Why We’re Bringing Machine Learning to the Consumer Energy Market  

As you may have read in Fortune or Fast Company today, PowerScout just announced that it has secured $5.2 million in funding for technology that lowers the price of clean energy. How? By predicting which homes are most likely to adopt it. Yep. We’re aiming to be the Nate Silver of solar. We’re also making the process of shopping for and buying clean energy a lot easier and more transparent for consumers. 

(More on that piece in a bit.) 

First, we want to talk a little about the funding, because it directly relates to one of our biggest ambitions at PowerScout. The funding was provided by a mix of private and public sources including the U.S. Department of Energy, which awarded PowerScout a total of $2.5 million in grants via its well known SunShot Initiative 

Now, the SunShot Initiative is an effort aimed at making solar cost competitive with traditional grid power and predictive analytics has the potential to do be a huge lever on that. It’s not well known, but when you go solar through a traditional provider today, you often end up paying more to cover the company’s marketing expenses than for the panels themselves. Predictive analytics can shave a huge portion off the price tag of solar because it eliminates the cost of finding homeowners who want clean energy. 

It makes a lot of sense, actually, because for years, the retail, transportation, and financial services industries have all been benefitting from predictive analytics, prescriptive analytics, machine learning, and cognitive computing. These technologies introduce more predictability and stability into the sales funnel and supply chain alike, which has a calming effect on costs. We think it’s time these technologies benefit today’s energy consumer. After all, electricity bills are increasing at a rate that outpaces inflation and investor-owned utilities don’t have much real incentive to help you understand your own patterns of power use, so our aim is not only to make solar more approachable by lowering costs, but to usher in an era of more data-driven pricing and greater consumer choice in general. 

So, how does the predictive part work?  Well, our Foresight platform uses a bunch of different sources including high res rooftop analysis, LIDAR data collected by planes, and in-depth consumer data to analyze entire neighborhoods at a time. We tag each home with over 1200 data points ranging from income and education levels to political affiliation and even the type of car someone drives. The platform analyzes which houses in the neighborhood already have solar panels then it crunches all that data to make predictions about which other households in the area will benefit from the most from clean energy, aka see the greatest return on investment. 

In addition to predictive analytics, PowerScout is aiming expand what’s sometimes called “the connected economy” by creating value around the entire process of buying clean energy. It’s surprising, but some of the world’s largest solar and clean energy companies actually still rely on the same high pressure, door-to-door tactics used to sell vacuum cleaners in the 1950’s. As we’ve already said, that adds a lot of cost for the consumer in the end, but it also tends to be really uncomfortable for them as well. Call us crazy, but we think people should be able to shop for clean energy the way they shop for other things: online and without pressure. PowerScout is just a better way to discover and buy clean energy.

If you’d like to see how PowerScout rates your home’s overall solar potential , just enter your street address directly on the PowerScout home page. On that platform, you can also get firm solar price quotes on a system and installation by experienced local providers in your area (in 15 states and counting). For added support, we have a team of subject matter experts known as PowerScout Concierges available by phone (650-999-9900) , video, and chat.