In 2002, the Oakland A’s discovered a new data-driven way to value players that would become the basis for the movie Moneyball. The basic premise is that the individual value of every single player can be calculated allowing you to compare value versus the cost of acquisition in order to optimize a lineup. In the same way Moneyball created a way to value and acquire baseball players, TROVE is helping utilities use a data-driven approach to value and acquire customers for their EE, DR, and DER programs.
As utilities pave the way to a Clean Energy Future, their customers are a more important part of the resource mix with continued focus on energy efficiency, a renaissance in demand response, distributed production resources with solar and storage, and growth in electric vehicles to decarbonize transportation. Just like with baseball players, there are customers who can provide exceptional value in your Clean Energy Game and the data is available to know who they are and get them signed up on your team.
The goal of the Clean Energy Game is to secure cost-effective customer resources that are as reliable as a power plant with the precision to be called at the feeder level. The key to winning this game is to build dynamic micro personas for every program that continually update with every marketing campaign. It’s analogous to knowing how every baseball player performs against every team in every ballpark and every pitcher to determine their value to your line up. As in Moneyball, this approach requires a utility to challenge conventional wisdom and let the data do the talking.
Conventional wisdom in most utilities is to operate from static company personas. There are typically 5-10 personas that segment the entire customer base and highlight key differences in demographics, behavior patterns, motivations and goals to help bring the unique characteristics of customers to life for employees. Most get labeled with catchy names like Sensible Savers, Urban Tech, etc. These have been around for a couple decades now and are useful in facilitating a culture that recognizes differences in customers beyond the foundational marketing age and income starting points. What they are not very good at is identifying the high value specific customers to add to your team and developing personalized offers that resonate with them.
They are Dynamic in that they are applied at program level. AI models crunch the data and return the differentiating attributes to segment customers without human bias, and finally the AI models are updated continuously to learn with feedback from each campaign. Micro in that the analytical models are applied at the individual customer level across over 650 residential and 350 commercial attributes based on specific program goals. Literally, every customer is evaluated and categorized for a particular program with estimates of their propensity to participate in the program and expected contribution towards your goal. This level of granularity also provides a new level of precision by being able to map and target customer resources across the grid down to the transformer level. Personas provide even more value in the dynamic micro world as they are the foundation for personalizing program offers to your high value customers. Bringing customers to life by highlighting the key attributes that define their micro persona informs go to market campaigns to get them to sign up on your team. Once you complete a campaign, it is important to provide the feedback to the models, so the data keeps doing the talking.
This approach is still new in the utility industry, but we are seeing micro personas with 2 to 4 times the resource contribution per customer. Dynamic Micro Personas are the basis for Utility Moneyball, data-driven solutions to help utilities achieve their program goals cost effectively by focusing on high value customer resources on the path to a Clean Energy Future.