Did you know that U.S. companies could save over $35 billion annually by satisfying existing customers? Understanding why customers want to leave can help you retain them and reduce acquisition costs. But, how do you identify customers at risk of leaving? You could guess based on their activity, but that would be ineffective. Instead, you need to leverage churn prediction to learn why customers may leave and what you can do about it.<\/p>\n\n\n\n
Churn prediction detects which customers are likely to discontinue business with you. This churn could occur as a canceled subscription or product abandonment. There are several types of churn you can predict, including:<\/p>\n\n\n\n
Predicting churn in any form is key to customer retention<\/a> and satisfaction. It is important for businesses because:<\/p>\n\n\n\n A good example of the importance of reducing customer churn comes from nib New Zealand. Through its partnership with Pearl-Plaza, nib rolled out a closed-loop feedback process to improve the customer experience. Pearl-Plaza\u2019s churn propensity modeling was crucial to identifying and retaining customers showing signs of dissatisfaction. As a result, nib improved its NPS and reduced churn by 6% within six months of rolling out the program. To learn more, download the full story below!<\/p>\n\n\n\n\n