Methods and systems for tracking potential activity of a customer based on location

Abstract

Computer-implemented systems and methods for the sale of consumer services. Predictions are made based on the behaviors, preferences, assets, identifying characteristics, and other attributes associated with customers and merchants. In one implementation, a prediction is made as to whether a customer is likely to request a service and whether a merchant is likely to be selected by the customer to provide the service. In another implementation, the calendars of a merchant and customer are automatically updated to account for the customer's late arrival to an appointment at the merchants location. In yet another implementation, a customer purchases an appointment for a service from another customer that has the appointment scheduled with a merchant providing the service.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method for tracking potential activity of a customer based on location, the method comprising:
 receiving a request for a service for a customer from a customer device, the customer device comprising a location tracking sensor;   at a first time, receiving via the location tracking sensor of the customer device a first geographical location of the customer device, and automatically accepting an appointment for the service on behalf of a service provider based at least in part on a location of the service provider and the first geographical location of the customer device at the first time;   identifying a requirement associated with the service, wherein the requirement comprises a requirement to which the customer should adhere prior to a scheduled time of the appointment for the service;   at a second time, later than the first time, receiving via the location tracking sensor of the customer device a second, different geographical location of the customer device;   identifying, based at least in part on the second, different geographical location of the customer device at the second time, a type of location where the customer device is present;   determining that (i) a relationship exists between the type of location and the requirement associated with the service and (ii) the type of location may affect the customer's ability to adhere to the requirement; and   in response to the determination of (i) and (ii), providing a notification to the customer device of the requirement.   
     
     
         22 . The computer-implemented method of  claim 21 , wherein the customer device comprises a device of the customer or a device of a third party. 
     
     
         23 . The computer-implemented method of  claim 21 , wherein the customer device is one of a smart phone, a smart watch, smart glasses, a portable computer, and a tablet computer. 
     
     
         24 . The computer-implemented method of  claim 21 , further comprising:
 collecting over a period time by a marketplace server information relating to transactions comprising services provided to a plurality of different customers by a plurality of different service providers, wherein each customer has a plurality of associated customer attributes and each service provider has a plurality of service provider attributes;   determining, for each of the plurality of different service providers, a respective on-time performance of the service provider for each of a plurality of different services, wherein a particular on-time performance of the service provider for a particular service comprises a measure of whether the service provider has historically commenced providing the particular service to customers by respective pre-scheduled appointment times.   
     
     
         25 . The computer-implemented method of  claim 24 , further comprising:
 training a classifier, using a subset of the collected information, to predict that a particular service provider has a respective probability of being selected by a particular customer to provide the service, wherein the subset of collection information comprises attributes of customers that have previously received the service and attributes of service providers that have previously provided the service including the on-time performances thereof;   selecting the service provider to provide the service, wherein the selecting is based at least in part on the on-time performance of the selected service provider for the service meeting a threshold level of timeliness, and wherein selecting the service provider comprises providing to the classifier as input one or more attributes of the customer and receiving from the classifier as output a plurality of potential service providers to provide the service.   
     
     
         26 . The computer-implemented method of  claim 25 , wherein selecting the service provider comprises determining that the service provider has a higher probability of timely providing the service than all of the other service providers output from the classifier. 
     
     
         27 . The computer-implemented method of  claim 21 , wherein automatically accepting the appointment for the service on behalf of the service provider comprises providing historical data regarding on-time performance of the customer to a device of the service provider, wherein the on-time performance of the customer is a measure of how the customer has historically adhered to scheduled appointments for services, and wherein the automatically accepting is based at least in part on the historical data. 
     
     
         28 . The computer-implemented method of  claim 21 , further comprising automatically accepting the appointment for the service on behalf of the customer based on historical data regarding the on-time performance of the service provider. 
     
     
         29 . The computer-implemented method of  claim 21 , further comprising monitoring a geographical location of the customer device to determine if the customer will be late for the appointment based on an estimated arrival time of the customer at a location of the service provider. 
     
