Five studies say faster wins. None of them measured a tradie, and none is Australian.
Every published study finds that responding faster to an enquiry wins more work, and every one is American, most vendor-funded, the most quoted from 2011. None measured a trade business and none is Australian. The direction is consistent enough to act on. The size of the effect for your business is unknown until you count it.
What does not exist, and where the data is sitting unpublished
There is no published study of how quote response time affects conversion for Australian trade businesses. There is none for any trade in any country. We looked for Australian sources first — the ABS, the trade platforms, the job management vendors — and then for anything in the building and services trades anywhere. Everything we found is below, and none of it is that.
The data exists. It is just not published. hipages alone reports over 100,000 jobs posted a month, a job every 25 seconds, more than 12 million to date, and 33,000 tradie members. hipages Group, quick facts, page dated 17 December 2025. Every one of those jobs has a timestamp on the request and a timestamp on each quote, and hipages knows who won. So do ServiceM8, Simpro, Tradify and Fergus, for every quote sent through them. None has published response time against win rate.
That leaves five American studies, four of them from companies selling speed. They are worth reading carefully rather than dismissing, because they agree with each other on direction, and because knowing exactly what each one measured is the difference between using them and being used by them.
The 2011 Harvard Business Review audit: the most quoted numbers, and what they actually measured
Researchers sent test web enquiries to 2,241 US companies and timed the response. 37% responded within an hour, 16% within one to twenty-four hours, 24% took more than a day, and 23% never responded. The average first response was 42 hours. Oldroyd, McElheran and Elkington, Harvard Business Review, March 2011. That last figure is often misquoted as 47; the paper says 42.
The finding everybody repeats: firms that tried to contact a lead within an hour were "nearly seven times as likely to qualify the lead" as those that waited even an hour longer, and "more than 60 times as likely" as those that waited a day or more. Oldroyd, McElheran and Elkington, Harvard Business Review, March 2011.
Three things to hold onto. "Qualify" means the company got to have a meaningful conversation, not that it won the work; the study did not measure sales. The 2,241 companies were selling to businesses online, not fixing hot water systems. And one of the three authors ran InsideSales.com, whose product was response speed, which does not make the audit wrong but does mean it was designed by someone who expected the result.
The vendor datasets: bigger, older, and skewed to industries that are not yours
The oldest study is the one people mean when they say "the MIT study". Between 2004 and 2007 an academic analysed six companies’ call data — more than 15,000 leads and 100,000 call attempts — for InsideSales.com, and found the odds of reaching a lead dropped 100-fold between a call at five minutes and a call at thirty, and the odds of qualifying it dropped 21-fold. It did not measure close rates. We could not retrieve the original report; those figures are as reproduced by a 2026 compilation that traced each figure to its primary source, fetched September 2026, which also notes the study predates smartphones.
The same vendor, renamed, revisited it with 5.7 million inbound leads across more than 400 companies between 2018 and 2020: conversion 8 times higher when the first call came within five minutes rather than six or more, under 1% of first calls made inside five minutes, 57.1% of first attempts taking more than a week, and 77% of leads never contacted. Reproduced by a second compilation with the same caveats, fetched September 2026.
Velocify, another speed vendor, analysed about 3.5 million leads around 2013 and reported that a call within one minute lifted conversion by 391% and that 93% of converted leads were reached by the sixth attempt — on a dataset weighted to mortgage, insurance and education. a second compilation with the same caveats, fetched September 2026. Those industries buy speed because their leads are shopping several providers at once. Whether a homeowner with a leaking tap behaves the same way is exactly the thing nobody has measured.
- KNDR·01HBR, 20112,241 US companies, test enquiries. 42-hour average, 23% never replied, 7x and 60x more likely to qualify. Qualification, not sales.
- KNDR·02InsideSales / Oldroyd, 2007Six companies, 15,000+ leads, 2004–07. 100x contact odds and 21x qualification odds, five minutes against thirty. Vendor data, pre-smartphone.
- KNDR·03XANT / InsideSales, 20215.7 million leads, 400+ companies, 2018–20. 8x conversion inside five minutes. 77% of leads never contacted. Vendor data.
- KNDR·04Drift, 2017433 B2B software companies tested. 7% replied within five minutes, 55% not within five business days. Live-chat vendor.
- KNDR·05Velocify, about 20133.5 million leads, mortgage, insurance, education. 391% lift inside one minute. Vendor data.
The 2017 Drift test, and the folklore that has no source at all
Drift filled in the demo forms of 433 business-to-business software companies and timed the replies. 7% — 32 companies — responded within five minutes. 55% had not responded after five business days. All ten of the fastest used live chat, which 14% of the 433 offered — and which Drift sells. Drift, lead response survey, 27 February 2017.
Then there are the numbers with no source. "78% of customers buy from whoever responds first" is repeated on hundreds of sales pages and traces to no published study anybody has located. "McKinsey found…" is attached to several response-time figures; McKinsey has published no such study. a 2026 compilation that traced each figure to its primary source, fetched September 2026. If a page quotes either without a link, the rest of its numbers deserve the same suspicion.
