Improved direct response program participation and reduced marketing costs with predictive modeling
Company Size
1,000+
Region
- America
Country
- United States
Product
- Predictive Modeling
Tech Stack
- Data Analysis
- Social Media Analysis
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Utilities
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Replenishment
Services
- Data Science Services
About The Customer
The customer is a large public utility company based in the United States. The company is part of the utilities industry and provides essential services to the public. The company was looking to improve its direct response program participation and reduce marketing costs. They wanted to understand the key drivers that influence the propensity to enroll in the program and identify the best residential customers for the program. The company was also interested in optimizing campaign costs by targeting the best subset of prospective customers.
The Challenge
The client, a large US public utility, was facing a challenge in understanding the key drivers that influence the propensity to enroll in their program. They wanted to identify which residential customers are the best prospects for the program and optimize campaign costs by targeting the best subset of prospective customers. The traditional response rate of program participation was 4%, and the client wanted to increase this rate while decreasing mailing costs.
The Solution
Blueocean Market Intelligence developed a predictive model using historical billing and usage data for customers over a two-year period and data from a satisfaction survey in the same time frame. Historical data analysis was used to understand what usage patterns would help to predict program participation. Historical and customer demographic information was captured to predict program participation and identify differences between program participants and non-participants. Blueocean Market Intelligence also conducted secondary research and evaluated social media conversations to obtain additional context on what customers think about the rate plan.
Operational Impact
Quantitative Benefit
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