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

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.

  1. 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.
  2. 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.
  3. 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.
  4. 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.

Calculator FAQ

What is speed to lead?
How long it takes you to give an inbound inquiry a real answer, measured from the moment it arrives. Not when it was seen, not when it was assigned to someone: when the prospect actually heard back with something useful.
Where do the coefficients come from?
The shape of the curve comes from two published studies listed in the sources section below: the Harvard Business Review analysis of online sales lead response, and the Lead Response Management study of qualification odds at five, ten and thirty minutes. The absolute caps are ours, and they are deliberately conservative.
Why not use the published ratios directly?
Because they are qualification odds ratios, and qualification odds are not closed revenue. At a four-hour response time the published ratio is in the hundreds, and multiplying anyone’s close rate by that would be indefensible. The calculator shows you that raw number for context, then applies a bounded uplift instead: a log ramp topping out at 2.5 times, with the resulting close rate capped at 50 percent.
Is this a forecast?
No. It is a directional estimate of the size of a gap, built to be argued with. That is why the arithmetic is on the page rather than behind the number. If your close rate already reflects fast response, the model will correctly tell you there is nothing to recover.
Does anything I type get sent to you?
No. The calculation runs entirely in your browser. There is no form, no submit button and no results email. We do record that a calculation was completed, as an anonymous analytics event, with none of your numbers attached.
What counts as my close rate?
The share of inbound leads that become customers, as a percentage. If you track it as deals per qualified conversation instead, use the leads-to-customer figure here, since that is what the model multiplies against your lead volume.
What if we already respond in under five minutes?
Then the model returns nothing to recover, which is the correct answer. Speed is only a lever where it is currently being lost, and if you are already fast the next gain is in qualification or follow-up rather than response time.
How would we actually get to a five-minute response?
Not by asking someone to watch an inbox. It requires a system that answers every channel automatically with something substantive, qualifies against your rules, and routes to a person only when it is worth their time. That is what we build.

Tell us what’s slowing you down.

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