We are not above this. An earlier draft of this page had the 78% figure in it. It came out when we went looking for where it was from.
Why none of it transfers cleanly to a Brisbane plumber, and what does
Every dataset above is a business buying software or finance from a stranger online, comparing several vendors at once, with a sales team on the other end. A homeowner ringing about a blocked drain is a different animal: often urgent, usually local, frequently choosing between the two tradies who answered the phone. That should make speed matter more, not less. It should also make "within five minutes" the wrong unit — a returned call the same morning may be the whole game.
Two Australian figures sit either side of the gap without filling it. On how enquiries arrive: 32% of Australian businesses received orders online in 2024–25, barely changed from 2021–22, and 12% reported using AI. ABS, Characteristics of Australian Business, 2024–25, released 25 June 2026. Most enquiries into a trade business still come by phone, and a phone enquiry unanswered leaves no timestamp anywhere. On what happens after the quote is won: small businesses waited an average of 22.9 days to be paid in the June quarter of 2026. Xero Small Business Insights, Australia, June quarter 2026, published 30 July 2026. The pipe is measured at the money end and unmeasured at the enquiry end.
What does transfer is the shape. Five datasets, five industries, fifteen years apart, and the curve is the same: steep in the first hour, flat after a day. The size of the effect for your trade is unknown; its direction is about as well established as anything in this field gets.
How to measure your own in ninety days, from data you already have
Your job management system already holds the two timestamps that matter, or one of them. ServiceM8 and Simpro both record when a job or enquiry was created, when a quote was sent and when it was accepted or declined. Export ninety days of quotes. For each, compute the hours from enquiry to quote sent, and bucket them: under one hour, one to twenty-four hours, one to three days, over three days. Then the win rate in each bucket.
You will have a small sample and it will be noisy. It will still be the only number on this subject that describes your business, and it will tell you which bucket most of your quotes sit in — which is usually the more uncomfortable finding. The ServiceM8 and Simpro pages document which fields hold the timestamps and what the API exposes.
The gap the export will not show is the phone. Enquiries that went to voicemail and never became a job have no record. If you want that number, log missed calls for a fortnight against jobs created; after-hours and customer intake describe the plumbing that puts a timestamp on every enquiry so that next quarter’s export includes them. Then run the buckets again, and feed the result into the leak calculator as a conversion delta rather than a guess.
- KNDR·01Export ninety days of quotesCreated, sent, accepted or declined. Both systems hold these; the integration pages say where.
- KNDR·02Bucket the delayUnder an hour, under a day, under three days, longer. Win rate per bucket. Expect noise.
- KNDR·03Count the missed callsA fortnight of voicemails against jobs created. That is the bucket the export cannot see.
- KNDR·04Fix the slow bucket firstUsually quotes written on Sunday night for calls taken on Tuesday. That is a process fix, not software.
What we have not measured, and what would change this page
Nothing above is a Kindra measurement. This page was specced as one — first-party data on quote response time against win rate for Australian trade businesses, licensed for anyone to reuse with attribution. We have not collected it, so the page publishes what is published instead, with the dates on.
What would change it is not a survey. It is timestamps from job management systems — enquiry received, quote sent, quote accepted — across enough businesses and quarters to bucket honestly, on real Australian businesses, for long enough that the numbers stop moving. When that exists it gets published here with the sample size, the method and the cases where it failed, and the borrowed figures above come out.
If our own numbers turn out smaller than the ones vendors quote, they still get published. That is the point of measuring instead of asserting. Until then, the arithmetic section above runs on your figures, which are worth more than anybody’s average.
The questions people actually ask.
01Why is there no Kindra figure on a page filed under research?
Because we have not measured one, and a number you cannot show the working for is a marketing claim with a chart. What we could do honestly was find everything that is published, date it, put the sources that disagree next to each other and mark where the data stops. That turned out to be more useful than the page we set out to write.
02Everybody says respond within five minutes. Is that wrong?
It is a rule from industries where the customer is filling in five forms at once — mortgages, insurance, software demos — and it comes from vendors who sell the tooling to hit it. For a trade business the honest version is narrower: the studies agree that the first hour matters far more than the second day, and nobody has measured the minutes in between for your kind of work. Same morning is a defensible target. Five minutes is a sales pitch until someone publishes trade data.
03Doesn’t faster quoting mean sloppier quoting?
It can, and a fast wrong quote is worse than a slow right one, because you either eat the difference or start the job with a variation argument. The fix is to separate the response from the quote. Acknowledge inside the hour — a text saying when you will be there or when the quote will land — and then quote properly. The studies measured the first contact, not the document. Most trade businesses lose the job at the first step, not the second.
04Will you publish your own data on this?
When we have it and can show the working. That means timestamped enquiry-to-quote-to-outcome data across enough businesses to bucket honestly, with the sample size and the failure cases published alongside. We have not done that, and we would rather publish five American studies with their dates on than one Australian number we cannot defend.
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