Community Solar Data
Subscriber counts, allocation credits, and churn rates for community solar programs -- the customer economics data that developers need to underwrite projects.
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Find Me This Data →Overview
What Is Community Solar Data?
Community solar data captures the operational and customer metrics that underpin shared solar projects, where multiple households subscribe to output from a single solar facility. This subtype includes subscriber counts, allocation credits tracking energy units per customer, and churn rates reflecting customer turnover—the core economics drivers that developers and investors use to underwrite project viability. Unlike rooftop solar, community solar removes barriers for renters and multifamily occupants, making it an equity-focused solar product class increasingly supported by state policies and federal incentives. Developers rely on this data to model project cash flows, estimate per-customer profitability, and assess customer retention risks.
Market Data
3,982 active subscribers
Community Solar Adopters in Sample (Colorado)
Source: ResearchGate
23,375 community solar subscribers
Largest State Dataset (New York)
Source: ResearchGate
Community solar adopters significantly more likely to live in multifamily buildings than rooftop solar adopters
Multifamily Housing Adoption
Source: ResearchGate
Community solar adopters more likely to rent compared to rooftop solar adopters
Renter Demographics
Source: ResearchGate
Who Uses This Data
What AI models do with it.do with it.
Project Underwriting & Development
Developers use subscriber counts and churn rates to model revenue stability and forecast customer acquisition costs. Bill management and customer turnover represent substantial operational costs that shape capacity allocation strategies.
Policy & Equity Assessment
State energy agencies and utility regulators analyze subscription data to evaluate whether community solar programs meet low-income and multifamily housing targets. At least 17 states have incentives or regulations promoting LMI community solar participation.
Investor Risk Analysis
Institutional investors assess project economics by examining customer demographics, income levels, and retention patterns to determine discount rates and IRR expectations. Renters pose higher turnover risk than homeowners.
Market Expansion Planning
Operators compare adoption demographics across states and income segments to identify underserved markets and optimize subscription marketing strategies.
What Can You Earn?
What it's worth.worth.
Subscriber-Level Data
Varies
Pricing depends on aggregation level (anonymized vs. identified), geographic scope (single program vs. multi-state), and historical depth. Individual project data often proprietary.
Subscription Data Feed
Varies
Specialized datasets tracking energy allocations per customer and monthly/annual churn rates command premium pricing due to operational forecasting value.
Demographic-Linked Datasets
Varies
Subscriber counts enriched with income, housing type, and renter status data typically license at higher tiers given equity-program validation use cases.
What Buyers Expect
What makes it valuable.valuable.
Current Subscriber Counts
Accurate, timestamped active subscription totals. Buyers distinguish between total enrollments and actively subscribed customers.
Allocation & Credit Transparency
Clear documentation of how energy allocations are credited per customer and billing methodologies. Standardized units (kWh, MWh, or percentage share) essential for modeling.
Churn & Retention Metrics
Monthly and annual turnover rates broken down by customer segment (residential, multifamily renter, LMI, anchor tenant). Reasons for attrition valued where available.
Demographic Alignment
Correlation of subscriber data with housing type, income level, and renter status to support equity program compliance and market segmentation analysis.
Companies Active Here
Who's buying.buying.
Aggregates and publishes community solar subscriber datasets across multiple states; primary source for comparative adoption research and policy evaluation.
Monitor subscriber demographics and program performance under IRA tax credit requirements and state equity mandates; use data for policy reporting.
Track internal subscriber growth, churn, and per-customer economics to optimize project sizing, customer acquisition strategies, and anchor tenant arrangements.
Analyze sector-wide and project-level churn, demographic composition, and income diversity to underwrite returns and structure non-recourse debt.
FAQ
Common questions.questions.
What is the key difference between community solar data and rooftop solar data?
Community solar data tracks shared system economics (subscriber counts, per-customer allocations, churn) across multiple households, whereas rooftop data focuses on individual system adoption and performance. Community solar emphasizes customer retention risk and collective billing, making churn rates and demographic turnover critical metrics.
Why do community solar projects care about churn rates?
Bill management and customer turnover represent substantial operational costs for community solar providers. Renters exhibit higher turnover risk than owner-occupants, so churn rates directly impact project cash flow and per-customer profitability assumptions used in underwriting.
Are community solar subscriber datasets publicly available?
Many are proprietary to utilities and state agencies. NREL publishes aggregated samples for research purposes covering states including Colorado, Illinois, Maine, Maryland, Massachusetts, and New York, but individual project data often remains confidential.
How does low-income (LMI) targeting affect community solar data collection?
At least 17 states have regulations or incentives requiring minimum percentages of LMI subscribers. This creates policy-driven demographic variation in subscriber profiles, with carve-outs and financial incentives influencing income distribution and renter adoption patterns across programs.
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