Improved direct response program participation and reduced marketing costs with predictive modeling
公司规模
1,000+
地区
- America
国家
- United States
产品
- Predictive Modeling
技术栈
- Data Analysis
- Social Media Analysis
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
技术
- 分析与建模 - 预测分析
适用行业
- 公用事业
适用功能
- 销售与市场营销
用例
- 补货预测
服务
- 数据科学服务
关于客户
The customer is a large public utility company based in the United States. They offer various utility services to a wide range of residential customers. The company was looking to optimize their marketing efforts by identifying the best prospects for their program and targeting them specifically. This would not only increase the response rate for their campaigns but also decrease mailing costs. The company was seeking a solution that would provide a scientific framework for this optimization, using data analysis and predictive modeling.
挑战
The client, a large US public utility, was looking to understand 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 challenge was to develop a robust and scientific framework to decrease mailing costs, and increase the campaign response rate by targeting only the best prospective customers for select rate plans.
解决方案
Blueocean Market Intelligence developed a 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.
运营影响
数量效益
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