It Is Time to Rethink Customer Loyalty in Travel
Customer loyalty isn’t what it used to be. In today’s highly competitive digital travel market, not only are consumers doing more complex research, but their decisions are based on individual need, not familiarity with the brand or the product they usually go for, making winning their loyalty tough. With artificial intelligence (AI), however, this task just got easier.
Fragmentation and Finding the Perfect Fit
It is widely proven that the chances of selling to an existing customer are higher than selling to a new one – as much as 60 to 70 percent compared to 5 to 20 percent. Not only do they know your brand but, if they have had a good experience with you before, there is also trust.
However, a customer can be exposed to hundreds of touch points on a single purchase journey, viewing multiple websites and ads before committing. So, securing that next booking is not guaranteed. Ultimately, if another brand sparks their interest, they are off.
Loyalty cards are no longer enough. Customers today are looking for that perfect travel product rather than familiarity or points, plus, checking out ratings and reviews for assurance. Because of this, loyalty must now be won by delivering exceptional experiences, meaning giving consumers exactly what they want, when and where they want it.
Cultivating Loyalty With Your Best Customers
Understanding what customers want in order to get them to book or re-engage them has typically been done by analyzing internal data. For example, if Sally previously booked a short break in Thailand through your website, you could reach out to her with fresh offers in similar destinations.
However, this limited approach means it could be a hit-and-miss. Sally could have also been viewing ski boots outside of your channel, which indicates that she could be interested in a trip to a ski resort.
By combining such third-party data with your own, AI can help you discover your customers’ other interests, or what else they have searched for. You can then reach them with relevant campaigns or products before they book elsewhere.
In addition, AI also allows you to apply predict conversion model to identify high-value customers based on signals derived from their past behavior, such as number of bookings and average spend. It can then rank them according to their conversion potential so you can focus your efforts accordingly.
Effectively Segment for More Relevant Retargeting
Once you have identified your highest-value customers, AI can drill down even deeper for more effective segmentation. How? By crunching third-party data and identifying common interests.
For example, AI analyzes your customers’ online behavior to identify websites that Sally has visited, brands she has shown an interest in and products she has purchased previously, both travel and non-travel related. It can then look for patterns in this data to identify keywords.
Once these keywords are identified, this information can be used to segment customers with common interests into groups. You can then target each group or segment more precisely with relevant and highly-personalized travel offers and campaigns.
However, no matter how in tune your remarketing is, if your identified customer segments don’t see it, it won’t be effective. To overcome this, AI can also analyze online user data to help you discover customer behavior patterns across different devices.
For example, it might identify that Sally likes to browse on her phone in the morning but to complete bookings on a laptop in the evening. Using this information, you can then target her with the right travel offer or campaign at the right time on the right device.
It is clear that building customer loyalty has become increasingly challenging. People are fickle and journeys to purchase are fragmented. However, by using AI to better understand and segment your existing customers and retarget them with personalized offers and campaigns, you can keep them coming back again and again.