to the given retailer,
• obtain historical purchase data associated with a given shopper at the given retailer,
• apply the machine learning algorithm to determine a shopper value for the given shopper based upon the historical purchase data for the given shopper, the corresponding shopper values for each of the plurality of shoppers, and the historical purchase data for the plurality of shoppers,
• update the machine learning algorithm based upon the shopper value for the given shopper to train the machine learning algorithm to assign shopper values to further given shoppers,
• generate and communicate a notification to a user device associated with the given shopper soliciting the given shopper to accept or deny enrollment in a retailer loyalty program for payment to the given shopper of the shopper value for the given shopper,
• generate a shopper identifier for a loyalty account associated with the given shopper based upon enrollment of the given shopper in the retailer loyalty program, and assign the shopper value for the given shopper to the loyalty account based upon the shopper identifier, and
• train the machine learning algorithm based upon whether the given shopper accepted or denied the enrollment in the retailer loyalty program so that the machine learning algorithm adjusts the shopper value to obtain acceptance of the enrollment in the retailer loyalty program.

A method of valuating a shopper comprising:

• using a shopper valuation server to
• obtain historical purchase data associated with a plurality of shoppers at a given retailer,
• apply a machine learning algorithm to determine a corresponding shopper value for each of the plurality of shoppers at the given retailer, each shopper value being a dollar value representation of a value of the corresponding shopper to the given retailer,
• obtain historical purchase data associated with a given shopper at the given retailer,
• apply the machine learning algorithm to determine a shopper value for the given shopper based upon the historical purchase data for the given shopper, the corresponding shopper values for each of the plurality of shoppers, and the historical purchase data for the plurality of shoppers,
• update the machine learning algorithm based upon the shopper value for the given shopper to train the machine learning algorithm to assign shopper values to further given shoppers,
• generate and communicate a notification to a user device associated with the given shopper soliciting the given shopper to accept or deny enrollment in a retailer loyalty program for payment to the given shopper of the shopper value for the given shopper,
• generate a shopper identifier for a loyalty account associated with the given shopper based upon enrollment of the given shopper in the retailer loyalty program, and assign the shopper value for the given shopper to the loyalty account based upon the shopper identifier, and
• train the machine learning algorithm based upon whether the given shopper accepted or denied the enrollment in the retailer loyalty program so that the machine learning algorithm adjusts the shopper value to obtain acceptance of the enrollment in the retailer loyalty program.

A non-transitory computer readable medium for valuating a shopper, the non-transitory computer readable medium comprising computer executable instructions that when executed by a processor cause the processor to perform operations comprising:

• obtaining historical purchase data associated with a plurality of shoppers at a given retailer;
• applying a machine learning algorithm to determine a corresponding shopper value for each of the plurality of shoppers at the given retailer, each shopper value being a dollar value representation of a value of the corresponding shopper to the given retailer;
• obtaining historical purchase data associated with the given shopper at the given retailer;
• applying the machine learning algorithm to determine a shopper value for the given shopper based upon the historical purchase data for the given shopper, the corresponding shopper values for each of the plurality of shoppers, and the historical purchase data for the plurality of shoppers;
• updating the machine learning algorithm based upon the shopper value for the given shopper to train the machine learning algorithm to assign shopper values to further given shoppers;
• generating and communicating a notification to the user device soliciting the given shopper to accept or deny enrollment in a retailer loyalty program for payment to the given shopper of the shopper value for the given shopper;
• generating a shopper identifier for a loyalty account associated with the given shopper based upon enrollment of the given shopper in the retailer loyalty program, and assigning the shopper value for the given shopper to the loyalty account based upon the shopper identifier;
• and
• training the machine learning algorithm based upon whether the given shopper accepted or denied the enrollment in the retailer loyalty program so that the machine learning algorithm adjusts the shopper value to obtain acceptance of the enrollment in the retailer loyalty program.