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The Evidence

The research behind
the system.

Everything we sell rests on findings that other people measured. This page collects them with their sources, their sample sizes and their limitations — including the places where the numbers get quoted more confidently than the underlying studies support, and one case where the most repeated statistic in the industry turns out to have no source at all.

You will not find client names or client results here. Every lead source behaves differently, and past results from one operation are not a forecast for another. We would rather argue from evidence you can check yourself.

Speed

Why the first hour decides most of it

The most quoted finding in this field is also the most consistently misattributed. The multipliers below come from the Lead Response Management study led by Dr James Oldroyd, then at MIT Sloan, produced in partnership with InsideSales.com. They are not from Harvard, and a page that tells you they are has not read either study.

What the analysis asked was narrow and useful: given a lead that arrives through a web form, how much does the delay before the first outbound call change the odds of reaching that person, and of that conversation going anywhere.

100×drop in the odds of contact, calling at 5 minutes versus 30
21×drop in the odds of qualifying over the same window
42 hrsaverage first response across 2,241 audited US firms
23%of those firms never responded at all
SourceOldroyd, J., with InsideSales.com. Lead Response Management Study, 2007.
SampleThree years of data across six companies — more than 15,000 web-generated leads and over 100,000 call attempts. A separate survey portion polled 495 companies across 40+ industries between June and September 2007.
SecondOldroyd, J., McElheran, K. and Elkington, D. The Short Life of Online Sales Leads, Harvard Business Review 89(3), March 2011 — the audit of 2,241 US firms, the 42-hour average and the 23% non-response figure.
AlsoThe HBR article draws on a further dataset of 1.25 million leads across 29 B2C and 13 B2B US companies: firms attempting contact within an hour were close to seven times as likely to qualify a lead as those trying an hour later, and more than sixty times as likely as those waiting a day.
Where this stops being reliable. The 2007 work is vendor-partnered research presented at an industry summit, not a peer-reviewed MIT publication, and the underlying data skews toward mortgage, insurance and education. The figures are odds ratios, not close rates — a 21× change in the odds of qualifying is not a 21× change in revenue. "Qualified" here means a meaningful conversation with a decision maker, not a sale. And the data predates the smartphone era, which has almost certainly tightened the window rather than loosened it, but that direction is an inference and not something the study measured.
Persistence

The gap between two attempts and six

Almost every agency selling follow-up quotes the same pair of numbers: that 80% of sales require five follow-ups, and that 44% of salespeople give up after one. Both are attributed to the National Sales Executive Association, an organisation with no verifiable existence. Neither figure traces to a study. The percentage breakdown that usually accompanies them was popularised by a marketing advice page that has since been taken down.

We do not use those numbers. The traceable evidence points the same direction, which makes the folklore unnecessary as well as wrong.

93%of converted leads were reached within six call attempts
50%of inbound leads were never contacted a second time
3.5Mlead records in the dataset
SourceVelocify. The Ultimate Contact Strategy, 2013.
SampleApproximately 3.5 million lead records across multiple industries, drawn from companies using the platform.
Where this stops being reliable. This is vendor data from a company selling sales-acceleration software, and the participating firms defined "converted" themselves. The six-attempt figure is also conditional on conversion — it describes leads that did convert, so it tells you where to stop rather than proving that a sixth call causes the outcome. Read it as a practical ceiling on persistence, not as a promise that more dials produce more sales. Beyond that range, the same body of work finds returns fall and opt-outs climb.
Reputation

What review count and recency actually do

Review expectations moved faster in the last year than in the previous five. The thresholds below are what consumers say they apply before they will consider a local business at all — which makes them a gate rather than a ranking advantage.

The recency finding is the one most owners are unaware of. A profile with a strong rating and no recent activity reads as a business winding down, and most owners have never looked at the date on their own newest review.

47%will not use a business with fewer than 20 reviews
74%prioritise reviews written in the last three months
31%will only use a business rated 4.5 stars or higher — up from 17%
81%expect a response to a review within a week
SourceBrightLocal. Local Consumer Review Survey 2026, published February 2026.
SampleA representative panel of 1,002 US adult consumers.
AlsoThe same survey records 45% of consumers using AI assistants for local business recommendations, against 6% a year earlier, while Google's share of local business discovery fell from 83% to 71%.
Where this stops being reliable. This is a consumer survey, so it measures stated preference rather than observed behaviour, and people reliably over-report how carefully they deliberate. It is run by a company that sells reputation software. The panel covers local business generally, not solar specifically, and year-on-year jumps as large as the star-rating one can reflect changes in question wording as much as real shifts in attitude. Treat the thresholds as directional, and the direction of travel as the more reliable signal than any single percentage.
The market

US residential solar after the credit reset

This is the public half of our market briefing. The Section 25D residential clean energy credit ended on 31 December 2025 as a hard cliff, with no phase-down, and 2026 is the first full year the market has run without it.

The consequence that matters for anyone buying leads is not the volume decline on its own. It is that acquisition cost is rising while the pool of buyers shrinks, so the same marketing spend now has to survive a harder market.

+40%forecast rise in residential customer acquisition cost in 2026
$0.84/Wthe 2026 CAC forecast, against $0.60/W in 2025
18–21%forecast contraction in residential installations in 2026
SourceWood Mackenzie. US distributed solar customer acquisition cost outlook 2026.
SecondSEIA and Wood Mackenzie, US Solar Market Insight — distributed segments forecast to decline in 2026, with recovery expected from 2027.
ContextThe 2025 CAC figure of $0.60/W was a five-year low produced by the rush to install ahead of the deadline, so the 2026 rise is measured against an unusually favourable base. Third-party ownership is absorbing part of the gap, moving from roughly 45% of residential installations toward a clear majority.
Where this stops being reliable. These are forecasts rather than outcomes, and they have been revised more than once during the year as quarterly data has landed. National averages also conceal wide state-level variation — California, with its own policy structure and utility rates, has not behaved like the national picture. Anyone quoting a single number for "the US solar market" in 2026, ourselves included, is simplifying something that is behaving very differently in different states.
The standard

Every figure on this page is traced to the study that produced it, with its year and its sample stated. Where a widely repeated number could not be traced to a source, we have left it out and said so rather than passing it along.

None of this is a projection of what will happen in your operation. It describes market conditions and measured tendencies, both of which are public. What we do with them is not, and we do not publish our call approach, our objection handling or our cadence.

If you would rather see this against your own numbers than in the abstract, we will walk through the same material on a call.

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