Smart Data

How to use data sets creatively

Creative data, smart data, big data. Members of the media frequently use these terms, which sometimes allude to the fact that large quantities of data make it possible to analyse consumer behaviour. As a creative netizen, I am naturally interested in creative data - and I would like to share some examples of how companies have used both personal data and demographic data for creative corporate communications. 

The following examples do not necessarily involve large volumes of data, but instead the creative use of data:

Deutsche Bahn

A well-known example comes from Deutsche Bahn (DB), Germany’s largest railway company.  German Facebook users see clever DB posts that make it clear they can discover amazing destinations without venturing into the big, wide world. There are great destinations in Germany, too – which ties in nicely with the topics of climate change and new mobility. By the way, DB launched this campaign before the coronavirus pandemic; the posts on Facebook have surely become even more topical in 2020.

DB’s strategy utilises the data generated by Facebook with regard to a user’s personal preferences, based on clues consisting of a user’s location-specific data.

Perhaps an example can illustrate this. Let us suppose that I love to travel, and I truly adore New York City. Facebook probably already knows that about me, as regular users of online media are aware of. So what is DB’s smart idea? An algorithm connects the dots by linking my love of The Big Apple with the price of round-trip plane tickets to NYC. I then see a personalised ad for Frankfurt am Main, the German city most similar visually to Manhattan and even nicknamed Mainhattan. Needless to say, transatlantic tickets cost much more for people living in Germany than train tickets to Frankfurt and back. Why not see for yourself?

Deutsche Bahn - No need to fly - Around the world in Germany (Ogilvy, Casemovie, 2019)


The digital music service Spotify caused quite a sensation in 2016. The company anonymously analysed its users’ listening habits within a certain time frame, and then commented on them by putting up humorous posters in public places. Because there were different posters in different cities, there was often a clear connection to a specific place and/or time. Soon after Valentine’s Day, for instance, this poster appeared: 

“Dear person who played ‘Sorry’ 42 times on Valentine’s Day, What did you do?”

Or in London, in the summer of 2016:

“Dear 3,749 people who streamed ‘It’s the End of the World As We Know It’ the day after the Brexit vote, Hang in there.”

At the end of every year, Spotify users get to see a particularly popular illustration of their data. The service uses eye-catching graphics to portray the user’s favourite songs and the percentage of new music they listened to over the course of the year. A user’s personal preferences also allow for many more treats that are similar to Instagram stories.

This year-end visualisation serves a purpose: most people want to regularly listen to good new music, although different people have different tastes in music. Data can help the platform to better tailor recommendations for the benefit of all listeners. And when I heard “Only 40% of the music you listen to is new”, I resolved to check out more new music in the new year. Here we are also primarily talking about the assessment of personal preferences. Demographic data is irrelevant to visual portrayals, although one could add some supplementary information, such as: “People the same age and gender as you haven’t listened to as much Miley Cyrus :/”.


Another example from Germany concerns Movinga, a start-up company for relocations. Moves generate a lot of data and can be illustrated on screen. A lot of people move to or within big cities such as Berlin, after all. And location trends naturally play a role, especially when it comes to the price of renting or buying a residence. After examining its treasure trove of data a few years ago, Movinga was able to express in statistics how Berlin has changed:

Pankow is the new black. One in five people who move within Berlin pick Pankow. 


Nobody wants to be caught dead in Spandau? Of all moves within Berlin, only 3% end up there.

Considering that I am from Düsseldorf, I am curious how many people move from Cologne to Düsseldorf, and vice versa. This sadly was not part of Movinga’s ad campaign, but the nerd in me enjoyed the stats on Berlin.

The examples above make it clear just what we can do with data, and that people do not need to feel threatened by data analytics. Granted, data protection is important – a frequent topic here in our Next.ERGO portal. It is impossible to protect all your personal data, unless you have neither an internet connection nor a smartphone nor any similar technology. But if you use any modern technology, then companies will gather your data – and sometimes utilise it for creative purposes. We should foster this trend!

Text: Markus Sekulla

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