The US online travel market is maturing. According to eMarketer, growth in US digital travel sales is slowing, down from 15.1% growth in 2011 to 8.0% in 2013, with 4.5% growth predicted for 2017. What does this mean for travel and hospitality companies? The endless stream of brand new consumers booking online is ebbing - it is no longer enough to have a web site with a booking engine, the online experience must be such that it attracts customers and keeps them coming back. Consumers have multiple options for making online and mobile reservations - to prevent your potential customers from booking with the competition, it is important to understand the intent of your potential customers, and provide relevant, timely and insightful interactions that increase the chance of conversion from browsing to booking.
To do so, hospitality and travel organizations need an analytic-based approach that focuses on using the masses of digital (web and mobile) data that is available to help identify what customers are searching for online and how content and search results can be tailored to deliver what the customer wants. Luckily, improvements in data storage and processing power mean that analyzing web and mobile behavior using predictive analytics has become much more feasible.
Digital data is quite simply a big data challenge. In the past web analytics have focused on aggregating data as a first step, then providing summary reporting. However, data storage has become relatively inexpensive and processing power has increased exponentially, enabling companies to access, process, and analyze their data in its entirety without sacrificing any speed or accuracy. Using predictive analytics, companies can use raw data collected from websites, mobile apps, and social media data and turn that into powerful insights on their customers.
Digital behavioral data and predictive analytics can supplement three areas within marketing: outbound, inbound and integrated marketing efforts. Digital behavioral data, business rules, and predictive analytics can help outbound marketing efforts by identifying which marketing offer to use in your email, display, or re-marketing campaign. Digital behavioral data, business rules, and real-time predictive analytics can deliver a personalized visitor experience when an inbound prospect returns to your website for the nth time this week. And finally, digital behavioral data, business rules, and real-time predictive analytics can be used in an integrated marketing approach that expands to every customer touch-point, including prescribing how a call-center or front desk team member can up-sell a repeat customer with the most relevant offer when that customer calls to make their next reservation. Personalizing the web experience and expanding it to the service operations experience is a comprehensive way to keep customers coming back to your booking site.
Displaying different options to different set of customers is fundamental to online retailing. The methods used to determine what product options to display to which customers and when are becoming increasingly sophisticated. Hospitality and travel companies have a multitude of different products that potentially can be displayed to a customer at the moment that customer performs a search of their website. Using personalization technology, hospitality and travel companies can present, customize or suggest the exact content that is relevant to an individual customer, based on an understanding of that customer’s preferences and behaviors.
Over the next few posts, we will be exploring the area of digital intelligence and personalization for hospitality and travel companies. I hope that you will join us for more on this subject!