System and method for analyzing and reacting to interactions between entities using electronic communication channels

Patent metadata

Field	Value
Publication number	US-11955117-B2
Application number	US-202117303345-A
Country	US
Kind code	B2
Filing date	May 27, 2021
Priority date	May 27, 2021
Publication date	Apr 9, 2024
Grant date	Apr 9, 2024

Abstract

A system and method are provided for analyzing and reacting to interactions between entities using electronic communication channels. The method includes receiving, via the communications module, data captured from a conversational exchange between a first entity communicating with a second entity using an electronic communication channel. The method also includes analyzing the captured data to detect an indication that the first entity is or was distracted during the conversational exchange, is or was disinterested in a portion of the conversational exchange or missed the portion of the conversational exchange. The method also includes determining based on the indication an action to address the distraction during, disinterest in, or missing of, the portion of the conversational exchange; and providing, via the communications module, an automated message to at least one of the first entity and the second entity for executing the action.

First claim

The invention claimed is:

1. A tracking system for analyzing and reacting to interactions between entities using electronic communication channels, the system comprising:
a processor;
a communications module coupled to the processor; and
a memory coupled to the processor, the memory storing computer executable instructions that when executed by the processor cause the processor to:
receive, via the communications module, data captured from a conversational exchange between a first entity communicating with a second entity using a first electronic communication channel;
analyze the captured data to detect an indication that content was missed or not understood by the first entity as a result of detecting that the first entity was:

distracted during a portion of the conversational exchange, disinterested in the portion of the conversational exchange, or missed the portion of the conversational exchange;
determine, based on the indication, content associated with the portion of the conversational exchange that was missed or not understood; and
provide, via the communications module, to a tracker notification module on a client device of the second entity, using a second electronic communication channel different than the first electronic communication channel, an automated message comprising the content or a link to the content, to the second entity, wherein the content or the link to the content is provided via the second electronic communication channel by having the tracker notification module display the automated message in an application used by at least the second entity while the conversational exchange is occurring via the first electronic communication channel, wherein the tracker notification module comprises a software component provided by the tracking system to interact with the automated message via the application used by the second entity.

2. The device tracking system of claim 1 , wherein the computer executable instructions further cause the processor to:
obtain a model trained by applying one or more machine learning techniques to prior conversational exchanges between a plurality of entities to identify one or more expected conversation paths according to a topic associated with conversational exchange between the first and second entities;
use the model to detect when the conversational exchange deviated from one of the expected conversation paths; and
use the automated message, via the communications module, to return the first and second entities to a point prior to the deviation or to a new conversation path.

3. The tracking system of claim 1 , wherein the automated message is also sent to the first entity via the communications module, following a termination of the conversational exchange and includes the content or the link to the content associated with the portion of the conversation exchange to supplement the conversational exchange.

4. The tracking system of claim 1 , wherein the computer executable instructions further cause the processor to:
generate a conversation script from the captured data, wherein the conversation script is analyzed to detect the distraction during, disinterest in, or missing of, the portion of the conversational exchange.

5. The tracking system of claim 4 , wherein the automated message comprises a portion of the conversation script or a link to the conversation script.

6. The tracking system of claim 5 , wherein the computer executable instructions further cause the processor to:
include a link to additional content associated with the portion of the conversation exchange, in the automated message.

7. The tracking system of claim 1 , wherein a notification is also sent to the first entity regarding the distraction during, disinterest in, or missing of, the portion of the conversational exchange.

8. The tracking system of claim 7 , wherein the notification provides an option to flag the portion of the conversational exchange for reiteration.

9. The tracking system of claim 7 , wherein the notification provides an option to skip over the portion of the conversation exchange.

10. The tracking system of claim 1 , wherein the automated message comprises a notification sent to the second entity, via the communications module, flagging the indication of the distraction during, disinterest in, or missing of, the portion of the conversational exchange.

11. The tracking system of claim 10 , wherein the notification provides an option to send additional information to the first entity.

12. The device tracking system of claim 10 , wherein the notification provides an option to trigger an automated conversation follow-up message to be sent via the communications module, a period of time after the conversational exchange terminates.

13. A method of analyzing and reacting to interactions between entities using electronic communication channels, the method executed by a device having a communications module and comprising:
receiving, via the communications module, data captured from a conversational exchange between a first entity communicating with a second entity using a first electronic communication channel;
analyzing the captured data to detect an indication that content was missed or not understood by the first entity as a result of detecting that the first entity was: distracted during a portion of the conversational exchange, disinterested in the portion of the conversational exchange, or missed the portion of the conversational exchange;
determining, based on the indication, content associated with the portion of the conversational exchange that was missed or not understood; and
providing, via the communications module, to a tracker notification module on a client device of the second entity, using a second electronic communication channel different than the first electronic communication channel, an automated message comprising the content or a link to the content, to the second entity, wherein the content or the link to the content is provided via the second electronic communication channel by having the tracker notification module display the automated message in an application used by at least the second entity while the conversational exchange is occurring via the first electronic communication channel, wherein the tracker notification module comprises a software component provided by the tracking system to interact with the automated message via the application used by the second entity.

14. The method of claim 13 , further comprising:
obtaining a model trained by applying one or more machine learning techniques to prior conversational exchanges between a plurality of entities to identify one or more expected conversation paths according to a topic associated with conversational exchange between the first and second entities;
using the model to detect when the conversational exchange deviated from one of the expected conversation paths; and
using the automated message, via the communications module, to return the first and second entities to a point prior to the deviation or to a new conversation path.

15. The method of claim 13 , wherein the automated message is also sent to the first entity via the communications module, following a termination of the conversational exchange and includes the content or the link to the content associated with the portion of the conversation exchange to supplement the conversational exchange.

16. The method of claim 13 , further comprising:
generating a conversation script from the captured data, wherein the conversation script is analyzed to detect the distraction during, disinterest in, or

Assignees

• Toronto Dominion Bank

Inventors

• Mcdermid Bridget
• Bellwood Brian
• Cornwall Natalie Thien Huong
• True Jeffery David
• Wall Ryan
• Chan Stella Pui Kwan
• D'Souza Venetia
• Caravan Christopher Michael Arthur
• Premathas Pranavan
• Qazi Sahifa Habib
• Siddiqui Mah Noor
• Moghaizel Joe
• Barnett Jonathan K

Classifications

• G10L2015/227

  of the speaker; Human-factor methodology · CPC title

• G10L2015/226

  using non-speech characteristics · CPC title

• G10L15/1822 Primary

  Parsing for meaning understanding · CPC title

• G06F40/30

  Semantic analysis · CPC title

• G10L15/1815

  Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning · CPC title