Hotel operators conceptually know the value of predictive analytics, or are at least familiar with the more general availability of “Big Data.” But many struggle to convert their adoption of a data-driven strategy into actionable insights and concrete steps for increasing bookings and revenue.
The more customer and competitor information can be put to use, the better-positioned a hotelier is to price rooms to fit real-time demand, encourage loyal repeat customers, and practice true one-to-one marketing and pricing with guests, according to revenue management experts leading EyeforTravel’s most recent webinar, “Predictive Analytics for the Hotel Industry.”
Pavan Kapur, Senior VP of Strategy and Revenue Optimization for the Atlantis Paradise resort, called the hospitality industry “fertile ground” for predictive analytics. All aspects of the business, from marketing to operations to revenue management, can benefit from using Big Data, he said.
He reiterated that customer data — down to crucial details, like which guests always order steak or which always play golf — is what enables hotels to craft custom offers that incentivize people to join loyalty programs and book rooms directly, rather than through online travel agencies.
“Knowing guests’ profiles and preferences allows hotel properties to know more about their guests than any OTA ever will,” Kapur said. “If you have [consumers] log in to your mobile app or to your website [as a loyalty member customer], you can give targeted offers that OTAs just can’t.”
[bctt tweet="Being able to offer custom promotions is very valuable."]
He added that predictive analytics comes into play across several verticals at Atlantis, including the hotel, casino, a large food and beverage operation, an entertainment venue and even a waterpark. Kapur sees great potential for data to improve all functions of a hotel, including in the following areas:
- Pricing: Better data has resulted in better forecasting, which leads to flexible, optimized pricing. Predictive analytics incorporates more than just historical room rates and competitors’ prices; it adds forward-looking data such as web shopping data, airline and weather information, and online reviews and social feedback. With that information in hand, a hotel can practice Open Pricing, where all room rates are calculated independently for each booking date, according to demand by customer segment, room type and distribution channel.
- Digital investments: Tracking the customer’s path to purchase helps hotels optimize their own booking channels. Analyzing how many guests book directly or through an OTA, as well as how many potential guests stopped shopping without booking, helps hoteliers understand how to streamline the booking process and which upgrades must happen.
- Labor optimization: This produces a huge bottom-line impact, as predictive models can determine each booking day’s most efficient number of housekeeping and front-desk staff members, as well as the right number of servers needed in the restaurant or lifeguards needed at the pool.
- Smart alerts: Revenue management systems built on predictive analytics can detect significant shifts in demand or booking pace, and send email or text alerts prompting decision makers to act immediately.
- Customized offers: Hotels can turn frequent customers into loyal guests if they know what those consumers want and need from their hotel stay. The brands must track frequency and spending and, most importantly, encourage guests to enroll in the property’s loyalty program. Once that information rolls in, Kapur said, it gets easier to develop compelling offers and amenities to keep customers coming back — and booking directly.
“Now we have daily collection of all data down to the SKU level, so we know if a customer likes white wine in the restaurant and not red wine,” he said. “It’s the most granular level of information you can have. Being able to offer custom promotions is very valuable.”
To learn more, view the webinar here.