Churn rate (sometimes called attrition rate), in its broadest sense, is a measure of the number of individuals or items moving out of a collective over a specific period of time. It is one of two primary factors that determine the steady-state level of customers a business will support. The term is used in many contexts, but is most widely applied in business with respect to a contractual customer base. For instance, it is an important factor for any business with a subscriber-based service model, including mobile telephone networks and pay TV operators. The term is also used to refer to participant turnover in peer-to-peer networks. Churn rate is an important input into customer lifetime value modeling, and can be part of a simulator used to measure Return on Marketing Investment using Marketing Mix Modeling.
The phrase is based on the English verb churn, meaning "to agitate or produce violent motion".
Churn Rate of a Customer Base
Churn rate, when applied to a customer base, refers to the proportion of contractual customers or subscribers who leave a supplier during a given time period. It is a possible indicator of customer dissatisfaction, cheaper and/or better offers from the competition, more successful sales and/or marketing by the competition, or reasons having to do with the customer life cycle.
Churn is closely related to the concept of average customer life time. For example, a churn rate of 25% implies an average customer life of 4 years. An annual churn rate of 33% implies an average customer life of 3 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.), or through retention activities such as loyalty programs. It is possible to overstate the churn rate, as when a consumer drops the service but then restarts it within the same year. Thus, a clear distinction needs to be made between 'gross churn', the total number of absolute disconnections, and 'net churn', the overall loss of subscribers or members. The difference between the two measures is the number of new subscribers or members that have joined during the same period. 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.
When talking about individual subscribers or customers, sometimes the expression "survival rate" is used to mean 1 minus the churn rate. For example, for a group of subscribers, an annual churn rate of 25% is the same as an annual survival rate of 75%. Both imply a customer life time of 4 years. I.e.: a customer life time can be calculated as the inverse of that's customer's predicted churn rate. For a group or segment of customers, their customer life (or tenure) is the inverse of their aggregate churn rate. Gompertz distribution models of distribution of customer life times can therefore also predict a distribution of churn rates.
If a company (such as a cable TV company) has a fast growing customer base, confusion can arise between the math associated with what percentage of the whole customer base churns in a given year (what percentage of the base of subscribers in all of 2010 churned out?) versus what the churn rate is for a given cohort of customers (e.g.: taking those customers who subscribed in given month, such as January 2010, how many had churned out by January 2011?). Looking at the churn rate for a fast-growing aggregate customer base will understate the true churn rate compared to cohort based approach to the calculation. The cohort based approach will also allow you to calculate the survival rate and the average customer life, whereas the aggregate approach can not calculate these two metrics.
The term 'Rotational churn' is used to describe the phenomenon where a customer churns and immediately rejoins. This is common in prepaid mobile phone services, where existing customers may take up a new subscription from their current provider in order to avail of special offers only available to new customers.
In some business contexts, churn rate could also refer to employee turnover within a company. For instance, most fast food restaurants have a routinely high churn rate among employees. For larger companies, such as Fortune 500 companies, the attrition rate tends to be much lower compared to a Fast Food franchise. The company size and industry also play a key role in attrition rate. An “acceptable” attrition rate for a given company is relative to its industry. It would not likely be useful to compare the attrition of Fast Food employees with a Fortune 500 company in a corporate setting. Regardless of industry or company size, attrition rate tends to be highest among the lowest paying jobs, and lowest for the highest paying jobs.
Attrition Rate has always played a role in how cash flow is affected for employee payroll. For example, if a company has 10,000 employees, and needs to save money on payroll, it may be wise to simply institute a temporary “hiring freeze” knowing that some people will leave the company through natural attrition, thus saving employee payroll by not replacing or hiring new employees. It could be expected that if the average employee makes $40,000 per year, and the company has 10,000 employees, a natural attrition rate could be between 1% and 5% depending on the size and industry of the company.[according to whom?] A rate of 5% or more for a larger company most often indicates layoffs in addition to natural attrition, early retirement, and firing.[according to whom?]
Employee moves/attrition rate
Churn rate can also describe the number of employees that move within a certain period. For example, the annual churn rate would be the total number of moves completed in a 12-month period divided by the average number of occupants during the same 12-month period.
Monthly and quarterly churn rates can also be calculated.
Attrition rate (%) = (Number of employees resigned during the month / Average number of employees during the month) x 100 where Average number of employees during the month = (Total number of employees at the start of the month + Total number of employees at the end of the month) / 2
- Berry and Linoff, Michael J.A. and Gordon S. (2000). Mastering Data Mining: The Art and Science of Customer Relationship Management. John Wiley & Sons. ISBN 0-471-33123-6.
- Insight paper on churn in the mobile communications industry - click on the link under "Market Studies" on the right side.
- 3 Steps to Building Customer Churn-risk Scores