If you would have asked me in the year of 2011 when I started my psychology studies whether I want to work with statistical questions and wether I would like to work with something called databases and programming structures I would have most probably said: “ABSOLUTELY NOT!!!” Nevertheless now I am here, just quit my job in Trade Marketing and working on becoming a Data Scientist with the help of the FlatIron School. I initially met the job as a data scientist when I was working for an innovative project of a big German airline company where we were working on enhancing respectively optimizing the personal customer experience of every single customer of that airline. Part of this project have not only been people from the airline itself but a looooot of consultants from all different areas: Project Manager, Scrum Masters, Marketing Specialists, Data Scientist, Data Archistect, and so on and so forth. The heart of this project was the database of the airline customers and the derivated questions that we could address in order to optimize the customer journey. I felt like the data scientists of this project where like the REAL brain behind it. Without them we would have just followed a strategy with no fundaments - we would address old and young customers, female or male customers, customers with kid, without kid, business travellers, leisure travellers - all with the same message! And this is probably the worst customer experience ever.
When I stopped my internship there I thought this data-driven work style is state-of-the-art in all companies. But little did I know!! When entering the trade marketing field after completing my masters studies I got to know the real world. Where you don’t really base your strategic activities on any data. Let’s just check out what will be the output after doing this and that. Seeing this made me aware of the actual importance that we need to give the data that is out there. It is extremely important to get to know about the data a company has, what they are allowed to do with it, how it can be structured and most importantly to be able to apply the right techniques in order to perfectly make use of the data that we have in place.
In fact I do not need to become a full and perfect data scientist in the end - I just want to get to know the bigger picture, to be able to work most efficiently around data scientist and to convert these data-driven learnings into a bad-ass marketing strategy :)
Cheers, Lexxi ```