Gutefrage.net is an advice website, supported by user-generated content. It is one of the widest-reaching websites in Germany, with up to 100 million visits per month. The company uses Tableau to monitor key performance indicators in specialist units and to make sound decisions based on confirmed data. Tableau enables employees to work quickly and independently, giving them more time to work on other projects. With Tableau, gutefrage.net found that reports are often available within minutes instead of weeks—increasing productivity and reducing the time it takes to complete daily tasks.
Tableau: What does gutefrage.net do? Dr. Franz Graf, Senior Data Scientist: gutefrage.net is Germany's biggest advice portal. It is a platform where users can ask questions about everyday life and receive useful answers within a short period of time. Tableau: How are you using Tableau at gutefrage.net? Dr. Graf: Tableau is used nearly every day. It offers quick, usage-relevant access to key data and independent access to data. Above all, the IT bottleneck has been dramatically mitigated, meaning that product owners or individual departments can work in a much more independent manner. Tableau: What do you like about Tableau in particular? Dr. Graf: The biggest benefit from the perspective of the users is certainly the fact that they no longer rely on IT for all tasks. They can work independently and access data quickly. In particular, they can quickly analyze data in an explorative manner and make quick, data-driven decisions. gutefrage.net benefits from Tableau as a BI analysis tool, because we have significantly reduced the round-trip times for answering analysis questions, partly from a matter of weeks in typical ticketing to a matter of minutes or hours. In the area of sales, we’ve also made savings. A half-hour investment in Tableau workbook creation can result in savings that are in the man-day double-digit range. And savings are also easily made due to the fact that sales people can directly access data quickly and easily, where they would otherwise need to keep writing tickets to IT.
Tableau: What was the situation like before you opted for Tableau? Dr. Graf: Before Tableau was rolled out, we didn't have a dedicated BI. Basically, we had no dedicated BI system. Consequently, analysis questions were passed on to IT, whether it was to the product owner or via tickets. Of course, this resulted in long round-trip times and long response times. Because the users were also used to having such long response times, they didn’t even ask many relevant questions. This has changed thanks to Tableau. We went through a larger evaluation process at the end of last year, during which we evaluated several candidates. Ultimately, the great user-friendliness, intuitive use, and quick operation, but also the price and license model, were great plus points for Tableau. Tableau: Are there any other key aspects that should be mentioned? Dr. Graf: One thing I really like about Tableau is the fact that it gives me the option to involve my colleagues in the analysis process. That means our colleagues can work independently, which gives me more time to invest in other projects. Tableau: What is the Tableau solution used for in your company? Dr. Graf: The users covered via Tableau are, above all, data scientists and product owners, but department heads also use Tableau to make data-driven decisions. We currently have about ten Desktop users working with Tableau. Added to that are about 15 Tableau Server licenses, which are mainly used by department heads. Tableau is mainly used in several areas. On the one hand, we use it for data science and data analysis to establish interrelations between data and run visual analyses. On the other hand, we also use Tableau in pure dashboarding, or in other words, when tracking KPIs, which are important to the company to get quick access to relevant data. Another example of an area where we use Tableau is for product owners who want and have to test quickly—whether they are developing the features for the correct KPIs or tracking the right KPIs to test whether the features work correctly and have the right impact. Of course, we also use it across the company in the areas of controlling, marketing, and sales to quickly access data and make these jobs easier.
Tableau gives me the option to involve my colleagues in the analysis process. That means our colleagues can work independently, which gives me more time to invest in other projects.
Tableau: What data sources do you use? Dr. Graf: At gutefrage, we currently use several data sources for Tableau. The MySQL database, where the master data is stored, is the main source used, but we also use Google Analytics as the tracking source and the source of events. The Google Analytics Connector of Tableau was an essential part of the evaluation for us because Google Analytics is a very common, deeply rooted tool. This also means that it was very important for Tableau to integrate well into the Google Analytics environment. Also important for us, of course, is the connection to AdSense so that we can check sales at all times. Another matter that is becoming increasingly important for us is event tracking, which comes directly from the website. This means that the events are saved in Hadoop and also back via the feedback loop to the Hadoop or Tableau users. This means that for all analyses run, MySQL is accessed directly, and the data is interpreted with Tableau. In terms of product owners, they definitely also use it at least several times per week and even daily, as the events and KPIs need to be permanently tracked in this case too. In terms of CEOs and CTOs, we’re certainly in the range of weekly usage: Company KPIs are also permanently tracked. Moreover, pure Tableau Server users, in other words, the individual departments, use it several times per week. Tableau: What is the outlook like for the future? Dr. Graf: We certainly plan to expand the use of Tableau in the future. On the one hand, we plan to connect more users to Tableau, which will allow even more users to make data-driven decisions, etc. And on the other hand, we are planning to integrate Tableau into the data warehouse and the entire Hadoop environment in order to quickly and efficiently analyze this data set, too.