As consumers, we constantly receive targeted ads in our inboxes, social media platforms, search results and more that offer suggestions as to what we should watch, listen to, buy or attend. Those ads are typically very relevant to us and in line with our preferences, because advertisers know that this behavioral science based approach makes it more likely that we will 1) pay attention and 2) respond to their call to action. 

This type of data-driven personalized outreach has transformed every aspect of the consumer marketplace. We’ve all come to expect that companies understand our wants and needs and will meet us where we are with tailored recommendations, and their energy providers are not immune to this expectation. 

Recognizing that this mindset is driving consumer behavior is particularly important as the utility industry increasingly needs the partnership of their consumers to participate in peak events and otherwise help alleviate peaks on the grid. Today, behavioral demand response programs must be framed around data-driven personalization, especially when it comes to calling peak events. Meeting customers where they are with an understanding of their energy use needs and habits will translate into messaging that is more impactful and, by extension, ensure greater peak event participation.

Avoiding Peak Event Fatigue

For example, when extreme heat impacted much of the United States and the world during the summer and fall of 2022, utilities and government officials in California, Texas and elsewhere not only broke generation records, they also made headlines for asking their customers to curtail their usage to prevent outages. Their peak event outreach campaigns included mass text alerts, emails, and social media posts asking every customer to conserve. In essence, the messages said “we’re all using a lot of energy. Please use less.”

The good news is that, for the most part, it worked.  Over the course of a few days, customers made what amounted to educated guesses as to how they could reduce their load, and utilities were able to avert mass blackouts.

But as extreme weather becomes more common and beneficial electrification continues to grow, consumers are going to be called upon to participate in peak events much more frequently and for longer periods. As those peak events become a more regular occurrence, blanket calls for non-specific actions will be  less effective. 

Without personalization and relevance, utilities risk creating a sense of “peak event fatigue” in which consumers become less interested in participating over time because calls to action are vague and don’t show consumers what behaviors they need to change. 

Engaging consumers in the sorts of numbers that will be required to ensure grid resiliency without direct load control requires precise requests for specific and relevant actions. Utilities need to educate each customer about their energy use on a per-appliance and day-and-time-of-use basis so that they understand exactly how they can make a meaningful contribution to reducing grid load. It comes down to targeted messages with recommendations about specific behaviors sent at the right time to the right person. 

Personalizing Peak Events

When it comes to providing consumers with energy insights that drive peak event participation, there are a variety of tools that can make a meaningful impact.

For example, when it comes to utility outreach, the goal is to evolve messaging from non-specific asks like “turn off or reduce nonessential power” to hyper-personalized and data-driven recommendations like “70% of your energy use is attributed to cooling during afternoon peak periods. Adjusting your air conditioning use during tomorrow’s peak event will help the grid. Pre-cool your home between 11 a.m. and 1 p.m. and then set the thermostat to 78 degrees until 6 p.m.”

On the self-service front, energy use activity maps allow customers to research their load profiles and learn which of their appliances use the most energy, and what days and times of day they use the most energy. With this personal level of detail, consumers are empowered with what choices they have at their disposal to make the greatest impact on the shift of their overall load. In the context of peak events in particular, an activity map empowers consumers to identify which of their energy use behaviors typically occur during the peak event time, and how they can change those behaviors to do their part to ensure grid resiliency. If the peak event is from 4 to 6 p.m. that day, and they typically charge their electric vehicle during that time, they know they can make a difference by shifting their charging to overnight instead of post-commute.

The guiding principle for all personalized outreach is that coaching consumers to change specific behaviors to outside the peak window will yield greater grid gains. 

Leveraging AI-Powered Data Science

Establishing the one-to-one consumer understanding that serves as the foundation for this personalized approach requires sophisticated machine learning and statistical solutions to analyze raw energy consumption AMI data. Bidgely’s advanced Time of Use (TOU) disaggregation breaks down household consumption to previously indiscernible granularity. This breakthrough level of precision opens up a new world of customer engagement possibilities for energy providers.

Granular energy use insights allow every step of a customer’s energy use journey to be both hyper-personalized with a clear explanation of the benefits they’ll realize for taking specific action based on how they use energy. Optimizing customers for success in this way is not only essential for peak event participation, but also to more effectively guide customers through billing, time-based rates, ongoing energy efficiency and more.

Learn more about how Bidgely’s Flex Demand and Analytics Workbench solutions empowers utilities and their customers with relevant, actionable energy insights to more effectively engage consumers in managing peak load.