Data analytics can help hotel owners and operators make informed decisions about providing free amenities in their properties, writes Surendra Yadav
Free amenities play an important role in the decision to book a hotel. Certain features such as Wi-Fi, pools, fitness centers, and parking, have become as important as a comfortable bed and a clean room. Even affluent travellers mention free amenities as a factor that influences their choice of hotel.
Various hotels’ decisions to provide certain amenities as perks for their loyalty programmes bears out how important these features have become. Different brands and programmes offer guests many complimentary services that range from bottled water to in-room Wi-Fi. For example, Wyndham, Hyatt, and Four Seasons provide free Wi-Fi to all; Hilton, Marriott, IHG and Starwood provide free Wi-Fi only to their loyalty and premium guests.
The decision to add free amenities can be quite contentious in the hotel industry. Since most hotels are owned by franchisees, free amenities can be seen as additional operating costs from their perspective. A conflict arises: the hotel brand would like to offer more included services to attract customers; the franchisees would like to keep their costs down and reduce operational complexity. And for them, that means fewer free services.
The ability to measure the financial return of free amenities is very important. Not only can it clarify which features to provide or add, it can also help convince franchisees of the benefits of providing certain free amenities.
Techniques currently used to measure the financial return of free amenities tend to focus on the effects of adding an amenity to an initial choice. This may distort the full impact of the investment on both current and future revenues. A hotelier should evaluate the profitability of offering a particular free amenity based on its effects on both initial choice and repeat purchases.
Professors Rebecca Hamilton, Ronald Rust, Michel Wedel and Chekitan Dev have published an interesting paper on this issue (Return on Service Amenities, Nov. 15, 2015). The paper presents a robust and comprehensive methodology for the hotel industry to measure the financial impact of providing specific amenities. What did the paper’s authors find?
The initial and repeat purchase factors, combined with historical customer data and cost structures, can be used by hotel owners to evaluate the impact that adding or dropping an amenity has on expected revenue. They can choose the best investment option based on the amenities’ ROIs.
Ensuring a positive impact
To make sure the amenity any hotelier chooses to offer will perform, there has to be some serious analysis first. When you’re calculating the financial return from a free service, you must consider the amenity’s impact on both new and repeat guests. They should be analysed in pre-stay, during stay, and post-stay timeframes to quantify the effect of expected and actual use of an amenity on repeat frequency and revenue per visit. A nonlinear factor model will then be developed with this data. This provides an expansion factor, which is in turn used to predict repeat frequency and revenue.
The results deduced by the above methods, coupled with customers’ historical average spend and the proportion of new customers, can be used to compute the expected sales from a free service. Related maintenance expenses can also be estimated; they normally directly corelate to per-usage costs and the number of customers using the amenity. However, a one-size-fits-all free amenity across hotel brands can be hard to find. Once again, though, data analysis can help brand managers or individual operators make an informed decision, initial and repeat purchase factors need to be combined with historical customer data and cost structures.
Successfully balancing attracting new guests and retaining current customers takes hard work, but with the right mix of options, it can be done. By using data analytics and techniques like conjoint analysis and nonlinear factor modeling, insights can be revealed that make the decision process easier.
(Surendra Yadav is Manager at Absolutdata)