Accounting for competition in revenue management

In my last post, I explored the importance of factoring price elasticity into a revenue management approach.  This week, we’re going to explore the importance of accounting for competitor pricing.

In today’s market, consumers have an unprecedented ability to shop around, with the internet now comprising approximately 35% of all hotel room bookings (2010 figures*).  The hospitality and travel customer has wide access to pricing information – allowing her to readily evaluate competitive pricing each and every time she begins shopping for a room.  As a result, many hospitality and travel operators take advantage of a wide variety of competitive information sources, including competitive rate and competitive performance benchmarking information.  This competitive information is used to inform both operational pricing and revenue management decisions, and to act as a gauge for overall revenue performance.

Too Much Focus on Competition?

An unfortunate side effect of this sort of focus on the competition is that it can lead to a “following the leader” mentality that really is not consistent with good revenue management practices.  We see many revenue managers whose primary instinct for pricing is driven by the question: “What is my competition’s price?” and not by the question: “How much inventory do I have left to sell, and how much demand exists for that inventory?”  For a telling story on the downfalls of “follow the leader” pricing, I strongly recommend reading this blog story about Amazon’s $23 million book about flies.

As the $23 million fly book story illustrates, it is imperative that we continue to use sound judgment in making pricing decisions, even as we incorporate competitive rates and competitive effects.  In hospitality and travel, it is particularly important to remember that a price change can be perfectly sensible for a competitor – but not be something that you would want to match.  For example, if I have managed to book a large group for my property during an otherwise low season, I may well increase my rates during the period that the group has booked: I have little inventory left, and need to maximize the value from it.  But, in this same scenario, my direct competitors would likely be foolish to match.  So, the right rate for me is the wrong rate for my competitor.

Competitive Information – A Weakness in Traditional Revenue Management

Traditional revenue management science was not designed to deal with competitive rate changes.  As was discussed extensively in my post entitled Revenue Management vs. Price Optimization: Part One, traditional revenue management science made the assumption that prices would remain relatively stable – and this included our fares and rates, as well as our competitors’.  With this assumption, simple time series approaches to demand are indeed sufficient to capture the variability of demand.

Unfortunately, as was discussed last week, the assumption of price stability is no longer valid.  Both our own and our competitors’ pricing is changing on a regular basis – and our customers have full view of our relative price position vs. our competitors.  This fact can lead one to assume (as many revenue managers do) that if a property is “competitive” in the market, then that property will “capture its share.”  The unfortunate corollary that often accompanies this belief is that in the absence of rate matching, a property gets little or no demand at all.

As a result of both this assumption, and the revenue manager’s desire to incorporate a significant driver of profitability (i.e., competitor pricing), revenue management vendors have often taken a short cut in addressing competitive influences into their systems.  Vendors employ heuristics or constraints to force pricing into a competitive range, in post-optimization processing.  Unfortunately, this approach doesn’t address the type of example that I’ve noted above – the circumstance where the right price for a competitor is wrong for you.

Using Competitive Information the Right Way

To properly deal with competitive influences, we need to recognize that consumer demand is complex, and driven by a number of factors in addition to price.  For hotels, this includes location, on-site amenities, room configurations, distribution channels, familiarity with the market, customer loyalty – and much more.  As our team developed SAS Revenue Management and Price Optimization Analytics, it was a critical goal for us to capture competitive impacts in this way – as part of an overall model for demand forecasting, rather than as a post-optimization heuristic.

In effect, when competitive data is available, we are modeling demand not simply as a function of our own price (as discussed last week), but as a function of how our price relates to the market.  As a result of modeling demand in this manner, we are able to recognize the impact on profitability of being below, at, or above market pricing – and to optimize rates and availability accordingly.  Incorporating elasticity and competitive effects in this way has other benefits, as well:

  • Demand forecasts are improved, because they are now capturing these factors that have a strong influence on demand (our own and our competitors’ pricing)
  • Demand forecasts react to price changes the way that revenue managers (and GMs) expect – higher prices lead to lower demand
  • Demand forecasts react to competitive price changes the way that revenue managers expect – higher competitive prices contribute to higher demand for our property
  • Revenue Managers have greater confidence in the forecasts, because they incorporate the factors that they know are important to the customer

In summary, we believe that the competitive price modeling within our recently introduced SAS Revenue Management and Price Optimization Analytics offers revenue managers an analytically-based approach to managing competitive price effects that has been neglected by other systems to date.

 

References:

* “Distribution Channel Analysis: a Guide for Hotels” Cindy Estis Green & Mark Lommano, An AH&LA and STR Special Report, published by the HSMAI Foundation

tags: Hospitality Analytics, Revenue Management and Price Optimization

Post a Comment

Your email is never published nor shared. Required fields are marked *

*
*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <p> <pre lang="" line="" escaped=""> <q cite=""> <strike> <strong>