Switchgear manufacturer (name under NDA) · Low-voltage electrical panels · Italy
2 days
to a priced quote, instead of about 10
Quoted by hand. Then not.
3 weeks
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Why the first quote wins, and why nobody can prove it
Lost requests leave no trace. Here is what the research on response time says, and how to see your own numbers.
Every salesperson believes the first credible quote has an advantage. Almost no company can show it in its own numbers. The reason is simple: a request that went to a faster competitor leaves no record. It doesn't appear as a lost deal. It just never becomes a deal.
What the research says
The best-known study is old, but nothing comparable has replaced it. Researchers looked at 1.25 million online leads at 42 US companies and timed how quickly companies responded (Harvard Business Review, The Short Life of Online Sales Leads).
7×
more likely to reach a decision-maker when answering within an hour, compared with an hour later. More than 60× compared with a day later.Harvard Business Review, 2011
The same researchers checked how 2,241 companies actually replied. 37% answered within an hour. 24% took longer than a day. 23% never answered at all. The average was 42 hours.
Two caveats. The data is from 2011, and most leads were online consumer enquiries. For a manufacturer receiving a drawing, an hour is not realistic. But the direction holds: interest decays, and it decays faster than most companies assume.
Manufacturers lose requests in a quieter way
In manufacturing the problem is usually not the first reply. It is the priced quote.
Before its rules went into a system, a Danish supplier of cement plants answered only half the requests it received. Quotes took three to five weeks. Afterwards it answered all of them in one or two days (Hvam et al., 2013). Half its market had been invisible.
In a vendor-commissioned benchmark, 75% of best-in-class companies issued quotes in two days or less (Aberdeen). Treat that as an industry estimate, not a law. It still tells you where the competition sits.
Why nobody can prove it
Ask a sales team how many quotes were lost to speed last quarter and you will get a guess. There are three reasons.
- Requests are not logged. They arrive by email, phone and WhatsApp. Only the ones that turn into quotes enter any system.
- The clock isn't recorded. Nobody stores when a request arrived and when the price went out.
- Lost reasons are not asked. A customer who went elsewhere rarely says why unless asked.
The result: slow quoting is a cost that never appears in a report.
Four fields that make it visible
You don't need a new system to start. You need four fields for every request:
- Date and time the request arrived.
- Date and time the priced quote was sent.
- Outcome: won, lost, no answer.
- If lost: the reason, in the customer's words.
After a quarter, sort lost quotes by response time. If losses cluster above a certain number of days, you have your threshold and your business case.
For the panel maker in Quoted by hand. Then not., we built this into the system from day one. The director's dashboard shows time to quote, conversion, the funnel with amounts at each stage and a list of orders sitting in one stage for more than 14 days, each one clickable. A priced quote now takes about two days instead of ten.
Speed is part of loyalty
68% of B2B executives say customers have become less loyal (Bain). 54% of decision-makers say they would drop a purchase or switch supplier after a bad experience in a channel (McKinsey B2B Pulse, via European Business Magazine). A ten-day quote is a bad experience, even when the price is right.
Cost calculator
What to do this week
Pick the last 30 requests. Find when each one arrived and when the quote went out. If you cannot find those dates, that is the first finding.
Related: Why your quotes take ten days · What a phone order really costs a manufacturer
Questions
How fast should we answer a B2B enquiry?
As fast as you can. In the Harvard Business Review study of 1.25 million leads, companies that replied within an hour were nearly seven times more likely to reach a decision-maker than those that replied an hour later.
Is the response-time data relevant for manufacturers?
As a direction, yes. The data is from 2011 and mostly US online leads, so treat the multipliers as an illustration, not a constant.
How do we know how many quotes we lose to slow answers?
Record four things for every request: the date it arrived, the date the quote went out, the outcome and the reason if it was lost. Within a quarter the pattern is visible.
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