We research how AI surfaces commercial solar companies.
KMS Signal conducted research into the Arizona commercial solar market using 20 buyer-intent queries in Gemini, observing which companies were surfaced most frequently and what characteristics appeared among frequently mentioned companies.
20 queries, one market, repeatable method.
20 buyer-intent queries, run in Gemini, focused on the Arizona commercial solar market.
We observed which companies were surfaced most frequently, then looked for shared characteristics. These are observations, not published ranking factors.
Clear commercial-and-industrial focus rather than general residential language.
Named projects, system sizes, sectors, and outcomes published on-site.
Explicit service areas, metros, and regional coverage.
Certifications, specialisms, and capabilities that separate one provider from another.
Third-party mentions, directories, and press that confirm the same facts.
Relative consistency across the 20 queries — a qualitative reading of the sample, not a measure of any AI system's internal weighting.
What appeared among frequently surfaced companies.
Commercial specificity
Companies that clearly presented commercial and industrial work — rather than general or residential language — appeared more often in commercial buyer queries.
Detailed project evidence
Named projects with sectors, system details, and outcomes gave AI systems concrete material to reference.
Geographic information
Explicit service areas and regional coverage aligned companies with location-specific queries.
Distinctive attributes
Certifications, specialisms, and capabilities made some companies easier to distinguish from otherwise similar providers.
External corroboration
Third-party mentions and directories that repeated the same facts appeared alongside frequently surfaced companies.
How to read this research
These are observations from a limited sample on one platform in one market. They are not official ranking factors, and KMS Signal does not claim to have reverse-engineered any AI platform or to control what AI systems recommend. We publish this work to show how we think about the market, and because it informs where we look first during an engagement.
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