Locatus Digs into Data for Actionable Trends

What took us hours or a day, we can do now in just a few clicks. That’s the biggest advantage.

Locatus is the market leader in the field of independently sourced retail information in the Benelux region (Belgium, the Netherlands, and Luxembourg). The company is currently expanding its working range throughout Europe. At the 2011 European Tableau Customer Conference, Chief Information Officer Gertjan Slob described how Locatus uses Tableau to dig into their data and identify historical trends that they couldn’t have seen otherwise. “Tableau makes it easier for us to come to new insights and bring new insights to our customers.”

Tableau: How did you first find out about Tableau? What problem were you trying to solve?
Gertjan: We had a problem with creating a historical database, and we wanted to use a database management system. From a previous job, I knew a system, but it was way too expensive for us. So we looked for a flexible, more affordable solution and found it in Tableau. That was two or three years ago.
   
Tableau: What type of data are you working with?
Gertjan: We have a data set with all of the shops in the Netherlands, Belgium, and Luxembourg. It’s created every week, and it’s always the snapshots of our data. The data became much too big for Access, and that’s how we came to Tableau.
   
Tableau: How do you collect your data?
Gertjan: We have a team of workers to collect our data. We have 15 people working and living across the Benelux region. I have the current data set of a municipality, and they just go to the municipality and do the checking if each shop on our list is still there and if the situation is still what we have in our database.

We also have some data entry people who do some checks on the formulas, and we do some web crawling to find all the shops for a certain multiple from the Internet. We do have some add-ons, but the core of our data collecting is our surveyors.

   
Tableau: What kinds of trends are you looking at over time?
Gertjan: We don’t always know the trends we’re looking for in advance. That’s one of the reasons we use Tableau, to just dig through the data and see if there are ideas coming up. We’re always using snapshots of the data, so looking in advance is quite new for us. But some things we have in mind because of what we see and what we have in our database and things we just know.
   
Tableau: Can you talk about some of the trends you’ve discovered?
Gertjan: One of the trends we discovered first was the development of the number of vacancies in the Netherlands and also in Belgium. We see a direct relation between the percentage of vacancies in shops and the economic situation of the last three years, after the economic crash. We showed a huge increase in the number of vacancies.

So what we did was dig down into this problem to see if there were differences in the situation in different parts of the cities and streets. We saw that in the top streets in Amsterdam, we didn’t see the national trends. The number of vacancies was very low and constant instead of increasing. But in the more outer parts of the cities, the national trends were steeper. So, there’s a big difference within the city, and we found that by digging into this data problem.

   
Tableau: What have you found to be the greatest benefits of using Tableau?
Gertjan: One benefit of using Tableau is the speed. What we had to do before to get historical analyses cost us a lot of time. We had to find the proper data sets and if we had the proper data sets, we also had to overcome definition problems. What took us hours or a day, we can do now in just a few clicks. That’s the biggest advantage.

By being faster and easier to use, Tableau also makes it easier for us to come to new insights and bring new insights to our customers, like what I just mentioned about the difference between parts of the city.

   
Tableau: How many people at Locatus are using Tableau?
Gertjan: Three.
   
Tableau: What do you see for the future of Tableau at Locatus?
Gertjan: We mostly want our customers to use Tableau. I think the insight it gives us and the help it gives us to do more analyses because it’s faster and easier should also be available to our customers. But our customers are not data-driven people, so we have to work with that.
   
Tableau: What advice would you give to another small company that was looking for an analytic solution? Whether they use Tableau or not, what best practices would you suggest to make their project successful?
Gertjan: They should pay a lot of attention and should invest time in definitions. It took us multiple weeks of work to overcome our definition problems, and still for every new data set, we have to look into these definition problems. And you have to keep good track of all the definition changes you make. If you know what the definition changes were, then it’s much easier to overcome problems if you create a new data set of multiple things that have changed over time.