Methods and systems for the sale of consumer services

• US 10,083,411 B2
• Filed: 11/15/2013
• Issued: 09/25/2018
• Est. Priority Date: 11/15/2012
• Status: Active Grant

• Current Assignee: Impel IT! Incorporated
• Original Assignee: Impel IT! Incorporated
• Inventors: Kinsey, II, Edward Phillip, Seidman, Glenn R.
• Primary Examiner(s): Gart, Matthew S
• Assistant Examiner(s): Swartz, Stephen S
• Application Number:
  US14/081,783
• Publication Number:
  US 20140136266A1
• Time in Patent Office: 1,775 Days
• CPC Class Codes: G06Q 10/063116 Schedule adjustment for a person or group
• CPC Class Codes: G06Q 10/1095 Meeting or appointment
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0627 using item specifications
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: Y02P 90/80 Management or planning

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.

Claims

1. A computer-implemented method 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 merchants, wherein each customer has a plurality of associated customer attributes and each merchant has a plurality of merchant attributes;

determining, by a computer utilizing a processor, for each of the plurality of different merchants, a respective on-time performance of the merchant for each of a plurality of different services, wherein a particular on-time performance of the merchant for a particular service comprises a measure of whether the merchant has historically commenced providing the particular service to customers by respective pre-scheduled appointment times;

receiving a request for a service for a customer from a customer device, the customer device comprising a location tracking sensor;

receiving, from the customer device, information indicating a plurality of different geographical locations of the customer device at different times based on data provided by the location tracking sensor;

training a classifier to predict that a particular merchant has a respective probability of being selected by a particular customer to provide the service that meets a threshold, wherein the predicting is based on attributes of customers that have previously received the service and attributes of merchants that have previously provided the service including the on-time performances thereof;

selecting a merchant from a subplurality of the merchants to provide the service, wherein the selecting is based at least in part on the on-time performance of the selected merchant for the service meeting a threshold level of timeliness, and wherein the threshold level of timeliness is based on, at least, the service, and wherein selecting the merchant comprises providing to the classifier as input one or more attributes of the customer and receiving from the classifier as output the subplurality of merchants;

attempting to schedule an appointment for the service on a calendar of the selected merchant and on a calendar of the customer;

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 the appointment on behalf of the selected merchant based at least in part on a location of the merchant 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, later time, a type of location that the customer has entered;

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 reminder notification to the customer device of the requirement.

2. The method of claim 1 wherein the customer device comprises a device of the customer or a device of a third party.

3. The method of claim 2 wherein the customer device is one of:

a smart phone, a smart watch, smart glasses, a portable computer, and a tablet computer.

4. The method of claim 1 wherein attempting to schedule the appointment comprises:

providing historical data regarding on-time performance of the customer to a merchant device of the selected merchant, wherein the on-time performance of the customer is a measure of how the customer has historically adhered to appointments for services that are scheduled prior to receiving the respective services from merchants, wherein the automatically accepting or declining the appointment on behalf of the selected merchant is further based at least in part on the historical data.

5. The method of claim 1 wherein attempting to schedule the appointment comprises:

providing historical data regarding the on-time performance of the selected merchant to the customer device, wherein the automatically accepting or declining the appointment on behalf of the customer is further based at least in part on the historical data.

6. The method of claim 1 wherein selecting the merchant comprises:

determining that the particular merchant has a higher probability than all of the other merchants; and

receiving selection of the particular merchant from the customer device.

7. The method of claim 1 wherein monitoring the merchant calendar and the customer calendar comprises 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 merchant.

8. The method of claim 7 further comprising providing notification to at least one of the customer device and a merchant device of the merchant if the customer will be late for the appointment.

9. The method of claim 8 comprising:

receiving a change to the appointment from the merchant device;

providing notification of the appointment change to the customer device; and

receiving acceptance of the appointment change from the customer device.

27. The method of claim 1, wherein the on-time performance is measured based on at least one of:

whether the merchant receives customers on or around scheduled appointment times, the frequency with which the merchant exceeds estimated service completion times, and the likelihood that the merchant will cancel a scheduled appointment.

10. A system comprising:

one or more computers programmed to perform operations 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 merchants, wherein each customer has a plurality of associated customer attributes and each merchant has a plurality of merchant attributes;

determining, for each of the plurality of different merchants, a respective on-time performance of the merchant for each of a plurality of different services, wherein a particular on-time performance of the merchant for a particular service comprises a measure of whether the merchant has historically commenced providing the particular service to customers by respective pre-scheduled appointment times;

receiving a request for a service for a customer from a customer device, the customer device comprising a location tracking sensor;

receiving, from the customer device, information indicating a plurality of different geographical locations of the customer device at different times based on data provided by the location tracking sensor;

training a classifier to predict that a particular merchant has a respective probability of being selected by a particular customer to provide the service that meets a threshold, wherein the predicting is based on attributes of customers that have previously received the service and attributes of merchants that have previously provided the service including the on-time performances thereof;

selecting a merchant from a subplurality of the merchants to provide the service, wherein the selecting is based at least in part on the on-time performance of the selected merchant for the service meeting a threshold level of timeliness, and wherein the threshold level of timeliness is based on, at least, the service, and wherein selecting the merchant comprises providing to the classifier as input one or more attributes of the customer and receiving from the classifier as output the subplurality of merchants;

attempting to schedule an appointment for the service on a calendar of the selected merchant and on a calendar of the customer;

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 the appointment on behalf of the selected merchant based at least in part on a location of the merchant 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, later time, a type of location that the customer has entered;

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 reminder notification to the customer device of the requirement.

