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ShowroomPrive uses Predictive Analytics to Anticipate and Reduce Churn
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ShowroomPrive uses Predictive Analytics to Anticipate and Reduce Churn

ShowroomPrive uses Predictive Analytics to Anticipate and Reduce Churn
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ShowroomPrive uses Predictive Analytics to Anticipate and Reduce Churn : Data Science Studio (DSS), developed by Dataiku has been adopted by Showroomprive.com one of the leading ecommerce websites in Europe, to develop and analyze its internal data to prevent churn and maximize the customer retention rates of its nearly 20 million members across Europe. In an ultra-competitive environment, optimizing retention rates is a major issue for commercial sites. Showroomprive.com soon realized the limitations of a generic marketing strategy to address their retention rate based on static rules common to all customers. To improve customer loyalty, it is fundamental to disseminate "the right message to the right customer." Simple in appearance, this solution presupposes the establishment of preliminary identification rules for potential "churners" (customers may not renew their purchases), and determine the value of each individual client. For Showroomprive.com, the challenge of customer loyalty rests largely on the value of this data, enabling it to support its customers in a more personalized manner.

Dataiku technology allows Showroomprive.com to detect customers who no longer make purchases on the site, depending on the frequency of individual purchases, and refine the precision targeting of marketing campaigns

With Data Science Studio, Showroomprive.com has established an effective tool which is complete and easy to use, allowing it to internalize the development of a predictive analytics application. Their solution, developed with DSS, automates the detection of customers who have a high probability of no longer purchasing products on the site. With Dataiku technology, the marketing and business intelligence teams at Showroomprive.com have mastered their anticipatory attrition project in full.

Showroomprive.com uses DSS for automating the integration and enhancement of a wide variety of data sources (customer data, order data and delivery, web logs ...). To create more than 690 features derived from this data and according to specific variables (clicks on sales, orders, litigation, customer ...).To test several machine learning algorithms to achieve the best predictive model.

Damien Garzilli, Strategy and Business Intelligence Manager at Showroomprive.com comments: "From the data import to the development of a predictive algorithm, DSS ease of use has allowed us to gain autonomy throughout the entire process. Today we are able to predict the future actions of our customers and act accordingly. It is also a tool that will allow us to speed up the production of other ‘big data’ use cases as our needs emerge."

Since the commissioning of the application developed with DSS, Showroomprive.com can now detect potential ‘churners’ with 77% accuracy, an AUC of 0.819, which in turn initiates targeted marketing actions.

The success of this first project on DSS has allowed the emergence of many other innovation data-driven initiatives with DSS and open has opened new perspectives for Showroomprive.com.

Damien Garzilli states: "The objective of churn prevention is to send the right message to the right person, we are more than satisfied with the results we get through DSS. Today, Dataiku allows us to talk about the data.. the past to project ourselves into the future. "

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