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Methods and systems for the sale of consumer services

  • US 10,402,760 B2
  • Filed: 11/15/2013
  • Issued: 09/03/2019
  • Est. Priority Date: 11/15/2012
  • Status: Active Grant
First Claim
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1. A computer-implemented method comprising:

  • (a) predicting, by at least one computer utilizing at least one processor, that a customer of a plurality of customers is likely to request a service, wherein the predicting in (a) is based on first historical data comprising attributes of different customers that have previously requested the service;

    (b) predicting, by the at least one computer utilizing the at least one processor, that one or more merchants of a plurality of merchants has a respective probability of being selected by the customer to provide the service that meets a threshold, wherein the predicting in (b) is based on second historical data comprising attributes of different merchants that have previously provided the service, the predicting in (b) comprising;

    training a machine learning classifier over a period of time, using the second historical data, to predict whether a particular customer would be likely to select a given merchant for scheduling an appointment for the service; and

    providing current attributes of the plurality of merchants and current attributes of the customer as inputs to the machine learning classifier and obtaining the predicted merchants as output of the classifier;

    (c) selecting, by the at least one computer utilizing the at least one processor, one of the predicted merchants based on one or more criteria;

    (d) scheduling the appointment for the service on a calendar of the customer and on a calendar of the selected merchant;

    (e) providing notification of the appointment to a customer device of the customer and a merchant device of the selected merchant;

    (f) determining a time of the scheduled service and a geographical location of the scheduled service;

    (g) identifying a plurality of previous appointments of the customer for one or more other services, the previous appointments having a pattern of being scheduled at times proximate to the time of the scheduled service, the previous appointments having a pattern of taking place at a geographical location same as or proximate to the geographical location of the scheduled service;

    (h) automatically scheduling on a calendar of the customer one or more appointments for one or more of the other services at one or more times proximate to the scheduled service;

    (i) predicting that the one or more appointments for the one or more other services are likely to require one or more electronic forms, wherein the predicting in (i) is based on third historical data comprising attributes of different merchants that have previously provided the other services and attributes of different users that have previously requested the other services;

    (j) automatically populating the one or more electronic forms with information associated with the customer based on a permission of the customer specified in a customer profile;

    (k) assigning a machine-readable unique barcode to the customer and storing a representation of the unique barcode in the customer profile;

    (l) tracking a location of the customer via a location tracking sensor of the customer device;

    (m) determining that the customer has arrived, based on information received via the location tracking sensor of the customer device, at a location of a merchant providing one of the other services;

    (n) in response to the determination of the arrival of the customer, causing the unique barcode of the customer to be presented on a display screen of the customer device; and

    (o) upon scanning the unique barcode by a scanning device at the location of the merchant providing one of the other services, registering the arrival of the customer and electronically issuing one or more of the electronic forms to the merchant providing one of the other services.

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