Is it already time to abandon the hotel loyalty pricing strategies that were, until recently, so highly touted for their potential to stave off OTAs? Definitely not, but they should be improved through better use of Big Data.
It’s good that hotel brands like Marriott and Hilton are advertising the value of booking direct and that those same companies are leading the charge to take market share back from OTAs.
But if hoteliers have an inflexible approach and don’t gather the right kind of data to refine their loyalty pricing, they’ll sabotage themselves — and their owners, who truly feel the pain of lost Average Daily Rates and profits.
It was a theme I heard several times at the Revenue Strategy Summit, particularly from a couple owners on the first panel of the morning: What good is loyalty pricing if the discounts are eroding profits? What good is spending all this money to peel away market share from OTAs if they’re accounting for only a fraction of some property’s bookings?
[bctt tweet="@ptbosworth: #Hotel loyalty won’t work without data-driven Open Pricing"]
Hotel loyalty strategies will not work if they’re not married to the comprehensive, data-driven philosophy of Open Pricing. Without that breakthrough practice, a hotel’s loyalty program will have too many inactive members, too few segments and loyalty tiers, and only discounts off BAR that are too static and too generous.
Big Data Enables Dynamic Hotel Loyalty
In order to achieve truly dynamic loyalty pricing, hotels first need to execute Open Pricing, in which rates are set not in relation to BAR but according to demand for any booking date, customer segment or room type. If the property’s prices can be flexed whenever demand conditions change, they also can be flexed according to the spending habits of the guest booking with the hotel.
Leveraging more data also will help your hotel divide its customer database into more segments, as many as you need to make sure each individual guest is treated as such at the time of booking. This helps your revenue managers identify which guests deserve a more valuable discount when they book.
Big Data also helps hotels refine their loyalty strategies. You can’t execute dynamic loyalty pricing without lost-business data like web shopping regrets and denials. These new forms of information let you experiment with loyalty rates and see what amount a discount needs to be to meaningfully increase conversions on your direct channels.
Is that offer you’re quoting to loyalty members creating business in excess of what you usually get with your publicly listed rate? If you’re offering an aggressive discount, say 15% off, and your conversions from look to book only increase a few percentage points, it’s not worth it. Many of those guests would book with your hotel no matter what, so the loyalty discount could be flexed down to 5% or 1% off.
But perhaps it’s different for another customer segment, with more price-sensitive guests and more elastic demand. If a 5% discount is causing a 10% shift in conversions within that segment and luring customers from an OTA to your direct channel, then a small amount makes a huge difference.
If you practice hotel loyalty the right way — starting from a base of Open Pricing and flexing discounts, instead of offering some set amount off BAR — you end up optimizing your rates for the most Net RevPAR and profit. Lost-business data helps you measure whether you’re right or not.
How Else Could Hotels Improve Their Loyalty Strategy?
A dynamic discount that can change to match what the hotel needs on any given booking date goes a long way toward making loyalty programs work for brands, owners and their guests. But consider a few other pricing moves beyond discounting you could make as well.
For one thing, on a compressed booking date, you could keep the rates static for loyalty club members and start yielding up all other publicly available rates. That’s the flipside to smart discounting. You have the opportunity to yield profitability with your loyal, core customers, and then you can drive rate on other channels.
If your lost-business data confirms that a customer segment has fairly inelastic demand, meaning that deeper discounts won’t move the needle, consider other perks that could be made available only to those club members.
I’m not talking just about free Wi-Fi, parking or breakfast. Depending on who your core guests are, those amenities can be more of an expectation than a perk.
Consider what you can do with your room inventory to make your loyal guests feel appreciated. Maybe they want higher floors, or quiet floors, or corner rooms. If the data behind your segmentation and forecasting is good, you’ll have a sense of how many loyalty members might book very late in the window, and how many of those premium rooms you will want to have held for them.
There are many ways to execute a hotel loyalty program. Leveraging data is the reliable way to make sure your property is getting it right.