Free tool
What is slow lead response costing you?
Four numbers you already know. The model uses published response-time research for its shape, applies two deliberately conservative caps on top, and shows you every step. Nothing you type leaves your browser.
Your numbers
Estimated revenue lost to slow response
over twelve months
The math, in full
- Response time entered:
- Published qualification odds ratio at that response time: (not used directly, see below)
- Applied uplift, bounded log ramp from five minutes to twenty-four hours:
- Close rate today: , modelled at a five-minute response:
- Deals per month today: , modelled:
- Difference, multiplied by average deal value: per month
Fill in the four fields to see the estimate and the arithmetic behind it.
How the model works
The calculation has four steps, and none of them are hidden.
- Your baseline. Monthly leads multiplied by your close rate gives deals per month; multiplied by average deal value, that is the revenue your current response time produces.
- The published penalty, shown but not used. Your response time is placed on a curve of relative qualification odds indexed to a five-minute reply, interpolated logarithmically between the anchor points below. At four hours that ratio is already in the hundreds. We display it, and then we do not use it, because qualification odds are not closed revenue and multiplying a close rate by 300 is not a model, it is a lie with arithmetic on it.
- The uplift we actually apply. A bounded ramp, logarithmic in response time, running from one times at five minutes to a hard ceiling of 2.5 times at twenty-four hours. The research contributes the log shape and the anchors; the ceiling is ours. The resulting close rate is additionally capped at 50 percent, and the page says so when that cap bites.
- The difference. Modelled deals minus current deals, multiplied by your average deal value. That gap, monthly and annual, is the output.
The honest framing: this estimates the size of a gap, not the revenue you will book. It exists to answer whether response time is worth doing something about, and it is deliberately built so you can argue with the arithmetic instead of trusting the headline.
Sources
- James B. Oldroyd, Kristina McElheran and David Elkington, "The Short Life of Online Sales Leads", Harvard Business Review, March 2011. Firms that attempted contact within an hour of an inquiry were far more likely to qualify the lead than those that waited an hour longer, and dramatically more likely than those that waited a day.
- Lead Response Management study, James B. Oldroyd (2007), reporting how sharply the odds of qualifying a lead fall between a five-minute, a ten-minute and a thirty-minute response.
Anchor points used, expressed as relative qualification odds against a five-minute reply: 5 minutes = 1.00, 10 minutes = 0.25, 30 minutes = 0.048, 60 minutes = 0.040, 2 hours = 0.0057, 24 hours = 0.00067.
What to do about it
Getting to a five-minute response is not a discipline problem, it is a systems problem. Nobody running a business can watch six inboxes. What works is a single intake across every channel, an automatic first reply with real substance in it, qualification against your own rules, and a human involved only once the conversation is worth their time.
That system is described in full on the AI lead response page, and the practical version of the problem by trade is on the industry pages. If you want the step-by-step for one specific case, we wrote up how to automate website quote requests.
On the phone the window is shorter still, and the fix is a single automatic text. The missed call text back generator writes the four messages that job needs: it is the same argument as this page, applied to the channel where the gap is measured in seconds rather than hours.
The evergreen companion to this calculator is the speed-to-lead guide: what the published research does and does not establish, where response time actually leaks, what counts as a real first reply, and how to measure your own median this week.