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Solar Energy Evolution and Diffusion Studies Webinars

These webinars provide more information about the National Renewable Energy Laboratory's (NREL's) work on the U.S. Department of Energy's Solar Energy Evolution and Diffusion Studies (SEEDS) program.

SEEDS 2017-2019 Study Webinars

Using Machine Learning and Data Analysis to Improve Customer Acquisition and Marketing in Residential Solar

July 20, 2017
Presenters:
Kiran Lakkaraju, Sandia National Laboratories
Yevgeniy Vorobeychik, Vanderbilt University
Michael Rossol, NREL

A flow chart figure shows how promotion strategies and environmental variables feed into an adoption model, which can produce an aggregate adoption forecast.

Computer models, educated by existing solar adoption data, can help predict future trends in solar adoption.

High customer acquisition costs remain a persistent challenge in the U.S. residential solar industry. Effective customer acquisition in the residential solar market involves multiple moving parts: increasing referral rates, having a good ground game, and designing effective marketing campaigns. This webinar presented new research by NREL, Sandia National Laboratories, and Vanderbilt University on how data analytics, machine learning, and social science can improve residential solar marketing and customer acquisition processes.

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SEEDS 2014-2016 Study Webinars

Solar Aspirations and Disinclinations: Learning from 3,600 Households

June 29, 2016
Presenters:

Kim Wolske, University of Michigan
Mithra Moezzi, Portland State University
Ben Sigrin, NREL

A diagram shows the steps to adopting or not adopting PV, as described in a conceptual model for understanding lead conversion.

Conceptual model for understanding lead generation and conversion.

Drawing from a coordinated set of surveys of the general population—households that have adopted rooftop solar and households that considered solar, but rejected it—this webinar presents new data and insights about how people view solar and the varied paths to (and away) from installing rooftop solar in the United States. Results are based on detailed data collected from nearly 3,600 homeowners living in Arizona, California, New Jersey, and New York. While the majority of households in these states claimed some level of interest in solar, only a small fraction has adopted it. This webinar covered who was interested in installing solar and why, why households who have considered solar give up on installation, and who does not appear interested at all.

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How to Get Those Considering Solar to Ultimately Make the Switch

June 15, 2016
Presenters:
James Tong, Spruce Finance
Allison Mickey, Spruce Finance
Ben Sigrin, NREL
Eric O'Shaughnessy, NREL

A chart shows how PV adopters and non-adopters rate the significance of motives and difficulties in their decision to adopt or not adopt PV.

Customer surveys reveal important differences between solar adopters and lost leads (considerers).

Selling solar is a two-step process: getting customers to consider solar and then getting them to adopt. Even getting customers to consider solar is difficult as awareness is often opportunistic (e.g., installer approaches customers) or event-driven (e.g., sticker shock from summer bills or moving to a new house). This webinar presented results indicating opportunities for industry to increase lead generation and conversion rates. In particular, we identified differences between solar "considerers" (those who have spoken with installers about solar but haven't "pulled the trigger") and "adopters" (those who actually made the switch).

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Agent-based Models of How Segregation and Peer Effects Influence Solar PV Adoption

June 7, 2016
Presenters:
Adam Henry, University of Arizona
Georgia Pfeiffer, University of Arizona
Heikke Brugger, University of Konstanz
Ben Sigrin, NREL

An image shows a representation of a social network model: two clusters of nodes, representing agents in the model, intra-connected by lines (with a few lines crossing between the clusters).

Agent-based models are useful tools to understand how the physical or social structure of a community affects adoption of a new technology.

This webinar presented a series of theoretical agent-based models that explore the relationships between solar PV adoption dynamics, segregation, and incentive programs. Segregation can dramatically change the effectiveness of incentive programs, particularly from a distributional equity point of view. These theoretical models are also applied to historical PV adoption in metropolitan regions of the United States, and they are used to estimate the relative influence of peer effects, cognitive factors, and economic factors in solar adoption dynamics.

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