IP Library Granted Patent US 8,051,086
Granted Patent B2
US 8,051,086 · App. 12/490,757 · Granted Nov 1, 2011

Enhancing call center performance

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Quick Facts
Patent No.
US 8,051,086
App. No.
12/490,757
Granted
Nov 1, 2011
Kind
B2
Abstract

Some general aspects of the invention relate to systems and methods of processing data, for example, to improve customer interactions. One aspect, in particular, relates to a computer-implemented method that includes accepting user input for analysis of a database having media data and metadata. The media data includes a group of audio recordings and the metadata includes descriptive information of the group of audio recordings. A representation of a set of call series is formed based on user input, and processed to generate an analysis report. A visual representation of the analysis report is formed for presentation to a user.

Claims (30)

1. In a system in electronic communication with a database having media data, the media data including audio recordings of calls and metadata associated with the calls, a computer-implemented method comprising:

accepting user input specifying a set of criteria that define a call series indicative of a plurality of content-related audio recordings, the set of criteria including a minimum number of calls sharing a common caller identifier within a defined time interval;

forming a representation of a set of one or more call series based on the user input, including identifying as a call series each of one or more pluralities of content-related audio recordings that satisfies the set of criteria;

processing the representation of the set of one or more call series to generate an analysis report; and

performing a content-based analysis of the media data that includes applying a phonetically based word-spotting technique to search for occurrences of one or more queries in the metadata, the metadata including a searchable phonetic representation of the media data.

2. The computer-implemented method of claim 1 , wherein forming the representation of the set of one or more call series includes performing a content-based analysis of the media data that includes searching the audio recordings for content associated with one or more queries, or with a predetermined combination of queries.

3. The computer-implemented method of claim 1 , wherein the searchable representation of the media data includes an at least partially textual representation of the media data.

4. The computer-implemented method of claim 1 , wherein processing the representation of the set of one or more call series to generate an analysis report includes:

determining a set of one or more common topics among the set of one or more call series.

5. The computer-implemented method of claim 4 , wherein determining the set of one or more common topics includes:

applying a set of one or more structured queries on a phonetic or textual representation of the media data.

6. The computer-implemented method of claim 5 , wherein the structured queries include phrases, Boolean operators, time-based operators, or a combination thereof.

7. The computer-implemented method of claim 1 , wherein processing the representation of the set of one or more call series to generate an analysis report includes:

determining a degree of correlation of the content of a first audio recording in each identified call series with the content of subsequent audio recordings in the identified call series.

8. The computer-implemented method of claim 7 , wherein determining the degree of correlation includes:

for each audio recording in the set of identified call series, determining whether the recording is associated with at least one of a predetermined set of content categories.

9. The computer-implemented method of claim 8 , wherein determining the degree of correlation further includes:

within a subset of call series whose first audio recording is associated with a first content category, computing the ratio of call series each having at least one audio recording associated with the second content category.

10. The computer-implemented method of claim 8 , wherein determining the degree of correlation further includes:

within a subset of call series whose first audio recording is associated with a first content category, computing the ratio of call series each having at least one non-first audio recording associated with the second content category.

11. The computer-implemented method of claim 8 , wherein determining the degree of correlation further includes:

within a subset of call series each of which has at least one audio recording being associated with a first content category, computing the ratio of call series each having at least one audio recording associated with the second content category.

12. The computer-implemented method of claim 8 , wherein determining the degree of correlation further includes:

within a subset of call series each of which has at least one audio recording being associated with a first content category, computing the ratio of call series each having at least one non-first audio recording associated with the second content category.

13. The computer-implemented method of claim 8 , wherein determining the degree of correlation further includes:

determining a linear or non-linear combination of call counts associated with a first and a second content category.

14. The computer-implemented method of claim 1 , wherein the set of criteria includes one or more of the following: a minimum number of calls within a call series, a minimum amount of time allowed between consecutive calls in a call series, a maximum amount of time allowed between consecutive calls in a series, a total duration of a call series, talk-time characteristics and/or non-talk time characteristics in a call series, and an occurrence of a search term.

15. The computer-implemented method of claim 1 , further comprising:

forming a visual representation of the analysis report for presentation to a user.

16. The computer-implemented method of claim 1 , wherein the caller identifier includes a customer ID value, automatic number identification (ANI), and caller ID value.

Assignments (3)
PATENT SECURITY AGREEMENT Recorded Dec 6, 2016
From: NICE LTD.; NICE SYSTEMS INC.; AC2 SOLUTIONS, INC.; ACTIMIZE LIMITED; INCONTACT, INC.; NEXIDIA, INC.; NICE SYSTEMS TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 040821/0818 →
RELEASE OF SECURITY INTEREST Recorded Oct 28, 2016
From: NXT CAPITAL SBIC
To: NEXIDIA, INC.
Reel/Frame 040508/0989 →
RELEASE OF SECURITY INTEREST Recorded Mar 23, 2016
From: COMERICA BANK
To: NEXIDIA INC.
Reel/Frame 038236/0298 →