So you need to fly to New York next week for a friend’s wedding. You will be busy the day of the wedding but you decide to stay on in a budget hotel and do a lot of sight-seeing because you’ve never been to the big apple.
Wouldn’t it be great if your online travel booking website not only recommended flights at the times that are most convenient for you but also offered you a list of hotels you may like to stay at? What’s more, the booking website could also throw in a free foot massage and an offer for discounted entry to a gig by your favourite band. How do they know you’re going to love the package they put together for you? The answer lies in the beauty of predictive analytics and modeling in the travel marketing space.
The increasing levels of customer data available to booking companies, travel portals, airlines, hotels and more makes it easy for anyone in the travel marketing industry to make complex decisions, offers and promotions with the right data. Travel marketing involves looking not just at current customer data, but creating an overall customer profile and understanding every buyer as an individual.
Understanding the Buyer’s Flow
From when they reach your website to when they complete they booking – a customer passes through various stages of engagement and looks at various combinations of travel and hotel options to suit their needs. Future vacationers and business travelers may both browse your website. These two groups are sure to have two very different patterns of searching and booking.
A vacationer may look for a beautiful hotel, located away from the hustle and bustle of the city – great views and facilities to unwind and relax. A business traveler looks for a hotel that is close to where she or he will be working and attending meetings, needs a functional room and a good breakfast spread, laundry, and wifi services, Understanding what these two very different customers want before they book may seem impossible. Yet with data on logged in customers, frequent flyers, age related demographics and so on – this can be narrowed down to near perfection and implemented in your travel marketing roadmap. You can then reach customers across channels like mobile, sms and push with customized offerings.
Predictive Analytics also plays a big role in building customer loyalty. When it comes to travel marketing, it is crucial to use past data and current browsing patterns to personalize and optimize every customer’s booking experience. Offers, promotions, calls-to-action, room or seat preference, type of traveler etc are all factors that must not just be used, but also personalized to fit the unique taste, preferences, likes, and pet peeves of your customers. Its important that these offers and promotions don’t get invasive or creepy, which is sure to make your potential customers annoyed, and more likely to use a competitor to book their next trip.
Frequent flyers have been around as a segment for ages. We all know how useful travel miles were because we were definitely related to or knew somebody that took advantage of this facility to enjoy free travel to different destinations. Similarly, ‘business’ and ‘leisure’ travellers are standard segments that you can use in your travel marketing strategy.
What’s great is that predictive analytics lets you go beyond these basic categorizations and use customer behaviors and booking patterns to come up with even more customized offerings. When you look at customers who fly into a city, find accommodation near a certain hospital, and spend large chunks of their time there, predictive analytics can help you deduce that they are probably visiting someone they care about who is ailing. Offering these caregiving customers special benefits or discounts for their regular trips makes them grateful and loyal to your brand.
Strategic pricing of flight tickets while they are in demand and scarce or strategically lowering of prices for limited, short periods both encourage customers to book. Predictive analytics gauges demand and determines which of these models to incorporate. This model can be applied across the board in travel marketing, from hotels and BnBs to local festivals and getaways.
One move that wins customer loyalty is the option to let customers ‘save at this price’ Which means customers can come back to your website and book tickets at a price once they save it, even if it has gone up since. Using predictive marketing to understand who is most likely to go for this offer or making it available only to signed up customers is another great way to build exclusivity and loyalty.