Multinational automotive manufacturer improves customer retention with churn analysis and machine learning in Azure

Unveiling a complex industry challenge

The company is a multinational commercial car manufacturer. Their customer demographic is diverse. To efficiently target their marketing, they needed a deeper insight into their costumer base.

SoftwareOne recommended a customer churn analysis solution to identify customers who are less likely to switch to a competitor. This allows the client to focus their strategy where it’s needed, increasing customer retention while saving money.

To increase customer retention, SoftwareOne needed to implement a solution that would provide the following insights:

• Analysis and monitoring of customer satisfaction and loyalty.
• Monitoring the number of customer departures and detecting trends.
• Examining customer behavior patterns, like what actions precede customer attrition.
• Defining customer segments and determining which ones are at the highest risk of leaving.
• Using machine learning models to calculate the probability of a particular customer leaving.
• Analysing customer revenue and taking into account various dimensions such as time, geography, product models, etc.
• Researching and understanding customer purchasing patterns.

Enabling a retention strategy with custom analytics

SoftwareOne created a customised analytics system using technologies including Microsoft R Open, Apache Hadoop, and Tableau.

SoftwareOne’s consultants first analysed the data for its application and validity to forecast customer migration. SoftwareOne then built machine learning and Tableau models. The models have been tested and one best suited to define customer expectations has been selected.

In addition, SoftwareOne implemented clustering algorithms to segment customers based on various parameters. Tableau was used to visualise the resulting information.