System and method for enhanced customer support experiences

1. A method for improving customer support electronic communication systems by presenting customer-specific information to a support agent, the method comprising:

receiving, via an application on a mobile computing device, a first input from a first customer describing a first issue for which a solution is being sought, the first input being inputted into the mobile computing device through a touchscreen on the mobile computing device;

storing at least the first input in a customer database as a first activity record;

accessing by an intelligent guidance system, in response to a request for a communication session between the first customer and a support agent, the first activity record;

determining, via a machine learning algorithm that is part of the intelligent guidance system, at least a first recommended solution to the first issue;

the machine learning algorithm being configured to improve recommended solutions it generates over time by using as inputs

the first activity record,

data received from the customer database describing past attempts by the first customer to resolve the first issue for which a solution is sought, data received from a solutions database,

feedback received from the support agent upon termination of a previous communication session between the support agent and a previous customer regarding whether a previous recommended solution was successful in addressing the previous customer's issue for which a solution was being sought,

data from an electronic repository of previous communication sessions and customer records, and

feedback received from the first customer regarding whether a recommended solution was successful in addressing the first customer's first issue for which a solution is being sought;

presenting, at a computing device associated with the support agent, a first report including data from the first activity record and a description of the first recommended solution;

the support agent choosing not to implement the first recommended solution with the first customer and instead disregarding the first recommended solution; and

the support agent requesting that the machine learning algorithm generate a second recommended solution as an alternative next-best solution to the first recommended solution that was disregarded;

wherein the machine learning algorithm further uses as an input for improving recommended solutions it generates over time the disregarding of the first recommended solution by the support agent.

2. The method of claim 1 , wherein the first customer has a first customer account through which access to the application occurs, and the first activity record is associated with the first customer account.

3. The method of claim 1 , wherein the first activity record corresponds to a first period of in-app activity by the first customer.

4. The method of claim 1 , wherein the first input corresponds to data about a product or service provided by an entity associated with the support agent.

5. The method of claim 1 , wherein the application is provided as a tool for use by customers of an entity associated with the support agent.

6. The method of claim 1 ,

wherein the step of accessing the first activity record by the intelligent guidance system includes the first activity record being stored in symbols or other non-dialogue text, and a natural language generation module converting the first activity record into a natural language response; and

wherein the step of presenting the first report at a computer device associated with the support agent includes presenting the natural language response generated by the natural language generation module.

7. The method of claim 1 , wherein the first report is rendered in natural language format.

8. A method for improving customer support electronic communication systems by presenting customer-specific intelligent recommendations to a support agent, the method comprising:

receiving, via an application on a mobile computing device, a first input from a first customer describing a first issue for which a solution is being sought, the first input being inputted into the mobile computing device through a touchscreen on the mobile computing device;

storing at least the first input in a customer database as a first activity record;

determining, via a machine learning intelligent recommendation model, at least a first recommended solution to the first issue;

wherein the first recommended solution is based in part on data from the first activity record, data received from a solutions database, data received from the customer database describing past attempts by the first customer to resolve the first issue for which a solution is sought, and data from an electronic repository of previous communication sessions and customer record;

wherein the machine learning intelligent recommendation model is configured to improve recommended solutions it generates over time by receiving as inputs

feedback received from the support agent regarding whether the first recommended solution is accepted or disregarded,

feedback received from the support agent upon termination of a previous communication session between the support agent and a previous customer regarding whether a previous recommended solution was successful in addressing the previous customer's issue for which a solution was being sought,

feedback received from the first customer regarding whether a recommended solution was successful in addressing the first customer's first issue for which a solution is being sought; and

presenting the first recommended solution at a computing device for a support agent in response to a request for a communication session between the first customer and a support agent;

the support agent choosing not to implement the first recommended solution with the first customer and instead disregarding the first recommended solution; and

the support agent requesting that the machine learning algorithm generate a second recommended solution as an alternative next-best solution to the first recommended solution that was disregarded;

wherein the machine learning algorithm further uses as an input for improving recommended solutions it generates over time the disregarding of the first recommended solution by the support agent.

9. The method of claim 8 , further comprising:

accessing, in response to the request for a communication session between the first customer and a support agent, the first activity record;

wherein the first activity record is stored in symbols or other non-dialogue text, and accessing the first activity record includes a natural language generation module converting the first activity record into a natural language response; and

presenting, at a computing device for the support agent, a first report including data from the first activity record that includes the natural language response generated by the natural language generation module.

10. The method of claim 8 , wherein the first customer has a first customer account through which access to the application occurs, and the first activity record is associated with the first customer account.

11. The method of claim 10 , wherein the first activity record corresponds to the most recent period of in-app activity for the first customer account.

12. The method of claim 8 , wherein the first input corresponds to data about a product or service provided by an entity associated with the support agent.

13. The method of claim 8 , wherein the application is provided as a tool for use by customers of an entity associated with the support agent.

14. The method of claim 8 , wherein the request for the communication session is submitted by the first customer via the application.

15. A system for presenting customer-specific information to a support agent, the system comprising a processor and machine-readable media including instructions which, when executed by the processor, cause the processor to:

receive, via an application on a mobile computing device, a first input from a first customer describing a first issue for which a solution is being sought, the first input being inputted into the mobile computing device through a touchscreen on the mobile computing device;

store at least the first input in a customer database as a first activity record;

access by a machine learning algorithm, in response to a request for a communication session between the first customer and a support agent, the first activity record;

determine, using the machine learning algorithm, at least a first recommended solution to the first issue;

wherein the machine learning algorithm is configured to improve recommend solutions it generates over time by using as inputs

the first activity record,

data received from the customer database describing past attempts by the first customer to resolve the first issue for which a solution is sought,

data received from a solutions database,

feedback received from the support agent upon termination of a previous communication session between the support agent and a previous customer regarding whether a previous recommended solution was successful in addressing the previous customer's issue for which a solution was being sought,

data from an electronic repository of previous communication sessions and customer records, and

feedback received from the first customer regarding whether a recommended solution was successful in addressing the first customer's first issue for which a solution is being sought;

present, at a computing device associated with the support agent, a first report including data from the first activity record and a description of the first recommended solution;

the support agent choosing not to implement the first recommended solution with the first customer and instead disregarding the first recommended solution; and

the support agent requesting that the machine learning algorithm generate a second recommended solution as an alternative next-best solution to the first recommended solution that was disregarded;

wherein the machine learning algorithm further uses as an input for improving recommended solutions it generates over time the disregarding of the first recommended solution by the support agent.

16. The system of claim 15 , wherein the first customer has a first customer account through which access to the application occurs, and the first activity record is associated with the first customer account.

17. The system of claim 15 , wherein the first activity record corresponds to a first period of in-app activity by the first customer.

18. The system of claim 15 , wherein the first input corresponds to data about a product or service provided by an entity associated with the support agent.

19. The system of claim 15 , wherein the application is provided as a tool for use by customers of an entity associated with the support agent.

20. The system of claim 15 , wherein

accessing the first activity record by the machine learning algorithm includes the first activity record being stored in symbols or other non-dialogue text, and a natural language generation module converting the first activity record into a natural language response; and

wherein presenting the first report at a computer device associated with the support agent includes presenting the natural language response generated by the natural language generation module.