PriceLabs analyses thousands of data points to set the optimal rate for every night. Connected to LetPilot, it updates your rates automatically.
If you set a nightly rate in January and leave it unchanged for the rest of the year, you are almost certainly losing revenue in some periods and losing bookings in others.
The demand for your holiday let is not constant. It peaks during school holidays, local events, bank holiday weekends, and the summer season. It troughs in January, during wet spells, and in the weeks between the summer rush and autumn half term. A static rate means you are underpriced in peak periods — rooms filling too cheaply when demand could command more — and overpriced in slow periods, with empty calendars because the rate is not competitive.
Dynamic pricing — adjusting rates automatically based on demand signals — solves this. And PriceLabs is the most widely used dynamic pricing tool in the short-term rental market.
PriceLabs analyses a large dataset of local booking activity, demand signals, competitor pricing, local events, and historical patterns to recommend an optimal nightly rate for every day in your calendar. It adjusts these recommendations continuously as conditions change.
Key features include a market dashboard showing how competitor properties in your area are priced, a demand calendar visualising demand levels by date, customisable minimum and maximum rate rules, automatic detection of local events that drive demand (music festivals, sports events, bank holidays), last-minute pricing that discounts dates within 7 to 14 days with no booking, and far-future premiums that increase rates for dates more than six months out.
Once connected, PriceLabs pushes its recommended rates directly to LetPilot, which then reflects those rates in your property calendar and booking channels.
Here is the flow: PriceLabs calculates recommended nightly rates based on your settings. PriceLabs pushes these rates to LetPilot via API at a configurable frequency, typically once or twice daily. LetPilot updates the nightly rates in your property calendar. When guests search for availability, they see the dynamically priced rates. Booking-specific adjustments such as discount codes, loyalty points, and add-ons are applied on top of the PriceLabs base rate.
You retain full control throughout. PriceLabs respects your minimum and maximum rate floors and ceilings, and you can override any specific date manually without disrupting the ongoing dynamic pricing.
In LetPilot integrations hub, select PriceLabs and follow the connection flow. You will need your PriceLabs API key, which is available in your PriceLabs account settings.
Each property in LetPilot needs to be mapped to the corresponding listing in PriceLabs. For multi-unit properties, map each unit individually.
Before the integration goes live, spend time in PriceLabs configuring your pricing strategy. Set your base price, which is the starting point PriceLabs adjusts up and down from. Set a minimum price, which is the floor below which you will not go regardless of demand. Set a maximum price to prevent unrealistic spikes. Configure minimum stay rules, which are important for profitability since a single-night booking at peak season may be less profitable than blocking for a two-night minimum. Configure health score targets if you want PriceLabs to target a specific occupancy rate.
For the first few weeks after going live, review the PriceLabs recommendations daily. Check that rates feel appropriate for your market and property quality. Adjust your base price and min/max settings if recommendations are consistently too high or too low.
PriceLabs works alongside LetPilot own pricing rule features. Use them in combination:
PriceLabs handles the dynamic market-based rate adjustments — responding to local demand, events, and competitor pricing in your area.
LetPilot pricing rules handle your business rules: weekend premiums, minimum stay periods, last-minute gap fill discounts, and seasonal overrides.
For example, you might set a PriceLabs minimum rate of £120 per night but also have a LetPilot rule that applies an additional 20% premium on bank holiday weekends. These stack correctly when both systems are configured appropriately.
PriceLabs takes into account a range of signals:
Local demand data from booking patterns in your area, updated continuously. Competitor pricing for comparable properties on the same dates. Seasonal patterns specific to your location and property type. Local events detected automatically — a festival, a sporting event, or a major conference that drives accommodation demand. Lead time and booking pace — whether properties in your area are filling fast or slowly for a given period. Day-of-week variation — Fridays and Saturdays typically command higher rates than midweek nights in most markets.
The quality of your listing data (your property type, capacity, amenities, location) determines how accurately PriceLabs compares you to relevant competitors. Complete your LetPilot property profile thoroughly for best results.
Hosts who switch from static to dynamic pricing via PriceLabs typically see revenue improvements of 10 to 30 percent in the first year, primarily from higher rates during peak demand periods, better off-peak occupancy through last-minute pricing, and optimised minimum stays that reduce unprofitable short bookings.
The exact improvement varies significantly by location, property type, and how competitive the local market already is. Properties in areas with high competition and well-calibrated competitor pricing see the most benefit from the market intelligence PriceLabs provides.
Properties in very remote or niche markets with few comparable properties may see less benefit from the market analysis component, but still benefit from the last-minute and seasonality adjustments.
PriceLabs optimises for revenue given the demand that exists. It cannot create demand where there is none. It relies on market data — in very niche or remote markets with few comparable properties, its recommendations may be less accurate than in well-populated markets. It optimises for occupancy and rate metrics, not for operational costs such as cleaning fees, which affect whether a short stay is actually profitable. Use PriceLabs as a strong starting point and layer your own knowledge of your property costs and guest price sensitivity on top.