U.S. Residential Solar PV Customer Acquisition: Strategies, Costs and Vendors
Customer acquisition currently accounts for about 10% of overall residential solar system costs but has great near-term potential for cost reduction. PV hardware costs, especially those of modules, are beginning to bottom out, and installers are looking at soft costs to save time and money. While some soft costs such as permitting will primarily be reduced with government support and industry lobbying, installers can make changes to their lead generation strategies, allocation of resources, software used, and other external services procured to reduce customer acquisition expenses. GTM Research estimates that residential solar customer acquisition currently costs installers $0.49/W. Over the next four years, this cost will fall to $0.35/W, saving the industry a total of $619 million between 2014 and 2017.
Leading residential solar companies have taken notice of the need for innovation and cost reduction in customer acquisition. A wide and varied landscape of software and service vendors has begun to take shape, and several acquisitions of these vendors have already occurred. This marks the beginning of what we expect to be among the most active spaces for innovation, mergers and aqisitions, and differentiation in the U.S. solar market for years to come.
FIGURE: Solar Customer Acquisition Service Providers
The focus of this 45 page report by GTM Research is the increasingly complex ecosystem of vendors active in the customer acquisition space as well as the strategies preferred by the leaders of the US residential solar market. The key objectives of this report are to:
• Describe the benefits, difficulties, and costs associated with the most common marketing and lead generation channels
• Highlight the customer acquisition strategies of the leading residential solar financiers and installers
• Identify vendors of customer acquisition tools, including both software and services
• Provide our outlook on trends in customer acquisition and a forecast for cost reduction
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