SYSTEMS AND METHODS FOR PRE-FILLING AND/OR PREDICTING RESPONSE DATA BY USE OF ARTIFICIAL INTELLIGENCE (AI) IN ON-LINE TARGETED SURVEYS TO CUSTOMERS TO IMPROVE THE COLLECTED SURVEY RESPONSE DATA

• US 20200134637A1
• Filed: 10/31/2018
• Published: 04/30/2020
• Est. Priority Date: 10/31/2018
• Status: Active Application

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Srinivasan, Karthick
• Application Number:
  US16/177,051
• Publication Number:
  US 20200134637A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 40/174 Form filling; Merging
• CPC Class Codes: G06F 40/216 using statistical methods
• CPC Class Codes: G06Q 30/016 After-sales

Abstract

A system and method for embedding response data to an on-line survey when soliciting feedback through the use of an on-line survey to user about an user experience to a software application service including: sending the on-line survey with response data included to aid the user in completing the on-line survey; embedding with response data pre-filled or predicted responses to at least one or more questions in the on-line survey by using an artificial intelligence (AI) model based on historical response data to on-line surveys and the response data predicted by algorithmic solutions from a set of data points and machine data designated within the software application service; and response time of providers to resolve the user requests during the software application service; and enabling the user to selectively agree or disagree with embedded pre-filled or predicted response data.

Claims

1. A method for embedding response data to an on-line survey when soliciting feedback through the use of an on-line survey to user about an user experience to a software application service provided, the method comprising:

receiving an acknowledgement that the software application service is completed by the user, prior to sending to the user the on-line survey for completion;

sending the on-line survey with response data included to aid the user in completing the on-line survey wherein the user is an electronically targeted user of the on-line survey by virtue of an use by the user of the software application service;

embedding with response data pre-filled or predicted responses to at least one or more questions in the on-line survey by using an artificial intelligence (AI) model based on historical response data to on-line surveys and the response data predicted either directly or indirectly by algorithmic solutions from a set of data points and machine data designated within the software application service wherein the set of data points at least comprise data of time periods corresponding to;

response time of providers to user requests, response time of providers to update data of the user requests; and

response time of providers to resolve the user requests during the software application service; and

enabling the user to selectively agree or disagree with embedded pre-filled or predicted response data included in the on-line survey prior to and during a completing of the on-line survey to ensure a sufficient level of accuracy in results of the response data collected by the on-line survey of the software application service.

2. The method of claim 1, further comprising augmenting response data in the AI model, by:

processing a set of event data using the AI model wherein the set of event data comprises identifying factors related to data points correlated to positive response data of users of the software application service.

3. The method of claim 1, further comprising:

computing a predicted time duration for each response using the AI model based on the historical response data.

4. The method of claim 3, further comprising:

associating index values of severity levels, acknowledge times, and updates to the response data.

5. The method of claim 1, further comprising monitoring the index value, by:

updating the index value by performing one or more additional index value calculations using the AI model and the historical response data.

6. The method of claim 4, further comprises:

scheduling software patches to resolve the user requests based on an index values of severity levels.

7. The method of claim 1, further comprises:

configuring embedding response data within the on-line surveys by measuring increases in an user response rate.

8. A computer program product tangibly embodied in a computer-readable storage device and comprising instructions that when executed by a processor perform a method for predicting response data in an on-line survey sent to a customer to solicit feed-back of a customer experience provided by a support service in an enterprise network, the method comprising:

resolving a customer request between a service agent and the customer by performing one or more actions, by the processor, on the enterprise network between the customer, an app of the enterprise network and the service agent;

configuring the one or more actions into one or more event of the support service associated with the customer request;

sending an on-line survey to the customer after resolving the customer request by an on-line survey app to solicit response data about the customer experience wherein the on-line survey app generates the on-line survey;

defining a set of fields for the response data in the on-line survey to configure a set of inputs for the on-line survey app wherein the set of inputs at least comprises;

a checkbox, a formula field and a numeric field data; and

pre-filling the response data by response data generated by an artificial intelligence (AI) app coupled to the on-line survey app for predicting the response data using a prediction solution application wherein the prediction data is based at least on a set of time periods of data points and historical response data of a set of events in the support service.

9. The computer program product of claim 8, comprising instructions for the processor to perform the method for processing the customer request further comprising:

enabling the customer to selectively agree or disagree with pre-filled predicted response data in the on-line survey prior to and during a completing of the on-line survey to ensure a sufficient level of accuracy in results of the response data collected by the on-line survey.

10. The computer program product of claim 9, comprising instructions for the processor to perform the method for processing the customer request further comprising:

checking a value of a predicted response to the value of the response data by the customer to ensure the value is with a normal value range for accuracy of the response data collected.

11. The computer program product of claim 9, comprising instructions for the processor to perform the method for processing the customer request further comprising:

receiving an acknowledgement that the support service is completed by the customer, prior to sending to the customer the on-line survey for filling out response data.

12. The computer program product of claim 9, comprising instructions for the processor to perform the method for processing the customer request further comprising:

filling response data which is un-filled on the part of the customer when completing the on-line survey.

13. The computer program product of claim 9, comprising instructions for the processor to perform the method for processing the customer request further comprising:

calculating a customer satisfaction (CSAT) score for the customer with a predicted value for the customer based on the predicted response data.

14. The computer program product of claim 13, comprising instructions for the processor to perform the method for processing the customer request further comprising:

suggesting a predicted value of the customer satisfaction score to the customer while the customer is filling out response data in the on-line survey.

15. The computer program product of claim 9, comprising instructions for the processor to perform the method for processing the customer request further comprising:

computing a predicted time duration for each response by the customer in the on-line survey based on a set of historical response data.

16. The computer program product of claim 15, comprising instructions for the processor to perform the method for processing the customer request further comprising:

associating index values of severity levels, acknowledge times, and updates to the predicted response data.

17. A system comprising:

at least one processor; and

at least one computer-readable storage device comprising instructions that when executed causes performance of a method for processing requests in an enterprise app session between a service agent and a customer, the method comprising;

resolving a customer request between the service agent and the customer for a customer service app by performing one or more actions, by the processor, on an enterprise network between a set comprising;

the customer, an app of the enterprise network and the service agent;

configuring the one or more actions into one or more event of customer support service associated with the customer request;

sending an on-line survey to the customer after resolving the customer request by an on-line survey app to solicit response data about customer satisfaction wherein the on-line survey app generates the on-line survey;

defining a set of fields for response data in the on-line survey to configure a set of inputs for the on-line survey app wherein the set of inputs at least comprises;

a checkbox, a formula field and a numeric field data;

pre-filling the response data by response data generated by an artificial intelligence (AI) app coupled to the on-line survey app for predicting the response data using a prediction solution application wherein the prediction data is based at least on a set of time periods of data points and historical response data of the events in the customer service app; and

enabling the customer to selectively agree or disagree with pre-filled predicted response data in the on-line survey prior to and during a completing of the on-line survey to ensure a sufficient level of accuracy in results of the response data collected by the on-line survey.

18. The system of claim 17, further comprising:

calculating a customer satisfaction (CSAT) score for the customer with a predicted value for the customer based on the predicted response data.

19. The system of claim 18, further comprising:

suggesting a predicted value of the customer satisfaction score to the customer while the customer is filling out response data in the on-line survey.

20. The system of claim 18, further comprising:

associating index values of severity levels, acknowledge times, and updates to the predicted response data.