CLIAMS:We claim:
1. A method for predicting customer satisfaction, the method comprising:
obtaining, by a utility management computing device, data associated with one or more electric utilities from an utility monitoring system;
determining, by the utility management computing device, an asset reliability score and a consumption score from the obtained data associated with the one or more electric utilities;
determining, by the utility management computing device, a customer satisfaction score for the one or more electric utilities based on the determined asset reliability score and the consumption score; and
providing, by the utility management computing device, the determined customer satisfaction score for the one or more electric utilities.

2. The method as set forth in claim 1 wherein the determining the asset reliability score further comprises:
identifying, by the utility management computing device, power outage data from the obtained data associated with one or more electric utilities;
determining, by the utility management computing device, a cumulative frequency of a power outage, a mean frequency of the power outage for each of one or more customers from the identified power outage data;
determining, by the utility management computing device, an average power outage value based on the determined cumulative frequency and the mean frequency;
identifying, by the utility management computing device, a power outage frequency percentile value from the determine average power outage value;
converting, by the utility management computing device, the identified power outage frequency percentile value to a frequency quartile value based on a power outage conversion table; and
determining, by the utility management computing device, the asset reliability score based on the converted frequency quartile value.

3. The method as set forth in claim 1 wherein the determining the consumption score further comprises:
identifying, by the utility management computing device, an actual power consumption value from the obtained data associated with one or more electric utilities for each of the one or more customers;
obtaining, by the utility management computing device, a regression estimated power consumption value for each of the one or more customers;
determining, by the utility management computing device, a consumption variance value based on the identified actual power consumption value and the obtained regression estimated power consumption value; and
correlating, by the utility management computing device, the determined consumption variance value to a consumption table to determine the consumption score.

4. The method as set forth in claim 1 wherein the determining the customer satisfaction score further comprises associating, by the utility management computing device, the determined asset reliability score and the consumption score to a one or more values present in a customer satisfaction table to determine the customer satisfaction score.

5. The method as set forth in claim 1 further comprising generating and providing, by the utility management computing device, a graphical representation of the determined customer satisfaction score.

6. The method as set forth in claim 1 wherein the data associated with the one or more electric utilities further comprises one or more of, a number of power outages within a set period of time, a summation of an entire power outage, billing information associated with power usage, or demographic information associated with usage of power.

7. The method as set forth in claim 1 further comprising recommending, by the utility management computing device, one or more stored customer service suggestions by correlating the determined customer satisfaction score with a customer service suggestion table.

8. A utility management computing device comprising:
one or more processors;
a memory, wherein the memory coupled to the one or more processors which are configured to execute programmed instructions stored in the memory comprising:
obtaining data associated with one or more electric utilities from an utility monitoring system;
determining an asset reliability score and a consumption score from the obtained data associated with the one or more electric utilities;
determining a customer satisfaction score for the one or more electric utilities based on the determined asset reliability score and the consumption score; and
providing the determined customer satisfaction score for the one or more electric utilities.

9. The device as set forth in claim 8 wherein the one or more processors is further configured to execute programmed instructions stored in the memory for the determining the asset reliability score further comprises:
identifying power outage data from the obtained data associated with one or more electric utilities;
determining a cumulative frequency of a power outage, a mean frequency of the power outage for each of one or more customers from the identified power outage data;
determining an average power outage value based on the determined cumulative frequency and the mean frequency;
identifying a power outage frequency percentile value from the determine average power outage value;
converting the identified power outage frequency percentile value to a frequency quartile value based on a power outage conversion table; and
determining the asset reliability score based on the converted frequency quartile value.

10. The device as set forth in claim 8 wherein the one or more processors is further configured to execute programmed instructions stored in the memory for the determining the consumption score further comprises:
identifying an actual power consumption value from the obtained data associated with one or more electric utilities for each of the one or more customers;
obtaining a regression estimated power consumption value for each of the one or more customers;
determining a consumption variance value based on the identified actual power consumption value and the obtained regression estimated power consumption value; and
correlating the determined consumption variance value to a consumption table to determine the consumption score.

11. The device as set forth in claim 8 wherein the one or more processors is further configured to execute programmed instructions stored in the memory for the determining the customer satisfaction score further comprises associating the determined asset reliability score and the consumption score to a one or more values present in a customer satisfaction table to determine the customer satisfaction score.

12. The device as set forth in claim 8 wherein the one or more processors is further configured to execute programmed instructions stored in the memory further comprising generating and providing a graphical representation of the determined customer satisfaction score.

13. The device as set forth in claim 8 wherein the data associated with the one or more electric utilities further comprises one or more of, a number of power outages within a set period of time, a summation of an entire power outage, billing information associated with power usage, or demographic information associated with usage of power.

14. The device as set forth in claim 8 wherein the one or more processors is further configured to execute programmed instructions stored in the memory further comprising recommending one or more stored customer service suggestions by correlating the determined customer satisfaction score with a customer service suggestion table.
15. A non-transitory computer readable medium having stored thereon instructions for predicting customer satisfaction comprising machine executable code which when executed by at least one processor, causes the processor to perform steps comprising:
obtaining data associated with one or more electric utilities from an utility monitoring system;
determining an asset reliability score and a consumption score from the obtained data associated with the one or more electric utilities;
determining a customer satisfaction score for the one or more electric utilities based on the determined asset reliability score and the consumption score; and
providing the determined customer satisfaction score for the one or more electric utilities.

16. The medium as set forth in claim 15 wherein the determining the asset reliability score further comprises:
identifying power outage data from the obtained data associated with one or more electric utilities;
determining a cumulative frequency of a power outage, a mean frequency of the power outage for each of one or more customers from the identified power outage data;
determining an average power outage value based on the determined cumulative frequency and the mean frequency;
identifying a power outage frequency percentile value from the determine average power outage value;
converting the identified power outage frequency percentile value to a frequency quartile value based on a power outage conversion table; and
determining the asset reliability score based on the converted frequency quartile value.

17. The medium as set forth in claim 15 wherein the determining the consumption score further comprises:
identifying an actual power consumption value from the obtained data associated with one or more electric utilities for each of the one or more customers;
obtaining a regression estimated power consumption value for each of the one or more customers;
determining a consumption variance value based on the identified actual power consumption value and the obtained regression estimated power consumption value; and
correlating the determined consumption variance value to a consumption table to determine the consumption score.

18. The medium as set forth in claim 15 wherein the determining the customer satisfaction score further comprises associating the determined asset reliability score and the consumption score to a one or more values present in a customer satisfaction table to determine the customer satisfaction score.

19. The medium as set forth in claim 15 further comprising generating and providing a graphical representation of the determined customer satisfaction score.

20. The medium as set forth in claim 15 wherein the data associated with the one or more electric utilities further comprises one or more of, a number of power outages within a set period of time, a summation of an entire power outage, billing information associated with power usage, or demographic information associated with usage of power.

21. The medium as set forth in claim 15 further comprising recommending one or more stored customer service suggestions by correlating the determined customer satisfaction score with a customer service suggestion table.

Dated this 19th day of March, 2014
SRAVAN KUMAR GAMPA
K&S PARTNERS
AGENT FOR THE APPLICANT
,TagSPECI:TECHNICAL FIELD
This technology relates to methods for predicting of customer satisfaction and devices thereof.