How to reduce churn with AI?
AI can help you predict customer churn 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.”
Global Advanced Analytics
Johnson Controls
With this case study, learn how to reduce churn:
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Johnson Controls is using AI to predict customer 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?

WE HAVE 25+ YEARS EXPERIENCE IN AI/ML DEVELOPMENT AND CAN DEMONSTRATE HOW TO REDUCE CHURN
