Price Elasticity And How It Can Influence Room Rates

Today’s era of infinite data empowers revenue managers with ever-deeper insights into market dynamics. Monitoring competition and adjusting rates in near real-time has become a bare-minimum activity. Dynamic pricing and data-based personalisation are now tools of the trade, leading to stronger performance for hotels that use data to track rates and react competitively.

NB: This is an article from OTA Insight

Yet, within this stream of bits and bytes of supply and demand, we can forget that human psychology underpins each and every booking. And when it comes to pricing, not every consumer sees the lower price as the better deal.

Enter the concept of price elasticity.

Simple in theory but complex in practice, price elasticity is the notion that consumers react to price in an individualised manner. Rather than only external demand factors such as seasonality and event, price elasticity puts consumer behaviour at the centre of pricing decisions. In other words, consumer behaviour is not always rational; a lower room rate doesn’t always increase bookings.

While we’re not going to dive (too) deep into the economic theory, here’s a primer on price elasticity and how it should influence your hotel’s room rates.

Individual versus market demand

The most relevant part of price elasticity for hotels is the difference between individual and market demand. In the broader sense, a hotel’s market might see a correlation where lower prices increase demand.

Put differently, higher room rates reduce demand.

When hotels increase rates in anticipation of higher demand, some customers are priced out. The overall revenue of the hotel is improved by better matching rates to demand.

However, at the individual level, there can sometimes be an opposite effect, whereby a lower room rate actually results in less demand, or a higher rate creates greater demand. In these instances, the inverse correlation is because travellers react to price in different ways.

For example, travellers at the lower end are more price-sensitive than those at the higher end. Dropping the price of the low- to mid-market hotel will generally result in increased demand, while lowering the rate at an upscale hotel doesn’t always have the same effect.

Since a lower price may signal lower quality, hotels must be especially careful to understand the correlation between price and demand at the property, market and category level.

Short- versus long-term

In an academic paper exploring the effects of elasticity on hotel demand curves, researchers found a difference in elasticity between a short booking window and one further out.

“In the short run, buyers have little time to find alternative accommodations or change their destination and therefore are not highly price-sensitive. Conversely in the long run, assuming a price change is permanent, buyers have time to react to new pricing.”

In other words, changes to rates for close-in booking windows are more likely to impact demand. Therefore rate adjustments should be made further in advance if a revenue manager wants to lessen effect on demand.

Category versus property

Price elasticity matters most at the category level. That’s because potential guests are usually comparing hotels within the same category. At the individual property level, revenue managers have more control, as price drops can attract demand from competing hotels in their market.

As the authors above explain (emphasis ours):

“At a property level, a hotel that significantly lowers its price could potentially take demand away from competing hotels and capture more demand than could be captured by lowering price at a city-wide or chain-scale level. Hence, [our analysis is] useful for interpreting differences in demand responsiveness to price changes among types of hotels. For example, we estimate the price elasticity of luxury hotels to be four times the price elasticity of economy hotels.”

Revenue managers should also know that price elasticity at the national level is less accurate. That’s because demand doesn’t budge much if everyone in a domestic market raises their prices. As the group of hotels analysed becomes more narrowly defined – whether by category or market – there’s more price elasticity.

How to calculate price elasticity

Price elasticity is the positive or negative correlation between how a change in price affects the demand. The higher the number, the more a price change reduces demand. The lower the number, the more a price change increases demand.

Generally, calculate price elasticity by dividing the change in demand over the change in price. This formula empowers revenue managers to understand how a particular change in price affects demand.

Whenever prices change in your revenue management software, the effect on demand can be calculated. The most active revenue managers will create experiments to gauge the correlation between price and demand at the property, market, and category level.

Such analysis is possible today thanks to the sheer amount of accessible demand data. As Rhett Hirko, at the time the Director of Revenue Analytics at Hyatt, presciently observed in 2012, “price elasticity is an important tool but should not be used in isolation; an understanding of a hotel’s market is critical to understanding the total impact of price elasticity.”

In other words, the most effective revenue strategy monitors not only how competitors react to pricing, but also how consumers react to that pricing.

Predictive demand intelligence tools are useful tools to see how pricing decisions will affect demand at the behavioural level. By offering a clear view into both historical and forecasted demand, revenue managers have a more granular understanding of how a property’s demographics respond to variations in rates.

Once price elasticity is understood, the fundamental tenets of revenue management still apply:

  • Know your customer;
  • Define your comp set carefully and monitor your competitors’ prices; and
  • Wield rate discounts carefully when reacting to market dynamics.

But with consumer psychology, it’s not always the low price that wins.

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