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Lead intelligence

Speed to lead: what it is, and how to measure it honestly

The most reported number in pipeline reporting, and the most commonly measured wrong.

Valenza.io ·

In short

Speed to lead is the elapsed time between an enquiry arriving and a real reply reaching the person who sent it. It is measured from the enquiry's own timestamp, not from the start of the next business day: an enquiry that arrives at 9:42pm on Saturday and is answered at 10am on Monday has a speed to lead of thirty-four hours, not ten minutes.

Both the median and the worst case matter. The median describes the ordinary experience; the worst case describes where the expensive losses are, because the enquiries that wait longest are disproportionately the ones that arrived outside hours — and the ones that arrived outside hours are disproportionately the ones from people deciding something seriously enough to ask at 9:42pm.

The three ways it gets measured wrong

Each of these produces a flattering number, which is exactly why each is common.

Starting the clock at the next working hour
The most common error. It defines away the entire problem: every out-of-hours enquiry is scored as if it arrived when someone was available to answer it.
Counting an auto-acknowledgement as a reply
'Thanks, we have received your enquiry' is not a reply to the question that was asked. A real reply engages with what the person wanted; anything else measures the auto-responder rather than the business.
Reporting only the mean
One rapid Monday morning hides a weekend. The mean of a distribution with a long tail is not a description of anyone's experience — report the median and the worst case instead.

Why it moves first, and why it is not enough on its own

Speed to lead is a property of the system rather than of the sales process, which is why it is the first number to change when the infrastructure changes and the first thing a business can verify for itself.

It is not sufficient. Speed decides the enquiries lost while waiting; capture decides the ones that were never visible to answer at all; qualification decides whether the fast reply reached the right person; follow-up decides the ones answered once and then abandoned. Fixing speed alone moves the number and then exposes whichever stage is leaking next.

The external evidence most often cited is a study of 2,241 companies published by Harvard Business Review, which found an average response time of 42 hours and a large qualification advantage for firms responding within an hour. It is a useful order-of-magnitude reference and a poor substitute for a business measuring its own distribution.

What to record per enquiry

Speed to lead is only interpretable alongside the facts that explain it, which is what Valenza.io's lead intelligence layer records for each enquiry: the channel it arrived on, the hour and day it arrived, whether it was answered at all, how long the first real reply took, the qualification result, the stage reached, and where it stopped.

With those fields, a sentence like 'our conversion is poor' becomes 'forty-one per cent of enquiries arriving after 7pm were never answered' — which names a stage, a channel and a time of week, and therefore names a fix.

Questions people ask

What is a good speed to lead?

Faster than the businesses the same person also enquired with, which is the only benchmark that decides anything. In practice that means seconds rather than hours, at every hour, and the useful internal target is to compress the worst case rather than to improve the average.

Does an automated reply count?

An acknowledgement does not. A reply that actually engages with what the person asked does, whether a person or a system composed it — and in Valenza.io's implementation that reply is written in the business's own voice from material the business approved, with sensitive conversations handed to a human immediately.

How do we measure it if enquiries arrive on five different channels?

You consolidate first. Speed to lead is not measurable across channels that are not in one pipeline, which is why capture is the stage that has to be fixed before the number means anything.

Run the same arithmetic on your own pipeline.

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