Analytics gives Scandinavian Airlines a clearer picture of its customers

“Where will you be going?” The airline Scandinavian Airlines (SAS), sometimes knows the answer to this question even before the customer does. Thanks to an advanced technology platform from SAS Institute and predictive models for customer behavior, the airline can develop more relevant offers for its customers.

“If you have previously visited our website and looked for trips to New York for two adults and four children, and we know through our models that you are sensitive to price but usually buy extra seating space and extra luggage, we can adapt our offer so that it will be the most relevant in real time.” 

Malin Nygren
Head of CRM

Scandinavian Airlines has a large customer base with different needs and preferences, and a broad product selection designed to appeal to the company’s different types of customers. Like most large companies, it also faces the challenge of targeting relevant offers through the right channel and at the right time at each individual customer.

The solution for Scandinavian Airlines has been to take a few steps back and renew its communication approach, which has given the airline a better picture of its customers as well as allowed the company to make the analysis process more efficient. Rather than focusing only on Eurobonus members, all customers are now a part of the analysis process and more sophisticated communication. The goal for Scandinavian Airlines has been to get a much more refined understanding of the customer, which can thereby provide a better basis for optimizing sales in both its own and external channels.

The airline commissioned SAS Institute to build an analysis platform and to train two employees to be data scientists. The purpose behind this was to raise the level of analysis in general, while simultaneously making it possible to work with more statistical models for creating future insights. With tools they can use themselves, analysts at the airline now have more time to spend on modelling for the future and doing what is known as predictive analysis. The organization now also has access to dynamic dashboards where employees can do simple analyses themselves.

Sell more – and communicate less

One of Scandinavian Airlines’ great challenges is the fact that the company, like most large companies, is organized in silos. Previously, important data wasn’t always shared between divisions, and there was a lack of an established cooperation between the analysists from the different units. For example, it happened that the team responsible for the website worked on one analysis of how customers behaved, while the team responsible for e-mail worked on another analysis of the same group at the same time, with the only difference being that they examined how the group behaved in different channels.

“The goal has been to get a more complete and correct picture of our customers than before. Since we are now including all customers in the analysis, we have changed our communication,” says Malin Nygren, head of CRM at SAS and leader of the project.

“The product owners’ basic attitude is to sell what they are responsible for – here and now, and always. We turn this thinking around and instead try to sell as efficiently as possible the product that is most relevant for the customer and what SAS makes most money on.”
Mattias Andersson Scandinavian Airlines Head of CRM Analytics

Mattias Andersson
Head of CRM Analytics

The fact that Scandinavian Airlines now have much better precision in marketing also means that clients are less exposed to irrelevant offers.

“We certainly don’t want to spam our clients so that we risk them choosing to not receive offers from us,” says Mattias Andersson, Head of CRM Analytics at SAS.

“With the help of predictive analysis we can, for example, send out offers to less than half as many recipients but still get almost just as high a response measured in the number of conversions, upward of 85%. In reality, this means an increase since we can then send another relevant offer to the others who did not get the initial offer. Knowledge of how the recipients act on the offers also helps to continuously make the analysis models better and better.”

Aside from responses to campaigns, there is a great amount of other information that forms the image of which individuals are most ready to jump on a certain offer.

“For our Eurobonus members, we can see their travel pattern and geodemographic data such as zip code, gender, age and a number of other things,” says Mattias Andersson.

“At the same time, the majority of our customers are not in the Eurobonus program and it is just as important to give them a tailored and relevant experience, so that they feel seen when they, for example, visit our website,” says Malin Nygren.

Today, many SAS Institute product owners use dashboards to help identify the right recipients for various offers.
“This is a huge step forward,” says Malin Nygren, although she feels that there is still more to be done.

“We are now working to develop cross-functional teams who, together, will work from the customer perspective from the start. It will help us be more relevant for our travelers, and at the same time we will save money. It is pretty meaningless to put resources into chasing an unprofitable customer,” says Malin Nygren.

“The program has increased the department’s ability to visualize analyses and build application areas where the product owners can look at their own data from different perspectives and create insights” – Mattias Andersson, Head of CRM Analytics

Scandinavian Airlines

Challenge

Product-oriented organization and insufficient effectiveness in marketing communication. Difficult to be relevant to all customers, both Eurobonus customers and others. 

Solution

The analysis platform and predictive models from SAS Institute, as well as professional training of two employees in SAS Institute’s Data Discovery Scientist Program to insource and centralize analysis. 

The result

More precise marketing, reduced costs, increased customer focus.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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