Beyond the Panels: Why Solar Success Hinges on Accurate Initial Data

Customers are souring on the idea of solar panels and that should spell concern for anyone with a solar business. Some 66% of homeowners in a recent survey shared that cost savings motivated them to install panels on their roofs, but 75% of homeowners with solar panels reported no change or an increase in their electricity bill, and only 25% see a reduction in their electricity bill.

Failures to maintain or adhere to solar expectations is doing more than generating dissatisfaction; it’s generating negative press too.


The primary concern? How systems have not delivered the corresponding economic benefits that the homeowner/hosts thought they would receive. As those concerns continued to pile up, they have cast a long, dark shadow on the residential solar sector as a whole. There was and is a sense from consumers that maybe residential solar electricity is a lot of sunny hype but not worth the investment because of the cloudy outlook on promised returns.

Pete Cleveland

We know that’s not true.

The problem between customer expectation and solar performance is fundamentally a data issue that relates directly to the solar workflow, and ultimately winds up impacting operations and management providers. This data inaccuracy starts much earlier in the solar workflow process during quoting, site audits, and installation. Yet, it becomes a headache for operations and management (O&M) teams that are responsible for responding to customer inquiries when production expectations are not met by actual production output.

Solving an Industry Problem

This is an industry problem that can be improved with better initial processes and inputs. By focusing on better upfront data, solar providers can help drive better customer experiences and outcomes while also delivering improved economics and referral sales dynamics for their businesses.

To illustrate, when businesses need to focus on labor-intensive site visits using inaccurate data, it can increase the downstream time needed for resulting design-related changes, cancellations, and delays on system installations. That negatively impacts the solar provider’s cash-flow and leads to unsatisfied customers who send fewer referrals.

However, if businesses focus on accurate upfront data collection, analysis, and implementation, they can create more optimal systems with less labor time. This improves scalability, speed to install, and cash flow. Plus, it results in more satisfied customers who enjoy the benefits of those systems, who increase referrals which then reduces the overall cost of acquisition for any customer.

Optimized Workflow

In contrast to the inefficiencies of the traditional solar lead to close-out workflow, an optimized workflow leverages advancements in software and remote measurement technology to collect and leverage high-accuracy data. As a result, the optimized workflow enables installation-ready designs that optimize available roof space, shorten project timelines, reduce labor and the opportunity for human error, increase profits, customer satisfaction and referrals, and empower companies to scale.

To summarize, many of the challenges O&M teams face when addressing system production concerns—and associated dissatisfaction—of residential homeowners are not technical issues at all. They are the result of unfulfilled expectations caused by faulty and inaccurate inputs at the start of the quoting, site audit, and installation processes. The residential solar industry, for its long-term health and ability to more effectively attract customers, can eliminate such dynamics through the use of better data and analytics and by employing more accurate production projections to better manage their end-user expectations.

Here are a few suggested tactics and techniques that solar providers need to think about employing to help eliminate downstream customer dissatisfaction and limit the impact on O&M teams:

  • More accurately determine a home’s true solar potential at the start of discussions with the homeowner/host. That analysis must include physical orientation of the roof, total annual hours of direct sunlight, shading, and roof capacity for panels including appropriate setbacks, obstruction detection and production modeling.
  • Educate the homeowner/host on site modeling and PV simulation technologies.
  • Educate the homeowner/host on how weather variations can impact system production output from year to year.
  • Set realistic expectations for annual minimum and maximum potential electricity production for the system.

If these changes do not occur, the solar industry will begin to suffer and the progress that has been made with federal and commercial partners will begin to falter. Let’s not let bad data have that big of an impact. This is something we can solve.

Pete Cleveland is the vice president of solar for EagleView, where he pursues his passion for evolving the solar industry by applying technology to solve real-world problems.

SHARE this article