A computer-implemented method of generating contextual feedback forms, the method comprising:
- requesting, by a point-of-sale (POS) processor of a POS device communicatively coupled with a server, an authorization of a customer transaction from a payment card issuer server;
- requesting, by the POS processor, an encrypted copy of a payment card token from a card issuer that generated the payment card token and mapped the payment card token to a card number;
- generating, by the POS processor, a customer transaction record for the customer transaction;
- linking, by the POS processor, the encrypted copy of the payment card token with the customer transaction record
- transmitting, by the POS processor, the customer transaction record linked with the encrypted copy of the payment card token to a server processor of the server;
- receiving, by the server processor from the POS processor, the customer transaction record linked with the encrypted copy of the payment card token;
- decrypting, by the server processor, the encrypted copy of the payment card token;
- associating, by the server processor, the decrypted copy of the payment card token with a customer account in the transaction database;
- storing, by the transaction database, customer-owned customer transaction records associated with customer accounts;
- storing, by a reviews database, customer reviews;
- obtaining, by the server processor from one or more data stores, at least one attribute associated with a customer transaction record;
- obtaining, by the server processor from the one or more data stores, at least one keyword associated with the at least one attribute;
- obtaining, by the server processor from a machine learning library, at least one contextual review form parameter associated with the at least one keyword, the at least one contextual review form parameter logically associated with a type of product or service listed in the customer transaction record, wherein the method further comprises:
- maintaining, by the machine learning library, a corpus of information it discovers from at least one of contextual review form parameters used in past received reviews, or contextual review form parameters defined or selected by users when customizing review forms;
- detecting, by the machine learning library, changes made by reviewers to past contextual review form parameters for a product or service listed in the customer transaction record;
- and
- updating, by the machine learning library, responsive to the changes, a lookup table of keywords and associated contextual review form parameters;
- generating, by the server processor, a contextual review form comprising at least one parameter field comprising a choice of different parameters logically associated with the type of product or service listed in the customer transaction record;
- sending, by the server processor to a mobile device or a computer associated with the customer account, the contextual review form;
- receiving, by the server processor from the mobile device or computer associated with the customer account, contextual review form data;
- sending, by the server processor to the machine learning library, a user-choice parameter selected from at least one parameter field in the contextual review form data;
- and
- storing, by the reviews database, the contextual review form data,
- wherein the corpus of information maintained by the machine learning library is updated responsive to the storing of the contextual review form data;
- and
- wherein:
- the at least one parameter field comprises an option for a user to define a user-defined parameter;
- the method further comprises:
- updating, by the server processor, a lookup table in the machine learning library to include a new user-defined parameter;
- and
- including, by the server processor, the new user-defined parameter as a selection option in parameter fields of future contextual review forms in response to a determination that a set number of received contextual review form data comprise the new user-defined parameter.