AWS for Industries

Personalizing loyalty programs for engagement in the travel and hospitality industry

The average American today participates in 14.8 different loyalty programs, and odds are you’ve participated in one, too. Some of the larger travel and hospitality loyalty programs include Alaska Airlines Mileage Plan, Hilton Honors, and Domino’s Piece of the Pie. Programs like these are popular because they work. Loyalty members generate on average 12% to 18% incremental revenue growth per year than non-members and 66% of consumers modify the amount they spend to maximize loyalty offers, buying more often and spending more than non-loyalty members.

But when most customers face a daily barrage of emails, messages, and loyalty offers from every company they’ve interacted with engage with, how do you, as an airline, hotel, or restaurant, keep your program relevant?

One powerful lever you can use is personalizing your engagements. Personalization is not a specific tactic, rather, it is a methodology by which organizations go about delivering more relevant communications to their customers. Personalization enhances the customer experience, deepens loyalty, and increases revenue by delivering the right message (offer) to the right customer over the right channel at the right time.

In fact, well-executed loyalty personalization efforts can drive a tenfold increase in member satisfaction. Let’s discuss how you can use AWS to personalize your loyalty programs and increase engagement.

How to deepen loyalty program engagement with personalization on AWS

AWS provides a suite of services that you can use to personalize your loyalty offers for increased conversions and deeper engagement. One solution we’ve developed combines Amazon Personalize and Amazon Pinpoint services into what we like to call Predictive User Engagement.

This solution enables organizations to deliver personalized loyalty offers based on real-time interaction patterns, stored profile data, and machine learning.

For instance, an airline can algorithmically inspect a customer’s clickstreams to see that the customer is looking at flights from JFK to SFO and normally purchases a seat upgrade on flights over 2,000 miles. The airline can then use this information to deliver an email offer offering priority seat upgrades on their next flight if the customer joins the frequent flyer program.

In another example, if the customer is a longtime loyalty member, the airline could send a text message offering an “aisle seat in business class for your loyalty” to deepen their engagement.

You can think of similar examples in hotels, where the hotel could use reservation, Wi-Fi, and beacon data to send a “get 20% off spa services when you join our rewards program” offer to frequent guests who often book spa appointments.

A restaurant could also send older customers an offer to join the program for 10% off entrées by identifying senior citizens with specific buying patterns.

Each of these examples uses Amazon Pinpoint to identify customer interaction patterns, group them into segments, and deliver the messages across channels. Amazon Personalize (or Amazon SageMaker) is the machine learning service used to generate the “next-best-offer” predictions that power the personalized recommendations.

Remember earlier where we talked about sending the “right message to right customer over the right channel at the right time?” Amazon Pinpoint takes care of the customer, channel, time, and message transport while Amazon Personalize or Amazon SageMaker takes care of the personalized or recommended offer content.

When evaluating personalized loyalty offers of your own, there are a few considerations you’ll want to keep in mind:

  1. Data sources: Where are you getting your data that’s being used to inform your personalized messaging? Is it being stored and structured in a manner that’s easy for a machine to access and read? Do you have the right data sources to make personalized messaging effective? (that is, reservation data, demographics, location, clickstreams, Wi-Fi, etc.). AWS has the deepest and broadest set of data management services in the industry.
  2. Timeliness of message: Are you delivering your message at the right point in the customer journey to optimize for conversion? If you send a drink ticket offer for an upcoming flight after the customer has boarded the flight and taken off, you probably won’t see a conversion. AWS Customer Engagement solutions can determine the right time to send a message based on prescriptive (defined) or predictive (inferred) patterns.
  3. Channel of delivery: Are you delivering your message across the right channel for each customer? For instance, your younger customers may prefer mobile channels like SMS while your older customers may prefer voice. You also probably won’t want to send a time-sensitive, proximity-based message over email. Amazon Pinpoint can deliver engagements across multiple channels, determine which channel each customer engages with the most, and even redeliver messages between channels if the customer doesn’t engage over the first.
  4. Segmentation: Are you able to segment your customers into groups based on their unique profiles or behavioral characteristics, such as “frequent visitors,” “new customer,” “corporate customer,” or “likely to churn?” Amazon Pinpoint enables you to programmatically segment your audience into groups like these, and machine learning tools like Amazon Personalize and Amazon SageMaker can turbocharge your segmentation capabilities. (I’ll talk more about this in a later post.)
  5. Program design: This one is personal. Ensure that your loyalty program design is enticing enough to attract customers, delivered on a schedule that encourages engagement and not spam, and is economically non-dilutive to your business.

Loyalty programs can be powerful engines to enhance travel and hospitality customer experiences, deepen customer engagement, and increase revenues. But today’s customers are bombarded with messages, meaning you need to ensure that your loyalty offers are personalized to each customer. All of the tools you need to achieve this – from customer data management to messaging to personalization – are on AWS.

Learn more about how AWS is enabling the most innovative Travel and Hospitality brands.

Andrew Levy

Andrew Levy

Andrew Levy is the Business Development Manager for Customer Engagement Services at AWS. He brings over a decade of experience leading digital strategy and growth efforts at brands like Twitter and multiple venture-backed startups and funds. In his spare time, he enjoys traveling, fitness, and eating tacos.