Getting warm: Hyatt on price elasticity, profiling and purchase history
Revenue management specialists have been working on methods to estimate price elasticity and optimise rates as part of pricing strategies. The objective is to make tactical revenue management decisions easier - not only from the aspect of inventory management, but also in optimising prices.
Overall, there is a slow realisation that knee-jerk reactions in setting prices would not be sustainable in the long-run. Some smarter revenue managers work through marketing and channel mix strategies, to optimise revenue performance.
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, says Rhett Hirko, Director of Revenue Analytics, International, Hyatt Hotels & Resorts.
Hyatt recently included price elasticity in its annual workshop to get revenue managers to use this measurement in their overall pricing posture. “As far as ‘specialists’ working on this, I have yet to see price elasticity truly integrated in overall demand optimisation but if someone is able to get this done accurately it could be powerful,” says Hirko, who has worked for Hyatt for over 20 years.
In the last nine years, Hirko’s has been in Hyatt’s international division. He designed the CRS-RM interface and the RM training programme and directs the RM process for all international hotels. Hirko further specialises in pricing and distribution strategies for the Park Hyatt brand in North America and all Hyatt hotels in Mexico and South America. He is well equipped to share his insights about price optimisation with EyeforTravel’s Ritesh Gupta.
EFT: Can you explain the meaning of predictive demand intelligence?
RH: Simply put, this uses a variety of data and analytics to understand customer behaviour to generate a forecast.
EFT: What is the current maturity level of predictive demand intelligence?
RH: This exists in the major brands at a rate market level and geographic origin. However, this is not customised to the specific customer. Defining some of the data is very difficult, but once a clear definition is accepted by an organisation, the data can be cleaned and maintained and more detailed predictive intelligence at the customer level can be used. I still see this in its infancy, perhaps late infancy, but it is hardly mature.
EFT: Hotel companies have been trying to develop the ability to set prices dynamically based on publicly available competitive rates and levels of demand at each rate level. What sort of progress in this respect?
RH: We have done significant research on this; an internal study showed that over 80% of the global chains use dynamic and length of stay pricing.
I think this is relatively mature at this point for non-qualified rates, but dynamic pricing for contracted and negotiated pricing has a way to go. We can do it, but the companies aren’t ready for it, and it can be challenging to convince sales to accept this pricing.
EFT: How do you assess the usage of price optimisation tools?
RH: This depends on staffing; price optimisation tools can be very complicated to use at the hotel level so they are likely to be adopted more at a corporate level, or outsourced, where there are individuals with high mathematical skills able to use and discern results. I think development of price optimisation tools that are easy to use would be quickly adopted by hotels, but I haven’t seen them yet.
EFT: How close are hotels to targeting consumers based on their profile and purchase history?
RH: Again a lot of this is based on the tools and predictive demand intelligence. I have yet to see any hotel company target a consumer based on that customer’s purchase history and demographics (CRM) – I suppose casinos do some of this with their frequent guests, but we aren’t there – yet. We are definitely working on it.
EFT: Can you provide an insight into initiatives being taken by the industry to maximise profits by accurately forecasting demand by segment?
RH: Disaggregation is the key, the challenge is the sheer quantity of data it requires. I think we’ll see in the next few years some new models and technology coming out that tackles this. Internally, at Hyatt we have given forecast accuracy tools to our hotels to monitor forecast at any level they want but emphasising market segments. Based on correctly monitoring this, using simple mathematical tools, a better forecast should emerge. We shall see.
EFT: What is the impact of mobile distribution on traditional demand forecasting and pricing?
RH: I don’t see this as having any impact. At Hyatt we want to sell wherever a customer shops, on whatever site. The cost of connecting to that site is the cost of doing business. Of course we have to weigh the value of developing and working with any channel as a positive return on investment. At this time, I don’t see that we would change or modify the way we forecast and price based on whether any channel is mobile or not.