Data Science as a Service (DSaaS)
Your Trusted Benchmarking and Analytics Provider
JD Power is a global leader in consumer insights, advisory services and data and analytics. A pioneer in the use of big data, artificial intelligence (AI) and algorithmic modeling capabilities to understand consumer behavior, JD Power has been delivering incisive industry intelligence on customer interactions with brands and products for more than 50 years. The world's leading businesses across major industries rely on JD Power to guide their customer-facing strategies.
Our Data Science as a Service (DSaaS) solution, tailored for the utility customer experience, leverages AI to ensure data activation, maximize customer impact and return on investment, while accelerating time-to-value and delivering best-in-class predictive models with our renowned consumer intelligence.
JD Power is a global leader in consumer insights, advisory services and data and analytics. A pioneer in the use of big data, artificial intelligence (AI) and algorithmic modeling capabilities to understand consumer behavior, JD Power has been delivering incisive industry intelligence on customer interactions with brands and products for more than 50 years. The world's leading businesses across major industries rely on JD Power to guide their customer-facing strategies.
Our Data Science as a Service (DSaaS) solution, tailored for the utility customer experience, leverages AI to ensure data activation, maximize customer impact and return on investment, while accelerating time-to-value and delivering best-in-class predictive models with our renowned consumer intelligence.
DSaaS Highlights
- Custom models and insights based on your utility’s specific needs including energy efficiency, Time-of-Use rates, demand response, electric vehicle (EV) adoption, lower-income initiatives and programs, and more depending on your business needs
- Expert analysis of the data to provide actionable insights tailored to your utility’s needs
- Optimize engagement and customer segmentation through customized data and reporting tools
- Develop and maintain versatile algorithmic models applicable to multiple use cases and enhance model accuracy and use case coverage by incorporating Voice of the Customer (VoC) data and intelligence
DSaaS in the Real World
You can use this highly sophisticated and targeted data in many ways, including:
- Foundational Customer Segmentation: Models that develop core foundational customer segments for your CX strategy.
- Reduce Cost to Serve and Increase Self-Serve Digital Engagement: Models to predict which customers will call, for what reasons, and when. Preempt calls by addressing customer needs proactively, arm customer services agents with insights to improve call handling times and first-contact-resolution, and appropriately staff your call center based on call forecasts. Additional models for driving self-serve digital engagement to further reduce call volume.
- Paperless Billing, Budget Billing, AutoPay, and Other Billing Programs: Models to drive adoption of various billing programs and understanding program saturation. Recommend the right programs and services to the right customers, driving program growth as well as customer satisfaction and engagement.
- AI-Driven Customer Satisfaction (CSAT): Estimate daily CSAT scores at the household level to proactively engage customers based on levels of and reasons for dissatisfaction. These models generate a dynamic view into short-term and long-term drivers of CSAT, allowing you to optimize your resources for maximum impact.
- Residential and Commercial EV Adoption: Models to forecast and drive adoption of electric vehicles by residential and commercial customers, understand customer barriers for adoption, and identify infrastructural weak points that may require proactive investment to support future electrification.
You can use this highly sophisticated and targeted data in many ways, including:
- Foundational Customer Segmentation: Models that develop core foundational customer segments for your CX strategy.
- Reduce Cost to Serve and Increase Self-Serve Digital Engagement: Models to predict which customers will call, for what reasons, and when. Preempt calls by addressing customer needs proactively, arm customer services agents with insights to improve call handling times and first-contact-resolution, and appropriately staff your call center based on call forecasts. Additional models for driving self-serve digital engagement to further reduce call volume.
- Paperless Billing, Budget Billing, AutoPay, and Other Billing Programs: Models to drive adoption of various billing programs and understanding program saturation. Recommend the right programs and services to the right customers, driving program growth as well as customer satisfaction and engagement.
- AI-Driven Customer Satisfaction (CSAT): Estimate daily CSAT scores at the household level to proactively engage customers based on levels of and reasons for dissatisfaction. These models generate a dynamic view into short-term and long-term drivers of CSAT, allowing you to optimize your resources for maximum impact.
- Residential and Commercial EV Adoption: Models to forecast and drive adoption of electric vehicles by residential and commercial customers, understand customer barriers for adoption, and identify infrastructural weak points that may require proactive investment to support future electrification.
