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Data Driven Customer Management

The Marketing office of an Energy company required assistance in implementing Customer Intelligence and Campaign Management capabilities starting from raw sparse data and unstructured data sources. Softlab worked on data modelling and exploration, churn analysis, reporting and ex-post, and campaign management. Softlab implemented prevention campaigns for high-risk customers and win-back campaigns to address abandoned operations while leveraging analytics. The overall results demonstrated an increased ROI, cost reduction, and Customer Satisfaction success, resulting in a 5.8% increase in RDP and a 7.5% reduction in churn rate.

 

    Process steps

    Approach

    For data modelling and exploration, Softlab built a first version of a Data Lake and implemented data governance policies, leading to 32+ KPIs. The Softlab team built a Churn Analysis to identify high-risk customers and designed corrective strategies to improve the customer life cycle. Softlab reported on the customer base, new activations, deactivations, and campaign results with nine reports and seven ex-post. Finally, Softlab developed campaign management through prevention campaigns for high-risk customers and win-back campaigns through analytics-driven strategies.

    Outcome

    Softlab's support led to an overall results demonstrating an increased ROI, cost reduction, and customer satisfaction success, resulting in a 5.8% increase in RDP and a 7.5% reduction in churn rate. The implementation of prevention campaigns, win-back campaigns, and churn analysis improved the customer life cycle. The reports and ex-post analyses provided insights into the customer base and the results of campaigns.

    Technology

    Softlab's solutions relied on Data Lake and data exploration techniques to build the harmonized data layer fed with 3 different customer bases, implementing data governance policies as well. Additionally, Softlab employed analytics to create churn analysis and develop management campaigns.

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