     
         30 . The computer-implemented method of  claim 29 , further comprising providing a notification to at least one of the customer device and a device of the service provider if the customer will be late for the appointment. 
     
     
         31 . A system for tracking potential activity of a customer based on location comprising:
 at least one memory for storing computer-readable instructions; and   at least one processor for executing the computer-readable instructions, wherein execution of the computer-readable instructions programs the at least one processor to perform operations comprising:
 receiving a request for a service for a customer from a customer device, the customer device comprising a location tracking sensor; 
 at a first time, receiving via the location tracking sensor of the customer device a first geographical location of the customer device, and automatically accepting an appointment for the service on behalf of a service provider based at least in part on a location of the service provider and the first geographical location of the customer device at the first time; 
 identifying a requirement associated with the service, wherein the requirement comprises a requirement to which the customer should adhere prior to a scheduled time of the appointment for the service; 
 at a second time, later than the first time, receiving via the location tracking sensor of the customer device a second, different geographical location of the customer device; 
 identifying, based at least in part on the second, different geographical location of the customer device at the second time, a type of location where the customer device is present; 
 determining that (i) a relationship exists between the type of location and the requirement associated with the service and (ii) the type of location may affect the customer's ability to adhere to the requirement; and 
 in response to the determination of (i) and (ii), providing a notification to the customer device of the requirement. 
   
     
     
         32 . The system of  claim 31 , wherein the customer device comprises a device of the customer or a device of a third party. 
     
     
         33 . The system of  claim 31 , wherein the customer device is one of a smart phone, a smart watch, smart glasses, a portable computer, and a tablet computer. 
     
     
         34 . The system of  claim 31 , wherein the operations further comprise:
 collecting over a period time by a marketplace server information relating to transactions comprising services provided to a plurality of different customers by a plurality of different service providers, wherein each customer has a plurality of associated customer attributes and each service provider has a plurality of service provider attributes;   determining, for each of the plurality of different service providers, a respective on-time performance of the service provider for each of a plurality of different services, wherein a particular on-time performance of the service provider for a particular service comprises a measure of whether the service provider has historically commenced providing the particular service to customers by respective pre-scheduled appointment times.   
     
     
         35 . The system of  claim 34 , wherein the operations further comprise:
 training a classifier, using a subset of the collected information, to predict that a particular service provider has a respective probability of being selected by a particular customer to provide the service, wherein the subset of collection information comprises attributes of customers that have previously received the service and attributes of service providers that have previously provided the service including the on-time performances thereof;   selecting the service provider to provide the service, wherein the selecting is based at least in part on the on-time performance of the selected service provider for the service meeting a threshold level of timeliness, and wherein selecting the service provider comprises providing to the classifier as input one or more attributes of the customer and receiving from the classifier as output a plurality of potential service providers to provide the service.   
     
     
         36 . The system of  claim 35 , wherein selecting the service provider comprises determining that the service provider has a higher probability of timely providing the service than all of the other service providers output from the classifier. 
     
     
         37 . The system of  claim 31 , wherein automatically accepting the appointment for the service on behalf of the service provider comprises providing historical data regarding on-time performance of the customer to a device of the service provider, wherein the on-time performance of the customer is a measure of how the customer has historically adhered to scheduled appointments for services, and wherein the automatically accepting is based at least in part on the historical data. 
     
     
         38 . The system of  claim 31 , wherein the operations further comprise automatically accepting the appointment for the service on behalf of the customer based on historical data regarding the on-time performance of the service provider. 
     
     
         39 . The system of  claim 31 , wherein the operations further comprise monitoring a geographical location of the customer device to determine if the customer will be late for the appointment based on an estimated arrival time of the customer at a location of the service provider. 
     
     
         40 . The system of  claim 39 , wherein the operations further comprise providing a notification to at least one of the customer device and a device of the service provider if the customer will be late for the appointment.