How to reduce churn with AI?

AI can help you retain more customers and preserve at-risk revenue

The goal was clear: every 1% reduction in attrition could help Johnson Controls retain $35M in revenues.

It wasn’t just about building machine learning models. The real challenge was starting from zero to build models and drive outcomes with those models.”

Miller speaks about how to reduce churn Terry Miller
Global Advanced Analytics
Johnson Controls

With this case study, learn how to reduce churn:

  • Aligning stakeholders enables you to clearly define the problem to solve using AI/ML.

  • An AI development process helps you create and deploy custom machine learning models.

  • Focusing on business outcomes enables you to engage with customers that are likely to leave or cancel their contract.

Download the case study

Johnson Controls is using AI to reduce churn and identify over $100M a year of protectable revenue

Is your company struggling with how to reduce churn?

Johnson Controls is a leader in smart buildings

Johnson Controls International (JCI), founded in 1885, is an industry leader in fire, security, and HVAC technology and services for buildings.

For decades, they have experienced significant growth in their recurring service contract businesses. The company is also an innovator in smart building technologies, including AI-infused solutions such as remote diagnostics, predictive maintenance, compliance monitoring, advanced risk assessments and more.

While Johnson Controls has been successful at using AI to deliver actionable insights for their industrial solutions, they recognized an additional opportunity: Could they use AI and machine learning (ML) to reduce customer attrition in their Global Services business?

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