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Thursday, August 11, 2011

How to to build and maintain traveler loyalty with Automated Digital Personalization

This article first appeared on Travel Mole on July 29, 2011.

When it comes to targeting consumers, the travel industry’s got it made. Think about it: to secure any type of travel—hotel, car, flight, tour, etc—customers have to release individual preferences and other information about themselves, which can later be used to personalize marketing efforts, and tailor the travel experience. Now, with the online world playing a major (and often, the only) role in the booking and research phases of trip planning, the opportunity to capture even more data about users and make their brand experience personalized across all channels is greater than ever.

Each visitor that comes to your website is equipped with a wealth of data that comprises their unique traveler “profiles”—powerful information such as previous trips booked, travel –related items they’ve researched, frequency and recency of travel, and ads or offers they’ve responded to (with a click or purchase). Needless to say, this information can help you better target content and offers for each individual, making their visit much more relevant, while helping you increase engagement, bookings and repeat customers. But how?'

One method is to define “rules” (or a set of conditions that must be met) that will dictate which visitor segments will get which experiences.  When defining rules, it’s important that you take into account the various stages travelers go through when planning for their trips; they may visit a site several times before actually booking a reservation. Use this to your advantage. This type of personalization technique allows you to adapt and match each forthcoming experience to the data collected during their previous visits. An example of how a rule can be used to define the experience for a repeat visitor is to re-target them based upon the last destination they searched. This may result in an offer for a vacation package that includes tickets to a local attraction, which could result in enticing them to book, or even extend their trip.

While targeting with rules can be effective, it can be nearly impossible to manually define rules for monstrous websites with copious amounts of daily traffic. So for increased sophistication, another method of behavioral targeting uses mathematical models to predict the most compelling content and offers based upon all that is known about a visitor. This type of model learns and adjusts over time to dynamically optimize visitor experiences with content that yields the highest conversion rate. This approach also enables a broader range of content—such as destinations or travel packages—to be presented to the right person based on their unique predictive attributes.

Examples of predictive attributes used to personalize the online experience:
• Planning days in advance of the trip
• Length of stay
• Number of people (adults and children)
• Last departure point (searched or booked)
• Last destination (searched or booked)

European airline carrier bmibaby, for example, uses real-time personalization to target visitors with different “Featured Destinations” on their home page. The destination each visitor sees is based on the visitor’s geographical region, past trips and searches. By personalizing in this way, bmibaby has seen a 34% increase in clicks on the Featured Destination features, and a 4% uplift in bookings.

Independent of which of these methods you choose, digital personalization will empower you to start targeting visitors at the right time, with the right content and offers based on their individual needs, wants and behaviors. Since visitor behavior can change with each visit to your website, targeting rules alone can grow to unmanageable numbers. When this happens, consider moving to automated behavioral targeting, which will help you properly personalize the real-time experience for each traveler, without the nightmare of creating and maintaining complex rules.

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