[clarification needed] Churn is widely applied in business for contractual customer bases.
Examples include a subscriber-based service model as used by mobile telephone networks and pay TV operators.
For example, an annual churn rate of 25 percent implies an average customer life of four years.
An annual churn rate of 33 percent implies an average customer life of three years.
The churn rate can be minimized by creating barriers which discourage customers to change suppliers (contractual binding periods, use of proprietary technology, value-added services, unique business models, etc.
Suppliers may find that if they offer a loss-leader "introductory special", it can lead to a higher churn rate and subscriber abuse, as some subscribers will sign on, let the service lapse, then sign on again to take continuous advantage of current specials.
Researchers at Deloitte have argued that social network analysis is a good tool to calculate churn.
[5] In recent years, using AI and machine-learning as a means to calculate customer churn has become increasingly common for large retailers and service providers.
[7] Some researchers have disputed the simple assumption that just dissatisfaction would lead customers to churn, and called for a more nuanced approach.