Event Summary
Do you need to understand income-qualified customers to guide marketing or increase participation in your affordability programs? How are you reaching underserved communities that haven’t participated before? Utilities can better connect with these customers by using data science for targeted engagement.
This session will provide an overview of predictive analytics, data science, and customer program design. We’ll conclude with breakout groups to develop actionable frameworks you can apply within your organization to drive positive change.
Attendees will receive 1 Professional Development Hour (PDH) upon completion.
Course Objectives
- Understand the fundamentals of predictive analytics
- Discover how data science can improve programs for low- and moderate-income and at-risk customers.
- Identify program design gaps and learn how data science can address them
Who Should Attend
- Low-income Program Managers
- Billing and Customer Care Team Members
Meet Your Instructors
Devon Grodkiewicz
Data Science Solutions Advisor, E Source
Devon joined E Source in 2022 as a Data Science Solutions Advisor, promoting data science through webinars, blogs, podcasts, and conferences. He helps utilities tackle challenges and improve operations using E Source’s data science solutions. Before E Source, Devon launched and sold a technology startup out of Northeastern University, where he earned a BS in environmental science with a focus on geospatial data science.
Bob Cooke
Executive Consultant, E Source
Bob is an executive consultant at E Source specializing in customer interaction and Meter-to-Cash operations, including contact centers, credit and collections, digital/self-service channels, billing, and payments. Recently, he’s focused on reducing arrears through targeted communications and treatment programs, supporting low-income assistance, and leading the transition to a unified customer self-service platform.
