SAS harnessed artificial intelligence to boost ancillary revenues. Here’s how.

Kati Anderssen

VP, Digital Sales & Distribution, SAS

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Every year SAS serves nearly 30 million passengers. It’s a priority for us to meet their expectations by understanding the context in which they are traveling. This not only ensures that they have a great travel experience, but it also positively impacts our ancillary revenue. All of this is made possible with cutting edge technology.

In today’s competitive landscape, airlines must continually search for new revenue opportunities. We saw the possibility for growth with ancillary services. In 2016, the SAS Ancillary Team set-up an ambitious target of doubling ancillary revenue by 2020. To achieve this goal, our ancillary offer had to be optimized and aligned to travelers’ expectations. This is why we joined the Accenture Amadeus Alliance.

By leveraging Amadeus technology and deep airline expertise along with Accenture’s powerful data analytics and machine-learning models, jointly developed with the Massachusetts Institute of Technology (MIT), the Alliance helped us create data-driven insights that rapidly generated value. We applied the Alliance’s expertise in artificial intelligence to study advanced seat reservations in our European market. This provided us with insights on how to best set and vary the pricing of this offer.

To deliver appropriate insights, SAS and the Accenture Amadeus Alliance followed the structured, agile and data driven approach that lies at the core of the Merchandising Intelligence offering. Clustering and data analysis were applied to our European route network to ensure that the design and execution of the experiment was fit for our purposes. Artificial intelligence was then used to identify the most significant variables that impact customer purchasing behavior.

By capitalizing on machine-learning algorithms, it was possible to identify purchasing probability based on a given context. From this, we derived both pricing recommendations and the predicted impact on the sale of seat reservations. During the project, customer satisfaction was also closely monitored to ensure no negative impact or sentiment was expressed.

After 12 weeks of working with the Alliance team, we applied 11 new pricing policies to offer the best price for a given context. The impact of the new context-based pricing implementation was immediate. During the three month monitoring period, we saw a consistent 14.5% uplift in ancillary revenue for advanced seat reservations in the European market while maintaining customer satisfaction.

So far, we couldn’t be happier with the results of this collaboration. Merchandising Intelligence is a new and innovative approach allowing us to gain deeper insight into our customers’ behavior. With an understanding of the customer context, we can enhance our ancillary offer and match value with traveler expectations to positively impact our ancillary revenue. Have a look at the SAS & Accenture Amadeus Alliance case study for more details.

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Customer Testimonial, Artificial Intelligence, Research, Guest Post