How Airline Marketers Can Be More Relevant with Hyper-Personalization

Hyper-personalization differentiates itself from personalization by going beyond simple segmentation – leveraging advanced predictive AI and real-time data to deliver highly individualized and dynamic experiences for each and every single customer. 

Let’s put ourselves in a traveler’s shoes to understand it better. 

You are a frequent business traveler between Amsterdam and London who needs to get in and out fast. You bring only an under-the-seat laptop bag and enjoy a preselected sandwich during the flight. 

Your preferred airline understands your preferences and offers you a bundle price that includes fast check-in, a business-class seat, and your favorite carpaccio sandwich. You’re no longer in the same marketing flow as a person who flies long distances – and offers you discounts on checked bags, in-flight entertainment options, holiday insurance packages or travel activities. 

Feels like a breeze, doesn't it?

Marketers fall short in satisfying their customers with a one-size-fits-all approach. With the diversity of travelers' preferences, destinations, and experiences, launching hyper-personalized campaigns isn’t a luxury – it is a key tactic for success, notes Skyscanner’s Future of Travel 2024 report. 

So why are so many airline brands missing the mark?

Well, hyper-personalization is difficult, and the more customers and prospects you have the harder it gets. That’s why marketers who have an ambition to reach hyper-personalization need to utilize advanced technologies such as predictive artificial intelligence and real-time customer data analytics.

When travel marketers use real-time data, such as anonymous clickstream data, to categorize their customers and orchestrate their journeys, they can then better target their advertising, personalize the web experience, and match every single traveler’s preferences. 

This all sounds great, but how do data collection, orchestration, and predictive AI work in practice? 
Let’s find out. 

Unifying Your Customer Data 

While booking a flight, travelers will navigate various price-comparison sites, travel agencies, devices, emails… This makes airline marketers’ jobs difficult. There is no way to push personalized ads when you don’t know who the buyer is, what their booking patterns and preferences are, and where they are in their purchasing journey. 

Only with a customer data platform that collects and unifies customer data from across the business, will you be fully empowered to craft hyper-personalized campaigns. 

For hyper-personalized campaigns to work, a CDP will bring together: 

• Demographic Information – Age, gender, location, and income level.
• Behavioral Data – Website visits, clicks, searches, purchases, and interactions with email campaigns or social media posts.
• Transaction History – Past purchases, bookings, and transactions.
• Preferences and Interests – Likes, dislikes, hobbies, and preferences related to travel experiences.
• Device and Channel Usage – Preferences to book travel via desktop, mobile, or tablet devices, as well as their preferred communication channels such as email, social media, or messaging apps.
• Engagement Metrics – Open rates, click-through rates, time spent on website pages, and social media engagement.
• Customer Feedback and Surveys – Direct insights into consumers' experiences, preferences, and satisfaction levels, and feedback collected through post-purchase surveys and customer reviews. 

When all this data comes together, you become equipped with highly detailed, insightful customer profiles to orchestrate omni-channel campaigns to target your audience in a meaningful way; which contributes to conversion rates as well as brand sentiment and loyalty. 

 
Staying Relevant 

Hyper-personalization needs to be crafted in a way to cover each step of the journey – from the moment of booking a flight, selecting ancillary services, purchasing in-destination experiences, checking in, and more. This way, you will know what each traveler wants, erase the kind of advertising that they don’t want to see, and place the ones that make sense. 

That needs to happen on a constant basis. 

Predictive analytics is then essential to interrogate all the data in the CDP to anticipate customer needs based on past booking patterns and identify individuals who are most likely to convert for a specific offer or destination. 

For example, if a customer has previously booked a beach vacation during the winter months, predictive analytics can anticipate their interest in similar destinations during the same time period in the future.

However, the AI predictions may also determine that a more optimal time to capture a re-booking might be a two-week period directly after they’ve arrived home. When trained on the full breadth of your data, these AI models can help you target these customers with relevant offers and promotions in a proactive manner.

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For travel marketers looking to stand out in a crowded marketplace and convert more holidaymakers, hyper-personalization is the key to success. Get more inspiration from our e-book on boosting your travel marketing strategy with 1-1 personalization.