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Last Minute and Far Out Pricing: Observations from our Experiments

Last Updated on 1 month by Vinay Sahu
Last minute price
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Are you a vacation rental owner or manager struggling to find the right pricing strategy? Look no further. PriceLabs’ Dynamic Pricing Product can be ideal choice to ensure that you are able to automate your pricing while maintaining control (as much as you need!).

Our Data Science team has been hard at work to build Hyper Local Pulse algorithm. While doing so they have unearthed some fascinating insights that could help you with how you approach pricing, especially when it comes to last minute prices and far out prices.

1. Perceived Value Trumps Low Prices

Picture this: you decide to offer your vacation rental at an unbelievably low price, almost too good to be true. But to your surprise, bookings don’t come pouring in. Why? The answer lies in the concept of “perceived value.” Unlike commodities with standardized quality, vacation homes are booked based on perceived and physical quality. Price serves as a signal of quality. If your price is too low, potential guests may question the quality, and you may not sell every night. It’s all about finding that sweet spot between affordability and quality.

2. We Sell Perishable Inventory

PriceLabs’ analysis of several markets reveals a straightforward pricing strategy: reduce prices as the booking date approaches. The logic is simple; as each day passes without a booking, your chances of getting booked decrease. This insight powers last minute discounts and far out premiums, helping you optimize your revenue.

Last minute price
Price Evolution Based on Lead Time

3. The Airline Way of Last Minute Price Increase

Does it ever make sense to increase prices as a date gets closer, similar to how Airlines do it?

Yes, in exceptional scenarios – when your market’s forecast changes because of a sudden unexpected surge in demand, the forecast is revised upward. This means that even with less time remaining, the probability of booking increases.

Usually, as noted in second point, for short-term rentals, it usually makes sense to reduce prices as a date approaches. Airlines increase prices for a different reason – they are in an oligopolistic market (and when you factor in business travel where loyalty programs factor in a lot, even closer to a monopolistic market). On the other hand, short-term rentals are much closer to perfect competition and thus see a very different lead time dynamic.

4. Tailoring Discounts to Market Dynamics

Urban markets often have shorter booking windows, suggesting that discounts should kick in closer to the booking date and not too early. For instance, in the case of 1BR vacation rentals in Chicago, PriceLabs’ optimization recommends starting last minute discounts at closer to check-in date rather than following a general approach to all markets.

5. Flexibility by Market and Season

Not all markets and seasons are created equal. In traditional vacation destinations where bookings happen far in advance, aggressive far out premiums may not be your friend. Even for last minute discounts – you may want to start those early relative to urban markets!

6. The Seasonal Surprise

Here’s a surprising twist: in highly seasonal markets, the data suggests that both low and high seasons tend to have smaller last minute discounts compared to the shoulder season. In the low season, the algorithm already recommends lower prices. Probability of getting a booking doesn’t change dramatically as we get closer to check-in date. On the other hand, in the high season, most competitors are likely to be booked. Hence, your probability of getting booked doesn’t decrease dramatically with time – thus a case for small last minute discounts.

Let the Algorithm Work for You

In an industry-first, the beauty of HLP algorithm is that it takes these market and season-specific nuances into account. You don’t need to constantly update your last minute discounts or far out premiums; the algorithm does the heavy lifting for you!

Of course, you can always override the algorithm if a different strategy aligns better with your portfolio.

In conclusion, pricing your vacation rental doesn’t have to be a daunting task. With the power of data and insights from PriceLabs’ data science team, you can make informed decisions and optimize your revenue. Remember, it’s not just about low prices; it’s about finding the right balance to signal quality and capture bookings.

Unlock the potential of your vacation rental pricing with PriceLabs’ cutting-edge algorithms.

Dynamic pricing in Airbnb refers to the practice of adjusting rental rates in real time based on various factors such as demand, seasonality, local events, and market conditions. This approach allows hosts to optimize their earnings by automatically increasing or decreasing prices to match supply and demand fluctuations. By utilizing data and algorithms, dynamic pricing aims to find the optimal balance between attracting guests and maximizing revenue, ensuring that prices reflect the current market dynamics.
To implement dynamic pricing for vacation rentals, collect relevant data, identify key factors, set pricing rules, use dynamic pricing software, monitor performance, and adjust as needed to optimize revenue.
The aim of dynamic pricing is to optimize revenue and occupancy rates. It is done by adjusting prices in real time based on factors such as demand, market conditions, competition, and other variables. Dynamic pricing softwares seeks to find the optimal balance between attracting guests and maximizing profitability by dynamically setting prices that reflect current market dynamics. The goal is to capture the highest possible value for each booking while ensuring competitiveness in the market.
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