Munich, Germany-based Urban Brand GmbH is an online retailer selling products for babies and children through its three European e-commerce sites: Windeln.de, Windelbar.de and Windeln.ch. The company's flagship site, Windeln.de, delivers products within 1-2 days to homes across Germany. Urban Brand GmbH reported revenues of seven million euros in 2011 and 27 million euros in 2012.
In this English-language video, Dr. Lucie Salwiczek, Data Scientist, Urban Brand GmbH, discusses how she uses Tableau to increase the speed and flexibility of data analysis.
There is also related content in German.
Tableau: Can you tell us what a data scientist does for an e-commerce company?
Dr. Lucie Salwiczek, Data Scientist, Urban Brand GmbH: I analyze data, collecting data, blending them, providing them internally to other departments and externally to our website, to our customers.
Tableau: What sort of data do you normally analyze?
Lucie: Our company focus is on young parents, pregnant women, and parents who have kids up to the age of four. We have more than 20,000 products that one can buy and we have approximately tens of thousands of customers who buy something, and millions of visitors. So we have quite a lot of data—and some of the data are really time-sensitive. For example, we have deals. I have to make the decision "Do I make a deal tomorrow again? Do I extend it? What was the customer response?
Tableau: And how does Tableau fit into this scenario?
Lucie: You want to analyze the data now, and Tableau can help with this. You use the data warehouse and the real, live data.
Real-time data is very important for us. In logistics, for example, we make the promise that if you order by 5 pm, you get the product the next day. We can't wait until the next day with a solution; the product has to get there.
Or as another example, we work with Google Analytics, Google AdWords, to obtain the data. Then when we have a deal, for example, to be able to respond immediately with prices, depending on how we see our product performing with this price relationship. And then we need to respond right away—within an hour, within a day, within two hours. But that needs to be monitored at all times.
Tableau dashboards provide a lot of flexibility, so you can provide a nice background, and still focus on a single detail. And with a dashboard, it's possible to stay in the overview, or also expand one part and analyze it in more detail. Since data doesn't mean anything out of context, it's good that the context is really accessible.
Tableau: That must help you make decision faster. Do you also use Tableau’s visual analytics to help others understand your findings?
Lucie: Tableau allows me to create something that's visually impeccable and still present complex data in one place. So I can have the whole marketing department sitting in front of one screen, and we can drill down and talk about details or look at the big picture. I think it's a cool thing, and will really, really advance decision making—making it quicker, making it more thorough.
Tableau: Are there other ways that Tableau is helping you?
Lucie: Tableau is very helpful to the extent that I can tap into a large number of data sources that I wasn't able to link together before.
Before Tableau, I had to get the data from everywhere and have it all in one place. Then I had to transform, compile or import it somehow so that I had it in a single system—which was quite an arduous task. With Tableau, that's far, far easier.
Now I can just combine the data together, merge, analyze and prepare it, check data quality, create reports, dashboards, and so on. It's really enjoyable to get data from everywhere and be able to analyze data visually, not just with numbers, but to have a combination of both.
Tableau: Are you using Tableau to look at data in new ways?
Lucie: Tableau is giving us new ideas about where we need more data, where we need more analysis. While I was playing with Tableau to get to know it better, I discovered that I can do many things in parallel. I play with it, analyze the data and see, “Wow, here I have to improve my data quality.”
So I do both in parallel, so to speak. It's not separate anymore, in my mind.
With Tableau, you already start analyzing. And by analyzing, you get two things: you get the result to a question, but you also look at your data and identify where you need some more data, where you need improvement.
And you also get ideas to say (to people), “Hey, did you ever ask this question? Is this interesting for you? Maybe I have an idea, and maybe they say, "I didn't know you could do it." So while you are playing with Tableau, you also create new ideas for new avenues that we haven't thought of yet.
Tableau: Can you tell us your overall impression of Tableau?