Targeting for EE and DR Requires Two Flavors: Potential to Save and Propensity to Buy

Posted
on
March 14, 2024

The growth of energy efficiency (EE), demand response (DR), building electrification, electric vehicles (EVs), and other behind-the-meter energy technologies promises significant environmental benefits, substantial savings for consumers, and vital grid stability for utilities. However, the success of these programs hinges on a nuanced approach to finding the right customers. 

Download our fact sheet to learn more about Recurve's approach to targeting and Beneficial Electrification.

To identify ideal customers, targeting must first identify potential consumers who are likely to save on their bills and benefit the grid (propensity to save), and then from that pool of customers, find the ones most likely to participate (propensity to buy). 

This blog delves into the symbiotic relationship between these two targeting strategies, showing why they should not be viewed in isolation but as complementary strategies for driving the adoption of behind-the-meter energy technologies.

The Two-Pronged Approach: Propensity to Save and Buy

The journey toward successful EE and DR program implementation begins with identifying customers who stand to benefit the most from these measures. Recurve's pioneering approach to customer targeting uses smart meter data to predict which customers will save money on their energy bills when adopting specific technologies. 

In addition, meter-based targeting can show which customers will have the largest impact on greenhouse gas emissions and provide the greatest benefit for the grid. For example, in California, Recurve's real-time measurement of the impacts of electrification showed that the 25 percent of identified customers who used the most air conditioning in the summer were delivering nearly all of the summer peak savings by switching to a heat pump. These customers also provided much greater value to the grid, even when considering increased electricity use in the winter.

Sample Targeting Dashboard from Recurve's Resource Planner for the TECH Clean California Electrification Initiative. By tracking how customers use energy in real time, Resource Planner can predict which potential future customers will save most on their bills, reduce greenhouse gas emissions, and provide value to the grid.

However, identifying the right candidates is only half the battle. The next step involves honing in on those within this group who are most likely to take the leap and purchase or participate in these programs. This is where the propensity to buy modeling comes into play, incorporating factors such as eco-friendly inclinations, past purchases of similar technologies (like solar panels or EVs), and socioeconomic data to pinpoint customers more inclined to invest in these technologies.

Potential to Save measures customers' capacity to achieve significant energy bill reductions and contribute positively to the grid's efficiency and stability through the adoption of energy technologies. It assesses the suitability of different technologies for specific customers based on their current energy usage patterns, the physical characteristics of their homes, and other relevant data, ensuring that deploying these technologies results in tangible financial savings for the consumer and enhances grid reliability.
Propensity to Buy refers to the likelihood of customers purchasing or participating in energy efficiency, demand response, electrification programs, electric vehicles, and other behind-the-meter energy technologies. This metric is determined by analyzing factors such as environmental values, previous purchases of similar technologies, and socioeconomic data to identify those most inclined to invest in energy-saving solutions.

Harmonizing Customer and Grid Benefits

The essence of this two-step process lies in its ability to serve customer and grid needs while ensuring that marketing and outreach resources zero in on customers who are likely to say yes to an efficiency retrofit, heat pump, smart thermostat, or other measure. By first targeting those who will benefit most and have the most significant positive impact on the grid, utilities and program administrators can ensure that the technologies deployed are not only cost-effective for the consumer but also contribute to the overall health and efficiency of the energy system. This approach mitigates the risk of encouraging investments that, while appealing to the consumer, might lead to increased energy consumption or peak loads, counteracting the broader energy efficiency and grid stability goals. Narrowing this list down further to customers who have a propensity to buy further improves the chance for program success. 

This integrated and holistic approach allows for designing programs that achieve higher adoption rates and scale effectively. It ensures that deploying energy-efficient technologies leads to tangible benefits for consumers, the grid, and the environment. In doing so, it will enhance operational efficiency and customer satisfaction and contribute significantly to the broader decarbonization and energy resilience goals.

Interested in learning more about how meter-based targeting can complement your efforts to engage customers most likely to adopt energy-saving technologies? Reach out to explore how our targeted strategies can enhance your program's reach and effectiveness, ensuring higher adoption rates and a greater impact on both savings and the grid.

Learn How Data-Driven Targeting Can Optimize Program Impacts

Want to lean how your program can identify the highest-impact customers? Contact us for a targeting demo.

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