CUSTOMER FRUSTRATION SCORE GENERATION AND METHOD FOR USING THE SAME

1 . A method comprising:

generating a customer frustration index for a customer; and

performing one or more operations based on the customer frustration index.

2 . The method defined in claim 1 wherein generating the customer frustration index comprises combining data related to one or more of sentiment, a temporal pattern, a behavior pattern and brand loyalty of the customer.

3 . The method defined in claim 2 wherein the data includes interaction data related to interactions with the customer.

4 . The method defined in claim 3 wherein the interaction data comprises text data from one or more of a text message, an email message, a chat session, a telephone call, a voicemail message, secure messages, secure alerts, and search.

5 . The method defined in claim 2 wherein the brand loyalty is represented by a brand loyalty index.

6 . The method defined in claim 2 wherein generating the customer frustration index comprises tuning a plurality of factors that are combined into the customer frustration index.

7 . The method defined in claim 2 wherein generating the customer frustration index comprises:

applying a customer sentiment-progression model to sentiment data taking into account its progression or temporal pattern;

applying a customer behavior model to behavioral data;

applying a brand loyalty index model to brand loyalty data; and

using scores output from the customer sentiment-progression model, the customer behavior model, and the brand loyalty index model to create the customer frustration index.

8 . The method defined in claim 2 wherein generating the customer frustration index comprises:

calculating a total number of interactions until a current time and calculating aggregated sentiment scores from previous interactions to generate a sentiment-progression score;

calculating a difference between values of the previous sentiment score and the current sentiment score and calculating a standard deviation of the sentiment scores until the current time to generate a behavior score;

applying a collaborative filtering method on customer activity data and summing a customer activity vector after collaborative filtering to generate a brand loyalty score;

tuning weights of the sentiment-progression score, the behavior score and the brand loyalty score;

applying weights to the sentiment-progression score, the behavior score and the brand loyalty score; and

aggregating weighted scores to create the customer frustration index.

9 . A system comprising:

a memory to store data related to a customer;

a customer frustration index generator for generating a customer frustration index for a customer; and

a controller to perform one or more business logic operations based on the customer frustration index.

10 . The system defined in claim 9 wherein the customer frustration index generator is operable to generate the customer frustration index by combining data related to one or more of sentiment, a temporal pattern, a behavior pattern and brand loyalty of the customer.

11 . The system defined in claim 10 wherein the data includes interaction data related to interactions with the customer.

12 . The system defined in claim 11 wherein the interaction data comprises text data from one or more of a text message, an email message, a chat session, a telephone call, a voicemail message, secure messages, secure alerts, and search.

13 . The system defined in claim 10 wherein the brand loyalty is represented by a brand loyalty index.

14 . The system defined in claim 10 wherein the customer frustration index generator is operable to generate the customer frustration index by tuning a plurality of factors that are combined into the customer frustration index.

15 . The system defined in claim 10 wherein the customer frustration index generator is operable to generate the customer frustration index by:

applying a customer sentiment-progression model to sentiment data taking into account its progression or temporal pattern;

applying a customer behavior model to behavioral data;

applying a brand loyalty index model to brand loyalty data; and

using scores output from the customer sentiment-progression model, the customer behavior model, and the brand loyalty index model to create the customer frustration index.

16 . The system defined in claim 10 wherein the customer frustration index generator is operable to generate the customer frustration index by:

calculating a total number of interactions until a current time and calculating aggregated sentiment scores from previous interactions to generate a sentiment-progression score;

calculating a difference between values of the previous sentiment score and the current sentiment score and calculating a standard deviation of the sentiment scores until the current time to generate a behavior score;

applying a collaborative filtering method on customer activity data and summing a customer activity vector after collaborative filtering to generate a brand loyalty score;

tuning weights of the sentiment-progression score, the behavior score and the brand loyalty score;

applying weights to the sentiment-progression score, the behavior score and the brand loyalty score; and

aggregating weighted scores to create the customer frustration index.

17 . An article of manufacture having one or more non-transitory computer readable media storing instruction thereon which, when executed by a system, cause the system to perform a method comprising:

generating a customer frustration index for a customer; and

performing one or more operations based on the customer frustration index.

18 . The article of manufacture defined in claim 17 wherein generating the customer frustration index comprises combining data related to one or more of sentiment, a temporal pattern, a behavior pattern and brand loyalty of the customer.

19 . The article of manufacture defined in claim 17 wherein the data includes interaction data related to interactions with the customer, and further wherein the interaction data comprises text data from one or more of a text message, an email message, a chat session, a telephone call, a voicemail message, secure messages, secure alerts, and search.

20 . The article of manufacture defined in claim 17 wherein generating the customer frustration index comprises:

applying a customer sentiment-progression model to sentiment data taking into account its progression or temporal pattern;

applying a customer behavior model to behavioral data;

applying a brand loyalty index model to brand loyalty data; and

using scores output from the customer sentiment-progression model, the customer behavior model, and the brand loyalty index model to create the customer frustration index.