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With over 3 million site visits a month and an impressive 96% customer satisfaction rate, online luxury fashion retailer Fashionette is one of the most popular online stores for bags, shoes and accessories in the German-speaking world.
In our recent webinar, Adverity’s Kirsten Ralph spoke with Fashionette’s Maximilian Nierhoff, Head of Business Intelligence, and Tobias Düperthal, BI Engineer, about why consolidation of data is a critical component of their success.
“Everybody knows that marketing has become more technical and complex in recent years,” says Neirhoff, “A key goal for Fashionette is to create individual shopping experiences, based on the latest data-driven technologies.”
According to Nierhoff, one of the big secrets behind Fashionette’s success is its sophisticated marketing intelligence. And the automated delivery of data generated from various sources is at the foundation of all the data-driven processes at Fashionette, whether data analysis or optimization.
But it wasn’t always that way. “When I started at Fashionette the company data was decentralized, stored in various silos,” explains Nierhoff, “and the workload required to keep an overview of all the tools and data structures was a major challenge.”
Things needed to change. And so Nierhoff sought out the help of Adverity; “I started talking with Adverity in 2018, looking for a tool to process and centralize our marketing data in the most logical and efficient way,” he says.
Fashionette took a broad approach to their data, preferring to cast a wide net and connect with as many data sources as possible. “Sometimes it is important to think big and import all your data in the most detailed way. This gives you much more flexibility and allows for deeper analysis in the long run,” says Düperthal, “but think about tomorrow, the only data you have is the data that you process.”
However, connecting to such a large number of data sources is a task full of challenges. “We are working with a mix of big and small players and each has their own interface, data structure, timing, and ways to make data available. This makes it very difficult to harmonize,” says Düperthal, “however, with the right tools at hand, you can very simply transform and unify the data structure to your own requirements.”
Working with Adverity allowed Fashionette to hit several key goals. The first was to replace manual workflows with data automation. The second was the ability to integrate and analyze a multiplicity of different data sources. And the third was to make fully-automated, up-to-date marketing costs data available to all stakeholders, for their own analysis and reporting.
Things went so well that in the summer of 2019 Fashionette launched a Business Intelligence department, with a focus on centralizing data across the whole company and establishing a multi-layered data stack that would produce relevant data intelligence for all segments of the business.
“Adverity is not a tool, it’s a process,” says Nierhoff. “Our goal as a business intelligence department is to satisfy the specific analytics needs of the company by providing useful and global data products,” he says , adding, “This is often a process of various improvements, feedback loops, and changing needs, and all this is only possible if the tool follows the specific process changes and not the other way around.”
To find out more about how Fashionette integrated their data to create actionable insights, watch the entire webinar on demand.