For example cloud software providers can use predictive analytics to predict which customer may not renew the cloud subscription based on a number of factors. They can combine user access information, support tickets, time to resolve support tickets and similar information to associate a risk value to every customer and determine whether a customer needs additional attention or not.
Most cloud software providers have account managers who are focused on ensuring good service for customers and whose performance is measured by customer renewal rates. In a company with thousands of customers, the account managers may have limited time and resources and may like to focus on customers who are not happy with the current service. They may also want to avoid annoying customers who are happy and do not want to be bothered with unnecessary meeting or phone calls.
Identifying a set of customers who might not renew the subscription and proactively reaching out to help them and ensure renewal will save a cloud service provider a significant amount of support cost, sales cost and avoid loss of revenue.
Similar models can and are being used to predict employees who are at risk of leaving the company, employees who are at risk of hospitalization among other things. Investment in a bit of prediction technology and expertise can save a huge amount of money for most organizations.