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Case Study

How an Online Retailer Transformed Itself With Holistic and Correlated Data

European on-line fashion business with millions of users. Leveraging e-commerce expertise to constantly optimise processes and platform. Strives for leadership in fashion, technology, marketing and logistics.

This e-commerce company operates a cross-platform online fashion store, offering a broad assortment of fashion for men, women and children. Founded in 2008, the company has since grown to encompass 17,000 employees, with millions of active users, across 25 European markets.

By constantly optimising its processes and platform offerings, using its e-commerce expertise the company had become Europe's leading online fashion retailer in only a few years.

Its goal is to create the world’s best online fashion experience. The core of its business are what the company focuses on, always striving to be cutting-edge in fashion, technology, marketing, and logistics.

Challenge

The company had successfully expanded over the past decade but was still relying on all homegrown infrastructure for billing and front-end systems. These systems couldn’t collect and bind platform usage insights to each customer—nor could they provide intelligence, insights and billing from business generated through third-party portals.

Company leaders recognized that, if they were going to keep up with competition, maintain and grow market share and develop innovative new business models, they needed a more modern and effective IT infrastructure.

They wanted to collect in-depth intelligence and insights from digital customer behaviour and buying patterns. Using this, they wanted to understand the buying process in detail, both when customers make a decision to buy, but just as important, when they don’t finalize the purchase.

Challenges in short:

Current front-end systems couldn’t collect and bind insights to each customer.

Wanted to collect intelligence from digital customer behavior and buying patterns.

Needed a more modern and effective IT infrastructure.

Solution

The company has primarily been selling their products via their own Mobile Apps and Web shop. Moving forward it has the ambition to act more like Amazon i.e. selling via channels.

The company now uses the DigitalRoute Usage Engine to maintain a holistic view of customer purchase patterns, both at their own online store, as well as customer behaviour through third-party portals.

With the Usage Engine, the company can also combine insights from the same customer regardless of whether the customer uses the website or mobile app. Additionally, the company can now validate credit cards, as well as provision new customers in the CRM, via the DigitalRoute Usage Data Platform’s Entitlement Gateway Application.

Outcome

The company can now maintain a comprehensive picture of digital customer behaviour and buying patterns.

With deeper insights and intelligence, they can now develop more effective promotional campaigns precisely targeting customers based on past behaviour and preferences.

Deeper cross-platform customer intelligence also allows the company to conduct more accurate predictive forecasting.
For example, they can now detect when a garment is selling quickly and proactively re-order it—before they disappoint customers or lose sales.

Outcome in short:

Comprehensive understanding of customer behaviour.

Develop more effective promotional campaigns precisely targeting customers based on behavior.

Accurate predictive forecasting and pro-active ordering.

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