Solar AI Quote Generator in Wisconsin

The intake form asks seven to nine questions tuned for solar: current monthly electric bill (the most important sizing signal), home square footage and number of stories, roof material (asphalt, tile, metal, flat membrane), roof age, primary roof orientation and shading (south-facing clear, south-facing with shade, mixed orientation), interest in battery backup (yes, maybe, no), interest in EV charger (yes, maybe, no), zip code (which the model uses to pull state incentive and net-metering rules), and an optional photo upload of the roof or a Google Maps screenshot. The form submits into n8n.

The workflow normalizes the inputs, runs them through an OpenAI prompt seeded with realistic system sizing logic (one kilowatt per one hundred to one hundred fifty dollars of monthly utility bill in most markets), per-watt installed pricing across Tier 1 panels (two-fifty to three-fifty per watt installed), premium panels (three-fifty to four-fifty), battery storage adders (eleven to fifteen thousand per Powerwall-class battery), EV charger adders, and the federal ITC at thirty percent, with state rebates and SREC values mapped by zip. The JSON estimate gets templated into a branded HTML email with the installer's logo, a system-size recommendation, the pre-incentive and post-incentive dollar ranges, an annual production estimate, and a payback period.

A matching SMS fires through Twilio. Total time from form submit to estimate in hand, around forty seconds.

Solar customers shop more bids than any other home services category. They have read the federal ITC paperwork, they have watched fifteen YouTube videos on net metering, they have used the EnergySage calculator three times, and they are gathering bids from Sunrun, Sunpower, the local installer, and a Facebook ad they clicked. The bid anchor matters enormously in solar because the customer is comparing per-watt rates, system sizes, panel brands, and payback periods across providers.

The installer who responds first with a credible per-watt rate, a correct system size, and a believable payback period wins the in-home consultation. Most local installers fail at the speed game because the sales rep is in an in-home consultation with another customer, the office is processing utility paperwork, and the inquiry from this morning gets a callback two days later. By that time the homeowner has already had Sunrun in for the in-home and signed a financing agreement.

The local installer sees the inquiry in their CRM, sees no booking, and assumes the customer went with the national brand. They did, because the local installer never got into the room.

A 6 kW system runs fifteen to twenty-two thousand pre-incentive, ten to fifteen thousand after the thirty percent federal ITC. An 8 kW system runs twenty to thirty thousand pre-incentive. A 10 kW system runs twenty-five to thirty-eight thousand pre-incentive. A Powerwall-class battery adds eleven to fifteen thousand.

Premium panel upgrades (SunPower, REC Alpha) add two to four thousand. A solar installer's gross margin on a residential install is roughly twenty to thirty percent, which means a 7 kW system at twenty-three thousand contributes four to seven thousand in margin. A local installer pulling fifty inbound inquiries a month and closing six at twelve percent close rate is below industry baseline. Push close rate to twenty-five or thirty percent on instant-quote leads, which is realistic because the homeowner is anchored to the installer who quoted first with a credible system size, and the installer adds six to nine extra closed jobs a month at a blended margin of fifty-five hundred.

That is thirty-three thousand to fifty thousand a month in extra margin on lead flow the installer is already paying for. The retainer pays for itself in the first week.

Complete n8n workflow with the Tally trigger, field normalization, OpenAI quote generation including ITC and state incentive math, email templating, and Twilio SMS dispatch. Tally form schema with solar-tuned questions, including the monthly utility bill question (the critical sizing signal), roof orientation, shading, battery interest, and EV charger interest. 0 California rules, NY-Sun, MASS solar tax credit, NJ SREC, Texas no-rebate framing) plus the federal ITC thirty percent calculation.

Branded HTML email template with system size, panel count, annual production kilowatt-hours, dollar range pre- and post-incentive, and payback period. Twilio SMS template with the headline net-of-incentive number. Setup guide for the OpenAI key, the Twilio number, the domain authentication, and the brand swap.

Also included: a three-touch follow-up sequence for unbooked quotes.

Wisconsin has 6 million residents distributed across major metros including Milwaukee, Madison, Green Bay, Kenosha, and Racine. Wisconsin's DSPS covers plumbing and electrical centrally. Milwaukee and Madison are the major metros.

The seasonality of solar work in Wisconsin is the single biggest factor that shapes how this ai quote generator actually performs in the market. Four-season cycle with winter heating dominant. Lake effect creates specific Milwaukee patterns. The template's qualification logic, dispatch rules, and conversation flow are tuned to handle these patterns rather than forcing the agency operator to customize from scratch. Shops that deploy this in Wisconsin markets see the seasonality framing show up in the conversations from the first call.

Regulatory framework for solar installers in Wisconsin varies at the local level rather than statewide, which is worth understanding because licensing references in customer conversations need to match local jurisdiction. The agent template handles this correctly by deferring licensing-specific questions to local context rather than asserting state-level rules that may not apply.

Plan four hours including the screen-share with the owner and the sales lead. You import the n8n workflow, paste the Tally form into the client's website, wire in their domain so the email comes from the installer name, swap in the logo and the brand colors, and test by submitting a fake quote for a 2,500 square foot home with a one hundred eighty dollar monthly bill, south-facing asphalt roof, no shade, interested in battery.

The pricing logic in the OpenAI prompt benefits from a real call with the sales lead: they will want to set the per-watt installed rate that matches their local install crew and panel supplier, set the panel brand premium based on which panels they actually sell (Q Cells versus SunPower versus REC), tune the battery adder pricing based on Powerwall versus FranklinWH availability in their market, and confirm the state incentive math for their service territory. That conversation takes forty-five minutes to an hour.

Once tuned, the system runs without intervention. Agency operators bill setup at eight hundred to fifteen hundred, retainer at four hundred to seven hundred a month, and the client pays gladly because two extra closed systems a month cover the retainer for five years.