Response Time vs. Booked Jobs in Home Services
Updated June 17, 2026
In home services, booking rate decays as response time grows. Modeling it as exponential decay from a 5-minute peak, a lead answered in 5 minutes books at roughly 40%, the same lead answered at 1 hour books near 24%, and by 24 hours it falls under 8%. The model says most of the booking is won or lost in the first hour — speed, not script, is the dominant variable.
Home-services buyers — a flooded basement, a dead furnace, a leaking roof — are buying urgency, not deliberating. They call several contractors and book the first one who picks up. That makes minutes-to-first-contact the single most predictive input for whether a lead turns into a booked job, yet most shops measure it in hours.
This is a transparent model, not a survey. Booking rate is computed as a decay curve anchored to a 5-minute peak, with the decay constant stated so you can reproduce the figures or stress-test them against your own call logs using the home-services response-time calculator.
Methodology
The model treats booking rate as exponential decay from a peak: booking rate = peak × 0.5 ^ (minutes ÷ half-life). The table fixes the 5-minute peak at 40% and the half-life at 50 minutes — meaning booking probability halves roughly every 50 minutes of delay.
A 40% peak reflects a strong but realistic same-minute close for an urgent service call; the ~50-minute half-life reflects the documented collapse in contact and qualification rates once response slips past the first hour. These are modeled outputs, not measured averages.
The curve assumes a single competitive market where the buyer is contacting multiple providers and books the first credible responder. Markets with less competition decay more slowly; emergency categories decay faster.
The data
| Time to first contact | Modeled booking rate | Share of peak retained |
|---|---|---|
| 5 minutes | 40.0% | 100% |
| 15 minutes | 36.7% | 92% |
| 30 minutes | 31.7% | 79% |
| 1 hour | 24.0% | 60% |
| 4 hours | 16.6% | 42% |
| 12 hours | 8.0% | 20% |
| 24 hours | 7.9% | 20% |
Booking rate computed as 40% × 0.5 ^ (minutes ÷ 50). Anchored to a 5-minute peak with a 50-minute half-life.
The first hour decides most jobs
Because the curve is steepest near zero, the difference between 5 minutes and 1 hour is enormous — the model puts a 5-minute response near 40% booking and a 60-minute response near 24%. That is a relative drop of roughly 40% in booked jobs from a single hour of delay, before the lead has talked to anyone else.
The practical reading is that response time is not a tie-breaker applied at the margin; it is the dominant variable. A mediocre pitch delivered in 5 minutes beats a polished one delivered the next morning, because by morning the buyer has already booked a competitor.
After a day, the lead is mostly gone
The tail of the curve is unforgiving. By 4 hours the model shows booking under 17%; by 24 hours it falls below 8%. A lead that sits in a voicemail box overnight has lost the majority of its value before anyone calls back — the spend that generated it is largely wasted.
This is why callback queues and next-business-day follow-up underperform so badly in home services. The asset depreciates by the minute, and a queue that clears in hours is selling a different, far cheaper product than one that answers in minutes.
Why coverage, not effort, is the constraint
Hitting a 5-minute response on every lead means answering nights, weekends, and lunch-hour spikes — exactly when an owner-operator is on a roof or under a sink. Human staffing can hit the peak occasionally but cannot hold it across the hours leads actually arrive.
An automated first response that texts or calls back within a minute, any hour, is what holds the lead near the top of the curve until a human can take over. BILT exists to capture that peak — turning the modeled 40% into the booking rate you actually realize rather than the one you theoretically could.
Frequently asked
How much does response time affect booking rate in home services?
In the model, a lead answered in 5 minutes books near 40% while the same lead answered at 1 hour books near 24% — roughly a 40% relative drop from one hour of delay. By 24 hours, booking falls under 8%. Most of the outcome is decided in the first hour.
Why does booking rate decay so fast?
Home-services buyers are urgent and contact multiple providers, so they book the first credible responder. The model treats this as exponential decay with a ~50-minute half-life — booking probability halves roughly every 50 minutes the lead waits, because a competitor is closing it in the meantime.
Can a small shop realistically respond in 5 minutes?
Not consistently by hand — leads arrive nights, weekends, and during jobs when the owner is unreachable. The model assumes a true 5-minute response every time, which only an automated first touch (text or callback) can hold until a human takes over.
Are these booking rates from a study?
No — they are a transparent model computed as 40% × 0.5 ^ (minutes ÷ 50), with the peak and half-life stated. The shape reflects documented speed-to-lead findings, but the exact numbers are illustrative. Reproduce them with your own peak and half-life in the response-time calculator.
The takeaway
Response time is the dominant predictor of booked jobs in home services because urgent buyers book the first credible responder. The model shows booking rate halving roughly every 50 minutes — a 5-minute answer books near 40%, a one-hour answer near 24%, an overnight answer under 8%. The job is won in the first hour, and only an automated first touch holds the lead near the peak until a human can close it.