What is a good close rate in solar? Nobody credible publishes one

A rep in their second month hears that top closers run 30%. They are sitting at 12%, they assume they are bad at this, and nobody in the room can tell them what the 30% was 30% of. That conversation happens in every solar office in the country, and it is entirely avoidable.

Every solar close rate published anywhere is self-reported. There is no registry, no audit, no standard definition, and no incentive for anyone quoting a number to quote a modest one. This page is about what to do instead.

We measured this and chose not to publish a number

We build a canvassing app, so we have a large amount of real door-to-door outcome data — and when we published door knocking statistics from it, we deliberately left the close rate out.

The reason is instructive, because it is the same reason everybody else’s number is wrong. Sale outcomes in a canvassing log are a door’s current status, not an event stamped at the moment of the knock. They get applied weeks later, updated when a deal firms up, and occasionally bulk-applied to an imported customer list. Run naive arithmetic over that and you get a door-to-door sold rate above 8%, which no one who has ever knocked a door believes for a second.

We could have published it. It would have ranked. Instead the honest version is: we can measure doors, answers and self-reported appointments, so those are what we publish, with a methodology section that says exactly what is excluded. Anyone quoting a precise national solar close rate without that section is reciting folklore.

What we can say, with the caveats attached

From 237,329 logged door outcomes across 7,241 real field days, derived 17 August 2026 from anonymised logs:

• Someone answers at 37.0% of knocked doors. Roughly two in three knocks reach nobody.
• Reps mark 5.8% of logged knocks “Appointment Set” — about one per 17.2 doors. That is the rep’s claim at the door, not a verified calendar event, and teams use the status differently.
• Renters account for 11.8% of all logged knocks, so a meaningful share of the conversations a rep has are with someone who cannot sign.

Notice that the funnel stops there. Between “appointment set” and “contract signed” sit two stages we cannot see from canvassing logs, and those two stages are where most of the variance lives.

Close rate of what, exactly

Walk the funnel and count the places the word gets attached. Each of these is somebody’s honest close rate.

1. Per lead. Deals divided by every lead worked, including the unreachable and the unqualified. The smallest number and the only one that maps to what a lead costs you.
2. Per contact. Deals divided by the people you actually spoke to. Quietly removes every data-quality problem from the measurement.
3. Per appointment set. Deals divided by appointments on the calendar. Popular, because it makes setters and closers both look productive.
4. Per appointment sat. Deals divided by appointments a rep actually ran. The number closers mean when they talk among themselves, and the largest of the four.
5. Per proposal delivered. Deals divided by presentations given. Larger still, and increasingly disconnected from anything a business plans on.

A rep who converts one deal from every three sat appointments and sits half of what gets booked has a 33% close rate and a 17% close rate at the same time, both truthfully. When someone quotes you a solar benchmark, the only question worth asking is which line of that list they are on.

Sit rate is where the money quietly leaves

The gap between “set” and “sat” is the least-managed stage in solar sales and the most expensive. A booked appointment that does not happen consumed a setter’s hour, a slot in a closer’s day, a drive, and — if it came from a purchased lead — the full cost of the lead. It then appears in no close-rate calculation anywhere, because nobody counts what did not occur.

There is no credible published sit-rate benchmark either, so measure it yourself, split by setter and by lead source. The pattern most teams find when they look for the first time is that one source books beautifully and sits badly, which had been hiding inside a blended close rate for months. Solar appointment setting covers the confirmation habits that move this stage more than any script change.

Why the definition matters more than the number

The figures in this section are round numbers chosen to make the arithmetic legible. They are illustrative, not benchmarks, and no company’s actual performance is implied.

Two reps both tell you, honestly, that they close 35%. Start each of them with 100 leads.

The first measures per sat appointment. Of 100 leads, 40 become contacts, 20 become set appointments, 12 sit, and 35% of those close: 4 deals.

The second measures per set appointment. Of 100 leads, 40 become contacts, 20 become set appointments, and 35% of those close: 7 deals.

Same claim, same funnel, nearly double the output — and if you are pricing leads off the first rep’s number while your business actually behaves like the second, every purchase decision downstream is wrong. The arithmetic that turns a close rate into a defensible lead price is in how to price a bought lead, and it is extremely sensitive to exactly this choice.

Build your own benchmark in six weeks

This is genuinely achievable and almost nobody does it. The requirements are boring:

• One definition, written down. Pick a stage, pick a denominator, date the document. Deals divided by appointments sat, in the week the appointment happened, is a good default.
• Cohort by entry, not by close. Track the 100 leads that arrived in week one all the way through, rather than dividing this month’s deals by this month’s leads. Solar sales cycles are long enough that the second method mixes two unrelated populations.
• Never blend sources. Self-generated, purchased shared, purchased exclusive and referral behave so differently that a combined rate describes none of them. Keep them in separate columns from day one.
• One owner. A single person responsible for the number, who is not the person whose performance it describes.
• Count the losses honestly. Including cancellations, failed credit, and the deals that never got installed. A signed contract is not revenue, and a close rate measured at signature flatters every downstream problem.

Six weeks of that is worth more than every benchmark you will ever read, because it is the only number that can tell you whether a change you made worked.

What moves it, roughly in order

• Lead source and exclusivity. The largest single factor, and mostly a purchasing decision rather than a selling one. How to buy solar leads covers what shared distribution does to everything downstream.
• Whether the person can actually sign. Renters, co-owners not present, homes in trusts, recent buyers who have not closed. Qualification failures look like closing failures.
• Speed to first contact. Unforgiving on purchased leads, where you are frequently not the only caller.
• Sit discipline. Confirmation calls, both decision makers present, and a booked time the household actually chose.
• Financing outcomes. A large share of solar losses are approvals, not objections, and no amount of rebuttal training changes a credit decision.
• What happens in the room. Real, coachable, and last on this list rather than first — rebuttals and objection handling is where that work lives.

When someone quotes you a number

Four questions, and you will rarely get four answers:

1. Close rate of what — leads, sets, sits, or proposals?
2. Over what period, and cohorted by entry or by close?
3. Which lead sources, and are they blended?
4. Measured at signature or at install, and net of cancellations?

A number that survives all four is worth listening to. In our experience of this market, almost none do — which is the strongest argument for measuring your own that we can make.

Disclosure: Scout Data is our product. We sell the data at the top of this funnel — verified ownership, roof and permit history, storm exposure and owner-matched contact — which is the first item on the “what moves it” list above, so read that section knowing who wrote it. We do not publish a close rate for teams using it, for the same reason we left one out of our door-knocking data: we would be quoting somebody else’s sales floor.

Frequently asked questions