Churn rate, in its broadest sense, is a measure of the number of individuals or items moving
out of a collective group 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".
Definition 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, an annual 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, 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 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. For companies with a fast-growing customer
base, confusion can arise between the statistical analyses 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 a particular customer cohort's churn rate. For
example: Taking those customers who subscribed in given month, say January 2010 – How
many had churned out by January 2011? Examining churn for a fast-growing aggregated 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. Calculate your own churn in a Churn calculation tool
Employee turnover 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. A rate of 5% or more for a
larger company most often indicates layoffs in addition to natural attrition, early retirement,
and firing. 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.
Formula: Attrition rate = x 100 where Average number
of employees during the month = / 2. See also
Customer attrition References
Further reading Berry and Linoff, Michael J.A. and Gordon
S.. 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