The travel industry is competitive. 

This case study breaks down one of the most successful travel sites in history: Booking.com. We explore how they use personalization to maximize conversions.

We'll also share relevant studies that substantiate these strategies. Lastly, for those interested, we'll share how you can replicate these techniques on your own site. 

Let's begin!

From the study:
“Getting that first visit is like planting seeds. It is a lot of effort and work and to prepare the land i.e. create the conditions to get a customer on site.

Returning visits takes that customer from seed to fruit bearing tree. All the profit happens as you are able to bring the customer back and begin learning, engaging with, and converting that lead.”

Here, Booking.com does a fantastic job recognizing returning clients, and use their pricing strategy to prompt customers to sign in.

When I first come back to the site, they welcome me. The copy is personal. Most beautifully, they give me a clear reason to login.

Instead of simply displaying a login button hidden in the far right corner of the page, they take the opportunity to reiterate their value proposition: "Sign in to see deals up to 50% off".  

How do you welcome returning customers who aren’t logged in? 

Booking.com understands the power of personalized recommendations.

Directly underneath the search bar is a recommendation widget.  As we will see, they personalize these recommendations in real time.

The question is, how should you personalize recommendations when you haven't gathered any data from your customers yet?

Upon landing, Booking.com knows where I am.

Based on my IP address, they create recommendations. My guess is that these recommendations are the most frequently searched for travel destinations from people in my current location of Omaha, Nebraska.

Previously, we studied how effective personalization can be on recommendations. 

You can see the full study on personalized recommendations here

Looking at over data from 300 randomly selected clients, we found that recommendations accounted for 31% of eCommerce revenue. In fact, customers who engage with recommendations have a  70% higher purchase rate. 

The kicker though is how personalization boosted conversions. Personalized recommendations outperformed generic/static recommendations by 170%.

Geographic personalization is a fantastic way to create relevant offers without knowing a lot about your customers.

There are actually multiple ways you can personalize your customer’s journey with minimal information. The first is through onsite personalization. We showcased how one of our clients is doing that through targeted messaging. 

Above, Skandium is presenting personalized message bars to new customers. The message changes depending on the location. For example, they address a common concern for US shoppers about  import duties, while conveying shipping deals to local customers (full case study here).

The second way, which is how Booking.com does it, is via personalized recommendations.

While you can personalize recommendations in a multitude of ways, here Booking.com selects geo-location as the primary way to select which offers to present. 

Booking.com boosts conversions by leveraging a number of social proof mechanisms. 

Depending on the current offer, they highlight various aspects to get browsers to pull the trigger today. The goal is two-fold:

Using various forms of social proof to create both trust and urgency helps improve these metrics. 

After my initial search, I went back to the homepage to see how Booking.com incorporated my session data into their offers.

They did so in three major ways. 

The most obvious are the recommendations. When I first visited Booking.com, they only knew my location. Therefore, they did their best to present offers that were relevant, based on other travers from my city.

There was no way for them to know that I was interested in visiting Puerto Vallarta. 

But, as soon as I initiated a search, I revealed an affinity. In this case, Puerto Vallarta, Mexico. Going back to the homepage, Booking.com updates the offers they make with this new information. 

Instead of offering "best guess" recommendations of Chicago, Reno, Atlanta, and San Diego, they incorporate my revealed preferences. 

First, they showcase my last search as the primary recommendation. They then supplement it with a number of similar travel destinations like Nuevo Vallarta and Guadalajara. 

Another nice touch Booking.com uses is personalizing their calls to action. 

Again, they incorporate my preferences in real time. When I navigate back to the home screen, instead of a generic search bar I see a pre-filled search, loaded with my latest information including the number of guests and checkout dates. 

Lastly, Booking.com distinguishes the most likely offer with product badges and rich data.

They place a flag emoji next to the city name.

They place the top reasons to visit as a secondary header. It reads: "beaches, relaxation, friendly locals". 

They overlay a simple call to action with a fantastic, short question. "Still interested in your previous searches for Puerto Vallarta". And - they let me pick up right where I left off by auto-filling my previous search. 

All of these actions display an understanding of what is relevant for me as the shopper. They place the offer with the highest chance to convert at the top, make it larger, and enhance the offering through data. 

The lesson is to incorporate your customers in-session behavior to all pages. 

Your home page, category, and product pages should all reflect what you know is true about your prospects. 

As always, the next step after learning is action.

We covered a lot. I suggest taking one tactic that you believe can help your travel site increase conversions and implement.

If you are looking for a technology partner that can give you all of these capabilities, consider Barilliance. We help dozens of travel sites and hundreds of eCommerce sites with real time personalization. 

If you want to learn more, setup a time to chat here.