11. The system of claim 10 wherein the customer device comprises a device of the customer or a device of a third party.

12. The system of claim 11 wherein the customer device is one of:

a smart phone, a smart watch, smart glasses, a portable computer, and a tablet computer.

13. The system of claim 10 wherein attempting to schedule the appointment comprises:

providing historical data regarding on-time performance of the customer to a merchant device of the selected merchant, wherein the on-time performance of the customer is a measure of how the customer has historically adhered to appointments for services that are scheduled prior to receiving the respective services from merchants, wherein the automatically accepting or declining the appointment on behalf of the selected merchant is further based at least in part on the historical data.

14. The system of claim 10 wherein attempting to schedule the appointment comprises:

providing historical data regarding the on-time performance of the selected merchant to the customer device, wherein the automatically accepting or declining the appointment on behalf of the customer is further based at least in part on the historical data.

15. The system of claim 10 wherein selecting the merchant comprises:

determining that the particular merchant has a higher probability than all of the other merchants; and

receiving selection of the particular merchant from the customer device.

16. The system of claim 10 wherein monitoring the merchant calendar and the customer calendar comprises 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 merchant.

17. The system of claim 16 wherein the operations further comprise providing notification to at least one of the customer device and a merchant device of the merchant if the customer will be late for the appointment.

18. The system of claim 17 wherein the operations further comprise:

receiving a change to the appointment from the merchant device;

providing notification of the appointment change to the customer device; and

receiving acceptance of the appointment change from the customer device.

19. An article of manufacture, comprising a non-transitory machine-readable medium storing instructions that, when executed, configure one or more computers to perform operations 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 merchants, wherein each customer has a plurality of associated customer attributes and each merchant has a plurality of merchant attributes;

determining, for each of the plurality of different merchants, a respective on-time performance of the merchant for each of a plurality of services, wherein a particular on-time performance of the merchant for a particular service comprises a measure of whether the merchant has historically commenced providing the particular service to customers by respective pre-scheduled appointment times;

receiving a request for a service for a customer from a customer device, the customer device comprising a location tracking sensor;

receiving, from the customer device, information indicating a plurality of different geographical locations of the customer device at different times based on data provided by the location tracking sensor;

training a classifier to predict that a particular merchant has a respective probability of being selected by a particular customer to provide the service that meets a threshold, wherein the predicting is based on attributes of customers that have previously received the service and attributes of merchants that have previously provided the service including the on-time performances thereof;

selecting a merchant from a subplurality of the merchants to provide the service, wherein the selecting is based at least in part on the on-time performance of the selected merchant for the service meeting a threshold level of timeliness, and wherein the threshold level of timeliness is based on, at least, the service, and wherein selecting the merchant comprises providing to the classifier as input one or more attributes of the customer and receiving from the classifier as output the subplurality of merchants;

attempting to schedule an appointment for the service on a calendar of the selected merchant and on a calendar of the customer;

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 the appointment on behalf of the selected merchant based at least in part on a location of the merchant 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, later time, a type of location that the customer has entered;

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 reminder notification to the customer device of the requirement.

20. The article of manufacture of claim 19 wherein the customer device comprises a device of the customer or a device of a third party.

21. The article of manufacture of claim 20 wherein the customer device is one of:

a smart phone, a smart watch, smart glasses, a portable computer, and a tablet computer.

22. The article of manufacture of claim 19 wherein attempting to schedule the appointment comprises:

providing historical data regarding on-time performance of the customer to a merchant device of the selected merchant, wherein the on-time performance of the customer is a measure of how the customer has historically adhered to appointments for services that are scheduled prior to receiving the respective services from merchants, wherein the automatically accepting or declining the appointment on behalf of the selected merchant is further based at least in part on the historical data.

23. The article of manufacture of claim 19 wherein attempting to schedule the appointment comprises:

providing historical data regarding the on-time performance of the selected merchant to the customer device, wherein the automatically accepting or declining the appointment on behalf of the customer is further based at least in part on the historical data.

24. The article of manufacture of claim 19 wherein selecting the merchant comprises:

determining that the particular merchant has a higher probability than all of the other merchants; and

receiving selection of the particular merchant from the customer device.

25. The article of manufacture of claim 19 wherein monitoring the merchant calendar and the customer calendar comprises 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 merchant.

26. The article of manufacture of claim 25 wherein the operations further comprise providing notification to at least one of the customer device and a merchant device of the merchant if the customer will be late for the appointment.