METHODS AND SYSTEMS FOR THE SALE OF CONSUMER SERVICES

• US 20140136264A1
• Filed: 11/15/2013
• Published: 05/15/2014
• Est. Priority Date: 11/15/2012
• Status: Active Grant

• Current Assignee: Impel IT! Incorporated
• Original Assignee: Ii, Edward Phillip Kinsey
• Inventors: Kinsey, Edward Phillip II
• Granted Patent: US 10,402,760 B2
• Time in Patent Office: Days
• US Class Current: 705/7.19
• 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:

predicting that a customer of a plurality of customers is likely to request a service wherein the prediction is based on historical data comprising attributes of different customers that have previously requested the service;

predicting 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 is based on historical data comprising attributes of different merchants that have previously provided the service;

selecting one of the predicted merchants based on one or more criteria;

scheduling an appointment for the service on a calendar of the customer and on a calendar of the selected merchant; and

providing notification of the appointment to a customer device of the customer and a merchant device of the selected merchant.

2. The method of claim 1 wherein scheduling the appointment comprises:

sending information to the customer device to cause the customer device to notify the customer of the appointment; and

after sending the information to the customer device, receiving from the customer device an indication of acceptance of the appointment.

3. The method of claim 1 wherein scheduling the appointment comprises:

sending information to the merchant device to cause the merchant device to notify the merchant of the appointment; and

after sending the information to the merchant device, receiving from the merchant device an indication of acceptance of the appointment.

4. The method of claim 1 wherein the notification is one or more of:

audio, visual, and haptic.

5. The method of claim 1 wherein predicting that the customer of the plurality of customers is likely to request the service comprises:

training a classifier to predict whether a given customer would request the service using the historical data comprising the attributes of different customers that have requested the service; and

providing attributes of the customer as input to the classifier and obtaining a prediction as output of the classifier.

6. The method of claim 1 wherein predicting that a merchant of the plurality of merchants is likely to be selected by the customer comprises:

training a classifier to predict whether a given merchant would be selected to provide the service using the historical data comprising the attributes of different merchants that have previously provided the service; and

providing attributes of the merchant as input to the classifier and obtaining a prediction as output of the classifier.

7. The method of claim 1 wherein attributes of a particular customer comprises a plurality of the following:

an identification attribute, a preference attribute, an asset attribute, and a task attribute.

8. The method of claim 7 wherein:

a particular identification attribute is one of;

name, gender, driver'"'"'s license number, social security number, no-show performance, and home address;

wherein a particular preference attribute is one of;

level of feedback expected from merchants, type of service, whether to automatically schedule appointments for services, whether to allow another user to purchase an appointment, physical exercise preference, whether to follow scheduled maintenance, a preference of merchant for a given service, and merchant location preference;

wherein a particular asset attribute is one of;

primary care doctor, spouse/partner, home address, and vehicle identification number; and

wherein a particular task attribute is one of;

car repair, car maintenance, doctor visit, exercise class, training, haircut, and spa appointment.

9. The method of claim 1 wherein attributes of a particular merchant comprises a plurality of the following:

an identification attribute, a preference attribute, a resource attribute, and a task attribute.

10. The method of claim 9 wherein:

a particular identification attribute is one of;

business name, service sector, business address, gender, business license, on-time performance, operating hours, type of personal care provider, type of automotive service provider, type of building maintenance provider, type of training provider, type of transportation services provider, and type of healthcare provider;

wherein a particular preference attribute is one of;

resource utilization, accept weekend appointments, automatic appointment triage, accept emergency requests, accept insurance, and type of insurance accepted;

wherein a particular resource attribute is one of;

employee name, employee specialty, and current location; and

wherein a particular task attribute is one of;

car repair, car maintenance, doctor visit, exercise class, haircut, and spa appointment.

11. The method of claim 1 wherein a service is one of:

car repair, car maintenance, doctor visit, exercise class, training, haircut, and spa appointment.

12. The method of claim 1 wherein a particular criterion is:

a distance between a current location of the customer device and the merchant, a customer approval rating of the merchant, a preference of the customer, customer feedback regarding the merchant, or a specialty of the merchant.

13. The method of claim 1 wherein the customer device is one of:

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

14. The method of claim 1 comprising:

predicting that one or more forms of a plurality of forms are likely to be required for the service, wherein the predicting is based on historical data comprising attributes of different merchants that have previously provided the service and attributes of different users that have previously requested the service; and

providing access to the predicted forms to the customer.

