An automotive dealer, one of the largest in Belgium, sought to gain customer insights from manually entered data, which existed in different formats and across different systems.
The focus of the project was to use existing data to improve communication with customers, in order to predict customer needs and reduce churn.
The project consisted of data collection and cleaning, data anonymization, data modeling (churn prediction), and data visualization. Moreover, the project included a review of the client’s cloud architecture, developing options for data storage and archiving, and API integration of databases. Klarrio delivered a model that leverages “cleaner” existing data augmented with a new type of information, working with 1.7 billion data points, thus ensuring targeted analysis and insights.
The Technology behind
- Machine Learning
- Apache Spark
”“Things work out best for those who make the best of how things work out.”— John Wooden
Data Cleaning | Significant cleaning of manual data entries in a variety of formats.
Single Source | Integrated data from disparate sources into a single high-quality data set.
Modeling | Insight from models based on the business rules.
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