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The answer sits in your own booking history. A method to build your booking curve and set a review rhythm from it.
By the DayRunner team ·
Change prices while there's still enough demand left to book. Make the big moves in the window where most of your bookings arrive, and only small corrections after that. Your own booking history tells you how many days out that window is, by month and car type. Nobody else's data can.
This guide shows you how to work it out from a booking export and a spreadsheet.
You'll see posts that say "change prices 60 days out" or "most bookings land three weeks before". Those numbers come from someone else's fleet, customers and channels.
A ski-season operator in Queenstown, a city-centre brand in Auckland and a campervan fleet will have very different booking windows. International visitors tend to book earlier than locals. Broker bookings arrive on a different pattern from direct ones.
We also want to be straight about what Rate Pulse can and can't tell you here. It shows market rates for the next 14 pick-up days, one snapshot a day, with each new snapshot replacing the last. It doesn't keep history yet, and it doesn't look further than 14 days. So it can't show you how the market moves as a date gets closer. Your bookings can.
Lead time is the number of days between the day a booking was made and the pick-up day. A booking made on 1 November for a 15 November pick-up has a lead time of 14 days.
The booking curve is the share of a period's final bookings that were already on the books at each lead time. If 40% of December's final compact bookings were made 60 or more days out, the curve reads 40% at 60 days. See booking curve.
Once you have the curve, the question "how far ahead?" answers itself. You change prices where the curve is still climbing.
One row per booking, with the date it was made, the pick-up date, the car type, the number of hire days and the status. Include cancelled bookings, flagged.
In a new column: pick-up date minus booking date, in days.
Use pick-up month. Do one curve per car type for your busiest months first.
A 14-day hire matters more than a 2-day hire. Sum the hire days at each lead-time band.
For each band, what share of the month's final hire days was already booked by then?
The bands where the curve climbs fastest are where most demand arrives. That's where price changes do the most.
Say you run 40 cars, 12 of them compacts. In a 31-day December, that's 372 compact car-days available. Last December you rented 316 of them, which is 85% utilisation.
You export last year's December compact bookings and group the hire days by lead time. These numbers are hypothetical.
| Days before pick-up | Hire days booked in this band | Cumulative hire days | Share of final |
|---|---|---|---|
| 120+ | 41 | 41 | 13% |
| 90 to 119 | 38 | 79 | 25% |
| 60 to 89 | 57 | 136 | 43% |
| 30 to 59 | 76 | 212 | 67% |
| 14 to 29 | 54 | 266 | 84% |
| 7 to 13 | 28 | 294 | 93% |
| 0 to 6 | 22 | 316 | 100% |
Read it from the bottom up. Only 7% of December's compact demand arrived in the final week. Another 9% arrived in the week before that.
The steep part is 30 to 89 days out. That band brought in 133 hire days, 42% of the month. A price that's wrong in that window costs you the most.
So for this operator, December compact prices should be set properly by 90 days out, reviewed every week from 90 down to 30 days, and fine-tuned after that. In the last fortnight, the job is mostly filling the gaps.
The curve also becomes your early warning. Compare this year's bookings on hand with last year's curve at the same lead time.
Say it's 60 days before 1 December. Last year's curve says 43% of final demand should be on the books. You have 168 compact hire days booked for December. Last year's final was 316, so 43% would be 136.
You're 32 hire days ahead of pace, about 24%. Either demand is up or you're too cheap. Check the market before you decide which. If your rates sit well under the market median, you're probably too cheap. See Am I too cheap?
If you were 24% behind pace instead, the questions flip. Are you too dear? Is a competitor discounting? Has a flight route changed?
Copy this into a sheet. One per car type per month.
| Days before month starts | Last year share of final | Last year hire days at this point | This year hire days on hand | Pace vs last year | Action |
|---|---|---|---|---|---|
| 120 | 13% | Set opening rates | |||
| 90 | 25% | Rates should be right by now | |||
| 60 | 43% | Review weekly | |||
| 30 | 67% | Review twice a week | |||
| 14 | 84% | Check market daily | |||
| 7 | 93% | Fill gaps only |
Pace vs last year = this year on hand ÷ last year at this point, minus 1. Plus 10% means you're 10% ahead.
Measuring days to the start of the month is a shortcut that's fine for a weekly check. If you want it tighter, measure each booking's lead time to its own pick-up date, as you did when you built the curve.
Adjust last year's numbers if your fleet size changed. If you had 12 compacts last year and 15 now, scale last year's hire days up by 15 ÷ 12 before you compare.
Inside the last 14 days, your curve is mostly flat but you still have cars to fill. That's where the market check helps.
Each morning, Rate Pulse shows the market median and cheapest rate for every car type and pick-up day over the next 14 days, plus the events and holidays in that window. If you have spare cars for a pick-up day and you're well above the median, that's the day to move. If the market is climbing for a date and you're already full, you've probably priced it too low, and that's a lesson for next year's rates, not this week's.
What it won't tell you is how those market rates got there. Without history, you can't see whether a rate is rising into a date or falling. Keep your own notes each week if you want that, or ask us about tracking it with your bookings.
When you're ready to turn this into a forecast, read how to forecast car hire demand in a spreadsheet and demand forecasting. If you'd rather have it built from your booking system and kept up to date, that's the kind of work we do in revenue management.
No. Rate Pulse shows the next 14 pick-up days, refreshed each morning, and each day's snapshot replaces the last. It has no history or lead-time curve yet. Your own booking data is the better source for this.
One full year is enough to start. Two years lets you see whether a pattern holds. Split it by month and car type before you trust it.
It depends on how much of the final demand is still to come. If your curve shows 15% of bookings arrive in the last week, a change then still moves real money. If it's 3%, it barely matters.
Forecasting, rate management and booking-system integration, scoped to how you run.