Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Blueocean Market Intelligence
Tech Stack
- Data Analytics
- Data Integration
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Brand Awareness
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Data-as-a-Service
Applicable Industries
- Utilities
Applicable Functions
- Business Operation
Services
- Data Science Services
About The Customer
The client is a leading natural gas and electric utility company. They have a large customer base and have been in operation for many years. They have a strong focus on customer satisfaction and have been conducting tracking studies to measure their performance in this area. However, a recent event in their service department raised concerns about the level of trust their customers have in the company. This led them to seek a more robust metric to assess their trustworthiness and understand the factors that drive it. They also wanted to understand the role of trust and customer experience in overall customer satisfaction and the effectiveness of their communication with customers.
The Challenge
The client, a large utility company, had been partnering with Blueocean Market Intelligence on a brand and customer satisfaction tracking study. However, a recent event in their service department made them question how much trust their customers actually had for the company. They requested Blueocean Market Intelligence to develop a robust metric that would allow them to assess their trustworthiness and determine which underlying factors drive the metric. Further, the study would need to determine the role of trust, customer experience and rate the overall satisfaction of communication with the utility.
The Solution
Blueocean Market Intelligence developed a new metric to assess the client's trustworthiness. They first reviewed the latest literature and thought leadership on customer trust in the utility and energy industry. They concluded that for most trust-relationships, the hierarchy of 'expectations' parallels the hierarchy of the 'end-users needs' with respect to the product or service offering. After collecting a sufficient amount of interviews, they tested hypotheses using hierarchical regression through dominance analysis. They built models that determined the impact of customer trust, experience, communication and each of their underlying factors on customer satisfaction. They also ran structural equation modeling to understand the interconnectivity between the factors and overall satisfaction.
Operational Impact
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