Trait Enrichment: The Future of Personalization in Travel, Hospitality, and Quick-Serve

There’s something comforting about landing in a new city, scanning the terminal, and seeing the familiar blue-and-white United Airlines logo at the gate. Or walking into a Marriott Hotels property, already knowing where the gym is located, what kind of breakfast I can expect, and that—yes—my Titanium Elite status will probably score me an upgrade.

It’s not just habit. It’s loyalty—and it could be deeply data-driven.

Behind the scenes, travel and hospitality brands are exploring more advanced ways to understand and serve their customers. One of the most powerful strategies on the table is trait enrichment—a capability that, when used effectively, can transform how brands think about personalization, loyalty, and retention.

What Is Trait Enrichment?

Trait enrichment refers to the process of enhancing behavioral event data—clicks, bookings, cancellations, app usage—with additional context from customer profiles, such as:

• Loyalty tier
• Preferred destinations
• Lifetime value
• CRM fields
• Membership tenure
• Personal preferences

By fusing behavioral data with these kinds of traits, businesses can create a far more complete and actionable understanding of their customers.

A Loyalty Story, Imagined and Enhanced

Let’s use a hypothetical example.

Say a traveler like me is loyal to Marriott for hotels and United for flights. Over the past few years, I’ve consistently chosen them over alternatives—not just because of brand familiarity, but because of small, seamless touches: app notifications, upgrades, loyalty rewards, and relevant emails.

Now imagine if these brands enriched their behavioral data with traits like:

• Loyalty tier (e.g., Titanium Elite or Premier 1K)
• Preferred booking channel (e.g., mobile app)
• Favorite room type or seat class
• Check-in patterns or cancellation frequency
• Engagement with loyalty emails or app notifications

With this enriched profile, they could notice when my activity starts to drop (a potential churn signal), and proactively personalize outreach—like offering bonus points, promotions, or experiences that match my preferences.

They might also better understand which traits correlate most closely with high-value behaviors—informing how they market to new members or prioritize upgrade offers.

Could Quick-Serve Brands Like McDonald’s Do This Too?

Now let’s apply this thinking to a different vertical: quick-serve restaurants.

Imagine a global brand like McDonald's, which has millions of customers engaging daily through mobile orders, kiosks, and loyalty programs. While the transactions themselves are straightforward, there’s potential gold in the data—if enriched properly.

For example, McDonald’s could hypothetically enrich behavioral data with traits such as:

• Loyalty tier (e.g., rewards program level)
• Preferred meal times (e.g., breakfast loyalist)
• Favorite items (e.g., double cheeseburgers, iced coffee)
• Average spend per visit
• Frequency of mobile app vs. in-store orders

With that, they could power use cases like:

• Churn prediction: Detecting if a once-frequent customer hasn’t visited in weeks
• Menu personalization: Highlighting favorite items or offering early access to new ones
• Reward optimization: Tailoring rewards based on lifetime value or order behavior

Again, this is entirely hypothetical—but it illustrates how trait enrichment can enable smarter, more precise customer engagement.

What Adobe Can Enable

Disclaimer: None of the companies mentioned in this article—Marriott, United Airlines, or McDonald's—are confirmed users of Adobe tools for the specific use cases discussed. These examples are purely hypothetical and based on my personal experiences as a loyal customer who uses their services weekly. The intent is to illustrate how trait enrichment could be applied in the travel, hospitality, and quick-service restaurant industries using technologies like Adobe offers.

If a brand were to pursue this type of strategy, Adobe’s tools can support it in a few key ways:

• Adobe Customer Journey Analytics (CJA) allows you to analyze behavioral data alongside enriched traits—providing historical and real-time insights into the omni-channel customer journey.
• Adobe Real-Time CDP (RTCDP) can collect and manage rich profile traits, stitching them across devices and channels.
• Adobe Journey Optimizer (AJO) can then use these enriched segments for personalized cross-channel activation, whether through email, push, or on-site messaging.

Together, these tools enable what we’re imagining here: a closed-loop system of data analysis, personalization, and activation—all built on a unified customer profile.

Why This Matters for the Future of Travel & Hospitality

In today’s market, loyalty is more fragile than ever. Travelers have endless options, and expectations are high. Brands that want to stand out must go beyond simple rewards and into truly understanding their customers’ journeys.

Trait enrichment makes that possible. It enables:

• More meaningful segmentation
• Timely, personalized outreach
• Smarter retention strategies
• A clearer understanding of what drives high-value behavior

It’s a mindset shift—from “what did they do?” to “who are they, and what do they need next?”

Because when your system knows your customers as well as they know themselves, every journey—whether in the air, on the road, or at the drive-thru—can become more rewarding.