From 28 pairs of shoes to 10 million products

The journey with Adobe Customer Journey Analytics began at OTTO (GmbH & Co KG), one of the largest e-commerce providers in Europe in early 2021 with a Proof of Concept (PoC), also supported by Adobe. Since mid-2021, the company has been working productively with Adobe's Advanced Analytics to optimise the websites of its online shop based on flexible data analysis. OTTO was already using Adobe Analytics and decided to make the switch mainly because of the great flexibility and deeper analyses that Customer Journey Analytics offers.

The e-commerce giant from Hamburg is currently in the process of converting its own successful business model into a platform on which retail partners can also participate with their products and brands. According to the company, this is “probably the most significant change for OTTO” since it began online trading in 1995.

A brief look at history reveals that OTTO has been a data-driven company since its beginning in 1949, when the Werner Otto mail-order business started with a selection of 28 pairs of shoes. Since then, the company has guarded a valuable treasure: the data of its many millions of customers, who used to order mainly via the famous Otto catalogue. The catalogue, with a circulation of millions, has been history since 2019, but data still plays a central role for the company in the total range of around 10 million items. According to Andreas Stuht, Head of E-Commerce Analytics at OTTO, “We firmly believe in a data-driven approach to developing and optimising our touchpoints ― both the otto.de website and our mobile apps.”

Looking for the added value of product data

With Adobe, Andreas Stuht and his team of data specialists go far beyond what normal analytics tools offer for the use of website data on entry and exit, referrer or dwell time. With Adobe Customer Journey Analytics, OTTO is able to include product metadata in its analyses. "By linking both data worlds in Customer Journey Analytics, we can find out what added value our product data offers," says Andreas Stuht. "We use this data to advise our customers on how to find the best product for them."

OTTO not only measures the classic data, but also analyses the interaction of potential customers with the product data over a longer period of time. For example, the company can analyse data to determine the ideal length for product descriptions, how many and which images facilitate a sales process and how OTTO can offer its customers the best possible environment for a mutually successful shopping experience.

It is easy for OTTO to implement the findings itself with modifications such as changes to product text or pictures. The procedure is similar for the partners, but here the operator naturally limits itself to recommendations.

With Customer Journey Analytics, OTTO accomplishes up to 40 optimisation cycles

Nevertheless, optimising the offers is also a complex process at OTTO; The company has around 40 cross-functional, agile product teams that take care of around 40 different ― and sometimes quite granular ― optimisation cycles. For example, optimisations might include improving landing pages, choosing colours for products or designing wish lists. Only in the end does an overall picture emerge from this and ideally the big picture shows satisfied customers.

"The combination of Query Service, Data Science Workspace and Customer Journey Analytics enables us to carry out powerful analysis and to do all the steps in one place," says Stuht when talking about the work of his analysis teams and product managers. With his team of 30 analysts and relevant departments, a total of more than 300 employees have access to the extensive and integrated data analyses. "For us, this is the great potential of Customer Journey Analytics, which has already proven itself in several use cases," he says.

Advantage flexibility

When asked what prompted OTTO to switch from Adobe Analytics to Customer Journey Analytics from the same company, Stuht answered with just one word: "flexibility". The system not only integrates more data sources, but also defines more variables for analysis and assigns more possible values to these variables. It is precisely the combination of the additional variables and data sources that allows completely different and valuable analysis. "This gives us the opportunity to model our own data models, use them to analyse data and thus optimise sales processes," he says.

Today there are practically no limits at OTTO when using data. "Many of the restrictions of the old system have been removed and all of this helps us to work in a much more integrated way," says Stuht. The bottom line is that his analysis team and the product managers also contribute to increasing sales through data-driven optimisations and insights. "We see uplifts wherever we use customer journey analytics and the platform has now become an indispensable part of our product development,” he says. “Good and helpful product information is the key to a good overall experience.”