Insights & Customer Behaviour Intelligence - Use Case - DigitalRoute

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Insights & Customer Behaviour Intelligence

World Leading Cross-Platform Online Fashion Store

This e-commerce company operates a cross-platform online fashion store. Founded in 2008, the company has grown to encompass 14,000 employees, operating in 15 countries across Europe.


The company had successfully expanded over the past decade but was still relying on all homegrown infrastructure for billing and front-end systems.

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

To maintain its leading market position, company leaders wanted to collect in-depth intelligence

and insights from digital customer behavior and buying patterns. 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.

The previous homegrown front-end systems couldn’t collect and bind these types of insights to each customer—nor could they provide intelligence, insights and billing from business generated through third-party portals.


Today, the company uses the DigitalRoute Usage Data Platform. They can now maintain a holistic view of customer purchase patterns, both at their own online store, as well as customer behavior through third-party portals. With the new Usage Data Platform, 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.


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 behavior 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.

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