Broad Targeting To Precision Marketing: How AI And ML Are Transforming Travel Marketing

Kurt Weinsheimer, Chief Product Officer at Sojern.

For years, marketers have collected data about traveler behavior to better understand what they want and tailor experiences accordingly. However, as the path to purchase became more complex, travel marketers had a problem: what to do with all that data. On average, American travelers view 185 pages of travel content during the 45-day window before booking. With so many touchpoints, it quickly became impossible for any human to sift through that much data in time to act on it, so marketers defaulted to broader campaigns.

But AI and ML are fast changing how we market, making one-to-one marketing possible. Recently, I talked about this shift and how these tools are allowing us to turn traveler data points into profiles and profiles into niche audiences that we can market to. Lately, we’ve seen incredible progress in the notoriously complex travel industry, and it’s laying the groundwork for hyper-personalization at scale.

Here are three ways one-to-one marketing is changing the travel industry and four steps marketers across industries can use to get started with hyper-personalization.

What’s Old Is New—And It’s Working

While many people think email marketing is dead, the opposite is true. We’ve seen a continued resurgence in email and an expansion of SMS marketing channels in the last several months. Given that 60% of consumers have made a purchase as a result of a promotional email, email should be on every marketer’s radar. But that doesn’t mean they can use the same old playbook.

Thanks to AI and ML, campaigns are no longer just seasonal; they’re seasonal and personal, which means marketers can target travelers based on their specific interests. With GenAI, marketers can use personal data from guests’ likes and experiences to create tailored content and promotions and then adjust campaigns in real time based on user behavior.

For example, a traveler searching for flights to Italy in the summer might be grouped into an audience of “European culture seekers” or “food and wine enthusiasts,” but if they start showing a preference for coastal destinations, the campaign will adjust accordingly. This allows marketers to deploy programmatic campaigns that reach travelers with specific, tailored messaging, such as promoting food tours in Tuscany or discounted stays in Cinque Terra.

Moving At The Speed Of (Near) Real Time

Data analysis has traditionally taken hours, days or even months, but AI and ML models can quickly analyze data at scale and respond to trends in the market. Right now, political and economic shifts are influencing travel behavior in real time.

According to our internal data, we’re seeing a sharp (32%) year-on-year drop in U.S.-bound flight bookings from Canada starting in mid-February, primarily among leisure travelers. At the same time, Canadian travel to Mexico rebounded after an 11.6% drop earlier in the year, with a week nine increase of 24.7%. This indicates a massive shift in Canadian travel preferences.

In the past, analysts spent massive amounts of time identifying those shifts. Now, marketers can leverage models to sift through big query tables in minutes to understand behavior. From there, they can quickly deploy personalized campaigns to interested travelers and capture revenue. This near-real-time personalization is a massive step forward because marketers can adjust their activities based on how travelers are behaving now to woo them when they’re motivated to purchase.

Siloed Departments Are Coming Together

Traditionally, in the travel industry, different teams engaged with different guests, and those teams rarely interacted. Marketing was for looking and booking, operations communicated about check-in and other property information and front desk, maintenance and housekeeping teams solved on-site problems. Thanks to GenAI messaging platforms that can ingest, understand and respond to disparate needs, travel brands are starting to use a single source of communication to determine what the guests want and then funnel them to the right team for up- and cross-selling (“Can I upgrade my room?”), operational (“What time does the pool close?”) or housekeeping (“Can I get more towels?”) needs.

Here’s how it works: Customers communicate using text, WhatsApp and more, and all that information goes into a centralized GenAI-enabled communication tool that takes in the requests, understands the type of opportunity and responds and routes the information accordingly. This “human-centered” approach depends on unified property and guest data, as well as dismantling internal silos. And all of this takes time. However, when brands successfully integrate these siloed departments, they can maximize revenue per guest, create a more seamless guest experience and generate positive reviews.

Getting Started With Hyper-Personalization

Hyper-personalization is here, and it’s clear consumers want it. So, it’s time for brands to get started. Here’s how:

1. Determine the problem you’re trying to solve and only deploy technology if it directly addresses your specific business challenge. A great way to start is to determine your biggest pain point, such as poor guest reviews. Look at these pain points and use them to define a great guest experience. This will save you a lot of time, money and headaches.

2. Identify internal and external silos—across data, operational and tech stack—and begin unifying them under a shared strategy. However, it’s important to remember that silos aren’t just internal anymore. For example, the first time a potential customer engages with a brand isn’t always on a website. They could see an influencer post or a review, so it’s important to think about the entire ecosystem as you plan.

3. Prove your hypothesis. Once you’ve broken down the silos, take a customer-centric approach that leverages the right data to demonstrate the experience. Then, test, adjust and repeat.

4. Land and expand. Once the data proves impact, it’s easier to secure broader buy-in and scale personalization efforts across your organization. Use that information to expand your footprint and start the process over.

The future of travel marketing lies in real-time, personalized engagement—at scale. AI and ML are no longer experimental; they’re essential.

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