C5i Case Studies Customer Satisfaction and Brand Health Analysis for a Large Public Utility Company

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	Customer Satisfaction and Brand Health Analysis for a Large Public Utility Company C5i

Customer Satisfaction and Brand Health Analysis for a Large Public Utility Company

C5i

Technology Category	Analytics & Modeling - Predictive Analytics
Applicable Industries	Utilities
Applicable Functions	Business Operation
Services	Data Science Services
Challenge	The client, a large public utility company based in the US, was facing challenges in establishing a common customer satisfaction framework for both residential and business customers. They needed to identify key metrics and determine the impact of relevant dimensions and factors influencing customer satisfaction. A significant challenge was accounting for low response rates among business customers. The company sought to assess and monitor customer satisfaction and performance drivers and benchmark brand health and performance. Read More
About Customer	The client is a large public utility company based in the United States. They operate in the energy and utility industry, providing essential services to both residential and business customers. As a public utility, they are subject to a high level of scrutiny and regulation, and customer satisfaction is a critical metric for their success. The company is committed to understanding their customers' needs and expectations and continuously improving their service delivery to meet these expectations. They sought to establish a common framework for assessing customer satisfaction across their diverse customer base. Read More
Solution	Blueocean Market Intelligence worked closely with the client to gain a deeper understanding of their business and touchpoints related to both residential and business segments. Based on domain knowledge and related historical results, an optimal customer satisfaction framework was developed for the client’s industry. The hierarchical customer satisfaction model framework consisted of two core constructs, which represented a set of company and service dimensions. A set of attributes or indicators were developed to represent each dimension. A sequential bottom-up model was then created relating each attribute to each dimension, and each dimension to each construct. Survey instruments were developed, and then analysis and reporting needs were aligned based on the model framework. A robust statistical approach, based on multivariate regression, was developed and applied to test the customer satisfaction framework on actual survey data. The model results were found to be consistent with the proposed conceptual framework and in line with the clients’ business and service delivery mechanism. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Utilities

Applicable Functions

Business Operation

Services

Data Science Services

Challenge

The client, a large public utility company based in the US, was facing challenges in establishing a common customer satisfaction framework for both residential and business customers. They needed to identify key metrics and determine the impact of relevant dimensions and factors influencing customer satisfaction. A significant challenge was accounting for low response rates among business customers. The company sought to assess and monitor customer satisfaction and performance drivers and benchmark brand health and performance.

About Customer

The client is a large public utility company based in the United States. They operate in the energy and utility industry, providing essential services to both residential and business customers. As a public utility, they are subject to a high level of scrutiny and regulation, and customer satisfaction is a critical metric for their success. The company is committed to understanding their customers' needs and expectations and continuously improving their service delivery to meet these expectations. They sought to establish a common framework for assessing customer satisfaction across their diverse customer base.

Solution

Blueocean Market Intelligence worked closely with the client to gain a deeper understanding of their business and touchpoints related to both residential and business segments. Based on domain knowledge and related historical results, an optimal customer satisfaction framework was developed for the client’s industry. The hierarchical customer satisfaction model framework consisted of two core constructs, which represented a set of company and service dimensions. A set of attributes or indicators were developed to represent each dimension. A sequential bottom-up model was then created relating each attribute to each dimension, and each dimension to each construct. Survey instruments were developed, and then analysis and reporting needs were aligned based on the model framework. A robust statistical approach, based on multivariate regression, was developed and applied to test the customer satisfaction framework on actual survey data. The model results were found to be consistent with the proposed conceptual framework and in line with the clients’ business and service delivery mechanism.

Impact #1	Developed monthly and quarterly reports highlighting performance on key metrics, perceived gaps in service levels and brand perceptions, and historical trends.
Impact #2	The key driver analysis identified the most important dimensions and attributes influencing overall customer satisfaction.
Impact #3	The analysis helped to quantify the relationships between dimensions and attributes, and using the importance of predictor attributes and dimensions and associated performance scores, identified areas for improvement and leverage.

Impact #1

Developed monthly and quarterly reports highlighting performance on key metrics, perceived gaps in service levels and brand perceptions, and historical trends.

Impact #2

The key driver analysis identified the most important dimensions and attributes influencing overall customer satisfaction.

Impact #3

The analysis helped to quantify the relationships between dimensions and attributes, and using the importance of predictor attributes and dimensions and associated performance scores, identified areas for improvement and leverage.

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Overview

Customer Satisfaction and Brand Health Analysis for a Large Public Utility Company

Operational Impact