Minodes saves high-end retailers five hours a week with Tableau

Minodes serves more than 50 national and international retail franchises, including European car manufacturers, India’s largest shopping mall operator, and leading food retailers. Minodes’ analysts use Tableau Desktop to create workbooks, sharing them with customers over Tableau Server. These customized workbooks allow Minodes’ customers to get a deep view into their data, refreshing it as it changes—eliminating the need to create a new report every week. Today, Minodes delivers a scalable analytics-as-a-service offering that pleases employees and customers.

Tableau: Tell us about Minodes. Daniel Getejanc, Head of Business Intelligence: What Google Analytics does for websites, Minodes does for offline retailers. We allow retailers to better understand consumers, how they move through stores, but also outside of stores. We do that using sensors, which we install everywhere and collect data through.

We can re-use the template as many times as needed. And we don’t need to handle the data refresh manually. Everything is automated.

Tableau: Can you share how Minodes uses Tableau? Daniel Getejanc: We are using Tableau internally, especially in the Business Intelligence team. But we are also using Tableau Server in order to provide our customers with direct access. There we are at roughly 500 users currently. We create a dashboard for our customers, so they can better understand their data. But we also analyze their marketing efficiency. So basically, we install this kind of sensors. For a medium-sized retail shop—for example, in Munich—we install 30 to 40 sensors that collect Wi-Fi signals. The collected data is processed by a machine learning algorithm that maps where the customers are in the store, how long they remain there and especially important, whether they do come back and if so, what do they do. In addition to that, we run specific analyses to generate actionable insights.

One report per week took 4 to 5 hours. With Tableau, those 4 to 5 hours have been eliminated. And that’s just one example.

Tableau: How did you analyze those huge data volumes before? Daniel Getejanc: Initially we created customer specific reports using Excel and PowerPoint. The biggest problem was scalability, because it involved a lot of manual work. And that is why we chose Tableau: it allows us to create truly individual dashboards for the customers, while automating the process behind the scenes saving us a lot of manual effort. We looked at a few alternatives but realized that especially the learning curve isn’t as good as with Tableau. Tableau: What benefit has the solution brought to your organization? Daniel Getejanc: The biggest benefit is the flexibility we now have. The business intelligence team creates a template that we can re-use. And we don’t have to manually refresh the data. It’s all automated. We have a customer in high-end fashion and they wanted a weekly report. That took us 4 to 5 hours every Monday. Tableau has eliminated those 4 to 5 hours completely, and that’s just one example.

We looked at a few alternatives but realized that especially the learning curve isn’t as good as with Tableau.

Tableau: How satisfied are your users? Daniel Getejanc: Our users are currently very satisfied. They especially love the flexibility in creating analyses. Before, everything was in SQL, Excel and PowerPoint. Now we can present the central insights directly with Tableau, while at the same time giving the customer the opportunity to ask their own questions of the data. Tableau: From your perspective, are there any other key aspects for which you'd recommend Tableau? Daniel Getejanc: The community, which is really engaged with the product, driving it forward and making sure Tableau stays as good as it is.