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Connected AI: Using Customer Behavior To Predict And Improve Retention

Jan 27, 2025 - forbes.com
The article discusses the importance of using AI and machine learning to better understand and respond to customer needs, emphasizing a three-pronged approach: listening to customers, competitors' customers, and team members. It highlights the limitations of current AI approaches that process siloed data types and introduces the concept of Connected AI, which integrates generative AI and ML outputs to provide real-time insights from various data sources. This approach can improve service, complaint handling, and churn prediction by linking customer feedback and behavioral data, ultimately enhancing customer retention and acquisition.

Additionally, the article stresses the need for employees to actively engage with AI-driven strategies to achieve company goals. It suggests that employees should lead, own, and update these strategies, ensuring that AI solutions are flexible and configurable. Companies should focus on integrating employee KPIs into AI strategies to measure effectiveness and encourage feedback. The article concludes by urging organizations to prepare for the evolving AI landscape by prioritizing customer and employee needs, rather than getting bogged down in core system tasks.

Key takeaways:

  • Connected AI can bridge data silos by integrating generative AI and machine learning outputs to better serve customers.
  • Listening to customer and competitor feedback through AI can enhance service improvements, complaint handling, and churn prediction.
  • Linking customer feedback to churn predictions can improve retention and acquisition strategies.
  • Employees should be empowered to lead and update AI-driven strategies, acting as humans-in-the-loop to optimize AI solutions.
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