IP Library Granted Patent US 10,623,572
Granted Patent B1
US 10,623,572 · App. 16/198,742 · Granted Apr 14, 2020

Semantic CRM transcripts from mobile communications sessions

Inventor: Shannon L. Copeland (Atlanta, GA)
Assignee: N3, LLC
H04M3/5191G06F16/9024G06Q30/016H04M3/2218H04M3/42221H04M3/5175H04M2201/40H04M2250/60
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Quick Facts
Patent No.
US 10,623,572
App. No.
16/198,742
Granted
Apr 14, 2020
Kind
B1
Abstract

Customer relationship management (‘CRM’) implemented in a computer system, including administering by the computer system a communications session that includes a sequence of communications contacts between a tele-agent and one or more customer representatives, the session and each contact composed of structured computer memory of the computer system; and generating by the computer system a digital transcript of the content of the communications contacts.

Claims (60)

1. A method of customer relationship management (“CRM”) implemented in a computer system, the method comprising:

administering by the computer system a communications session comprising a sequence of communications contacts between a tele-agent and one or more customer representatives, the session and each contact comprising a structure of computer memory of the computer system; and

generating by the computer system a digital transcript of the content of the communications contacts;

wherein administering a communications session comprises establishing, as structure of computer memory of the computer system, the session and each contact as object-oriented modules of automated computing machinery whose structure and contents are also stored as semantic triples in an enterprise knowledge graph.

2. The method of claim 1 wherein administering a communications session comprises:

storing in computer memory for the session a subject code, a timestamp, identification of the tele-agent, and identification of the customer representative; and

storing in computer memory for each contact a timestamp beginning the contact, duration of the contact, a session identifier for the contact, platform type, contact status, and any communications content of the contact.

3. The method of claim 1 wherein the digital transcript comprises:

content from text messaging and email identified by author; and

content from telephone conversations identified by speaker.

4. The method of claim 1 wherein generating a transcript comprises:

gathering text content from contacts that effect communications by text messages and emails; and

storing the gathered text content as semantic triples in said enterprise knowledge graph.

5. The method of claim 1 wherein generating a transcript comprises:

capturing speech content from telephone conversations between the tele-agent and the customer representative;

recognizing the speech content into digitized text; and

storing the digitized text as semantic triples in said enterprise knowledge graph.

6. The method of claim 1 wherein generating a transcript comprises:

storing speech content from telephone conversations between the tele-agent and the customer representative; and

storing, as semantic triples in said enterprise knowledge graph, storage locations of the stored speech.

7. The method of claim 1 wherein generating a transcript comprises identifying by voiceprint comparison the speakers in a conversation between the tele-agent and one or more customer representatives.

8. The method of claim 1 wherein generating a transcript comprises:

determining by voiceprint comparison during a telephone conversation between the tele-agent and a customer representative that the customer representative is unknown to the computer system;

recording by the computer system a voiceprint for the unknown representative;

identifying by the computer system, by prompt and response for an identification, the unknown representative; and

recording, by the computer system in association with the recorded voiceprint, the identity of the now-identified representative.

9. The method of claim 1 wherein generating a transcript comprises:

parsing, by a parsing engine of the computer system into parsed triples of a description logic, the content of the transcript;

inferring, by an inference engine from the parsed triples according to inference rules of said enterprise knowledge graph of the computer system, inferred triples; and

storing the parsed triples and the inferred triples in the enterprise knowledge graph.

10. A computer system that implements customer relationship management (“CRM”), the computer system comprising a computer processor operatively coupled to computer memory, the computer processor configured to function by:

administering by the computer system a communications session comprising a sequence of communications contacts between a tele-agent and one or more customer representatives, the session and each contact comprising a structure of computer memory of the computer system; and

generating by the computer system a digital transcript of the content of the communications contacts;

wherein administering a communications session comprises establishing, as structure of computer memory of the computer system, the session and each contact as object-oriented modules of automated computing machinery whose structure and contents are also stored as semantic triples in an enterprise knowledge graph.

11. The computer system of claim 10 wherein administering a communications session comprises:

storing in computer memory for the session a subject code, a timestamp, identification of the tele-agent, and identification of the customer representative; and

storing in computer memory for each contact a timestamp beginning the contact, duration of the contact, a session identifier for the contact, platform type, contact status, and any communications content of the contact.

12. The computer system of claim 10 wherein the digital transcript comprises:

content from text messaging and email identified by author; and

content from telephone conversations identified by speaker.

13. The computer system of claim 10 wherein generating a transcript comprises:

gathering text content from contacts that effect communications by text messages and emails; and

storing the gathered text content as semantic triples in said enterprise knowledge graph.

14. The computer system of claim 10 wherein generating a transcript comprises:

capturing speech content from telephone conversations between the tele-agent and the customer representative;

recognizing the speech content into digitized text; and

storing the digitized text as semantic triples in said enterprise knowledge graph.

15. The computer system of claim 10 wherein generating a transcript comprises:

storing speech content from telephone conversations between the tele-agent and the customer representative; and

storing, as semantic triples in said enterprise knowledge graph, storage locations of the stored speech.

16. The computer system of claim 10 wherein generating a transcript comprises identifying by voiceprint comparison the speakers in a conversation between the tele-agent and one or more customer representatives.

17. The computer system of claim 10 wherein generating a transcript comprises:

determining by voiceprint comparison during a telephone conversation between the tele-agent and a customer representative that the customer representative is unknown to the computer system;

recording by the computer system a voiceprint for the unknown representative;

identifying by the computer system, by prompt and response for an identification, the unknown representative; and

recording, by the computer system in association with the recorded voiceprint, the identity of the now-identified representative.

18. The computer system of claim 10 wherein generating a transcript comprises:

parsing, by a parsing engine of the computer system into parsed triples of a description logic, the content of the transcript;

inferring, by an inference engine from the parsed triples according to inference rules of said enterprise knowledge graph of the computer system, inferred triples; and

storing the parsed triples and the inferred triples in the enterprise knowledge graph.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 18, 2022
From: N3, LLC
To: ACCENTURE GLOBAL SOLUTIONS LIMITED
Reel/Frame 058678/0304 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 6, 2018
From: COPELAND, SHANNON L.
To: N3, LLC
Reel/Frame 047685/0804 →
Cited By (3)
US 12,381,983 US 12,395,588 US 12,400,238