SoftwareOne case study

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

A woman working on a car in a factory.

Acquiring a new customer is much more expensive than retaining one. Discover how SoftwareOne created a customised analytics system that provides higher quality and more relevant services, enabling a leading automotive manufacturer to reduce marketing costs and increase customer retention.

Customer attrition or churn is one of the most important challenges faced by modern enterprises. The problem aspects a growing number of industries. As the competition grows, so do customer expectations.

Wanting better product quality at a lower price is just one example of a case where a customer may choose one company’s offering over that of another. Gaining insights into customer satisfaction and risk factors helps to align the strategy with customer expectations and to reduce customer churn.

Automotive manufacturer
Automotive, Manufacturing
Azure Cloud
Application Services: Data and Analytics

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.

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Transforming insights into action

Data visualisations enable the client to see trends in a friendly format. End-users can now easily view reports and quickly scan them for signs of customer attrition. The reports also include features like drill-down analysis and trend forecasting. This helps our client to identify segments on which to focus their marketing strategy on.

New insights enable the client to provide higher quality and more relevant services, and thus, save on marketing costs, increase customer retention, and reduce churn.

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