15. A system comprising:

one or more computers programmed to perform operations comprising;

predicting that a customer of a plurality of customers is likely to request a service wherein the prediction is based on historical data comprising attributes of different customers that have previously requested the service;

predicting 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 is based on historical data comprising attributes of different merchants that have previously provided the service;

selecting one of the predicted merchants based on one or more criteria;

scheduling an appointment for the service on a calendar of the customer and on a calendar of the selected merchant; and

providing notification of the appointment to a customer device of the customer and a merchant device of the selected merchant.

16. The system of claim 15 wherein scheduling the appointment comprises:

sending information to the customer device to cause the customer device to notify the customer of the appointment; and

after sending the information to the customer device, receiving from the customer device an indication of acceptance of the appointment.

17. The system of claim 15 wherein scheduling the appointment comprises:

sending information to the merchant device to cause the merchant device to notify the merchant of the appointment; and

after sending the information to the merchant device, receiving from the merchant device an indication of acceptance of the appointment.

18. The system of claim 15 wherein the notification is one or more of:

audio, visual, and haptic.

19. The system of claim 15 wherein predicting that the customer of the plurality of customers is likely to request the service comprises:

training a classifier to predict whether a given customer would request the service using the historical data comprising the attributes of different customers that have requested the service; and

providing attributes of the customer as input to the classifier and obtaining a prediction as output of the classifier.

20. The system of claim 15 wherein predicting that a merchant of the plurality of merchants is likely to be selected by the customer comprises:

training a classifier to predict whether a given merchant would be selected to provide the service using the historical data comprising the attributes of different merchants that have previously provided the service; and

providing attributes of the merchant as input to the classifier and obtaining a prediction as output of the classifier.

21. The system of claim 15 wherein attributes of a particular customer comprises a plurality of the following:

an identification attribute, a preference attribute, an asset attribute, and a task attribute.

22. The system of claim 21 wherein:

a particular identification attribute is one of;

name, gender, driver'"'"'s license number, social security number, no-show performance, and home address;

wherein a particular preference attribute is one of;

level of feedback expected from merchants, type of service, whether to automatically schedule appointments for services, whether to allow another user to purchase an appointment, physical exercise preference, whether to follow scheduled maintenance, a preference of merchant for a given service, and merchant location preference;

wherein a particular asset attribute is one of;

primary care doctor, spouse/partner, home address, and vehicle identification number; and

wherein a particular task attribute is one of;

car repair, car maintenance, doctor visit, exercise class, training, haircut, and spa appointment.

23. The system of claim 15 wherein attributes of a particular merchant comprises a plurality of the following:

an identification attribute, a preference attribute, a resource attribute, and a task attribute.

24. The system of claim 23 wherein:

a particular identification attribute is one of;

business name, service sector, business address, gender, business license, on-time performance, operating hours, type of personal care provider, type of automotive service provider, type of building maintenance provider, type of training provider, type of transportation services provider, and type of healthcare provider;

wherein a particular preference attribute is one of;

resource utilization, accept weekend appointments, automatic appointment triage, accept emergency requests, accept insurance, and type of insurance accepted;

wherein a particular resource attribute is one of;

employee name, employee specialty, and current location; and

wherein a particular task attribute is one of;

car repair, car maintenance, doctor visit, exercise class, haircut, and spa appointment.

25. The system of claim 15 wherein a service is one of:

car repair, car maintenance, doctor visit, exercise class, training, haircut, and spa appointment.

26. The system of claim 15 wherein a particular criterion is:

a distance between a current location of the customer device and the merchant, a customer approval rating of the merchant, a preference of the customer, customer feedback regarding the merchant, or a specialty of the merchant.

27. The system of claim 15 wherein the customer device is one of:

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

28. The system of claim 15 wherein the operations further comprise:

predicting that one or more forms of a plurality of forms are likely to be required for the service, wherein the predicting is based on historical data comprising attributes of different merchants that have previously provided the service and attributes of different users that have previously requested the service; and

providing access to the predicted forms to the customer.

29. 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:

predicting that a customer of a plurality of customers is likely to request a service wherein the prediction is based on historical data comprising attributes of different customers that have previously requested the service;

predicting 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 is based on historical data comprising attributes of different merchants that have previously provided the service;

selecting one of the predicted merchants based on one or more criteria;

scheduling an appointment for the service on a calendar of the customer and on a calendar of the selected merchant; and

providing notification of the appointment to a customer device of the customer and a merchant device of the selected merchant.

30. The article of manufacture of claim 29, wherein predicting that the customer of the plurality of customers is likely to request the service comprises:

training a classifier to predict whether a given customer would request the service using the historical data comprising the attributes of different customers that have requested the service; and

providing attributes of the customer as input to the classifier and obtaining a prediction as output of the classifier.