Churn rate

Last updated

Churn rate (sometimes called attrition rate) is a measure of the proportion of individuals or items moving out of a group over a specific period. It is one of two primary factors that determine the steady-state level of customers a business will support.[ clarification needed ]

Contents

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. The term is often synonymous with turnover, for example participant turnover in peer-to-peer networks. Churn rate is an input into customer lifetime value modeling, and can be part of a simulator used to measure return on marketing investment using marketing mix modeling. [1] The term comes from the image of agitation of cream in a butter churn.

Customer base churn

Churn rate, when applied to a customer base, is the proportion of contractual customers or subscribers who leave a supplier during a given period. It may indicate 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 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.), 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 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 percent is the same as an annual survival rate of 75 percent. Both imply a customer lifetime of four years. I.e., a customer lifetime can be calculated as the inverse of that 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.

For companies with a fast-growing customer base (e.g., digital media companies in a BCG-matrix problem child or star phase), 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.

Researchers at Deloitte have argued that social network analysis is a good tool to calculate churn. [2]

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. [3]

The phrase "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 most circumstances churn is seen as indicating that customers are dissatisfied with a service. However, in some industries whose services delivers on a promise, churn is considered as a positive signal, such as the health care services, weight loss services and online dating platforms. [4]

Some researchers have disputed the simple assumption that just dissatisfaction would lead customers to churn, and called for a more nuanced approach. [5]

See also

Related Research Articles

The subscription business model is a business model in which a customer must pay a recurring price at regular intervals for access to a product or service. The model was pioneered by publishers of books and periodicals in the 17th century, and is now used by many businesses, websites and even pharmaceutical companies in partnership with the government.

RFM is a method used for analyzing customer value and segmenting customers which is commonly used in database marketing and direct marketing. It has received particular attention in the retail and professional services industries.

In marketing, customer lifetime value, lifetime customer value (LCV), or life-time value (LTV) is a prognostication of the net profit contributed to the whole future relationship with a customer. The prediction model can have varying levels of sophistication and accuracy, ranging from a crude heuristic to the use of complex predictive analytics techniques.

A service-level agreement (SLA) is an agreement between a service provider and a customer. Particular aspects of the service – quality, availability, responsibilities – are agreed between the service provider and the service user. The most common component of an SLA is that the services should be provided to the customer as agreed upon in the contract. As an example, Internet service providers and telcos will commonly include service level agreements within the terms of their contracts with customers to define the level(s) of service being sold in plain language terms. In this case, the SLA will typically have a technical definition of mean time between failures (MTBF), mean time to repair or mean time to recovery (MTTR); identifying which party is responsible for reporting faults or paying fees; responsibility for various data rates; throughput; jitter; or similar measurable details.

Average revenue per user (ARPU), sometimes known as average revenue per unit, is a measure used primarily by consumer communications, digital media, and networking companies, defined as the total revenue divided by the number of subscribers.

Broadly, retention rate is a statistical measurement of the number of people that remain involved with some kind of entity, such as a company or research group.

Relationship marketing is a form of marketing developed from direct response marketing campaigns that emphasizes customer retention and satisfaction rather than sales transactions. It differentiates from other forms of marketing in that it recognises the long-term value of customer relationships and extends communication beyond intrusive advertising and sales promotional messages. With the growth of the Internet and mobile platforms, relationship marketing has continued to evolve as technology opens more collaborative and social communication channels such as tools for managing relationships with customers that go beyond demographics and customer service data collection. Relationship marketing extends to include inbound marketing, a combination of search optimization and strategic content, public relations, social media and application development.

<span class="mw-page-title-main">Performance indicator</span> Measurement that evaluates the success of an organization

A performance indicator or key performance indicator (KPI) is a type of performance measurement. KPIs evaluate the success of an organization or of a particular activity in which it engages. KPIs provide a focus for strategic and operational improvement, create an analytical basis for decision making and help focus attention on what matters most.

Turnover or turn over may refer to:

Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.

In economics, valuation using multiples, or "relative valuation", is a process that consists of:

In human resources, turnover is the act of replacing an employee with a new employee. Partings between organizations and employees may consist of termination, retirement, death, interagency transfers, and resignations. An organization’s turnover is measured as a percentage rate, which is referred to as its turnover rate. Turnover rate is the percentage of employees in a workforce that leave during a certain period of time. Organizations and industries as a whole measure their turnover rate during a fiscal or calendar year.

Customer attrition, also known as customer churn, customer turnover, or customer defection, is the loss of clients or customers.

Production is the process of combining various inputs, both material and immaterial in order to create output. Ideally this output will be a good or service which has value and contributes to the utility of individuals. The area of economics that focuses on production is called production theory, and it is closely related to the consumption theory of economics.

Customer retention refers to the ability of a company or product to retain its customers over some specified period. High customer retention means customers of the product or business tend to return to, continue to buy or in some other way not defect to another product or business, or to non-use entirely. Selling organizations generally attempt to reduce customer defections. Customer retention starts with the first contact an organization has with a customer and continues throughout the entire lifetime of a relationship and successful retention efforts take this entire lifecycle into account. A company's ability to attract and retain new customers is related not only to its product or services, but also to the way it services its existing customers, the value the customers actually perceive as a result of utilizing the solutions, and the reputation it creates within and across the marketplace.

Uplift modelling, also known as incremental modelling, true lift modelling, or net modelling is a predictive modelling technique that directly models the incremental impact of a treatment on an individual's behaviour.

Employee retention is the ability of an organization to retain its employees and ensure sustainability. Employee retention can be represented by a simple statistic. Employee retention is also the strategies employers use to try to retain the employees in their workforce.

Optimove is a privately held company that develops and markets a Relationship Marketing software as a service (SaaS). Optimove's product has a Customer Data Platform at its core and applies algorithmic optimization to autonomously improve multichannel campaigns. The company serves various industries, including retail, eCommerce, travel and hospitality, gaming, and financial services.

<span class="mw-page-title-main">IFRS 17</span>

IFRS 17 is an International Financial Reporting Standard that was issued by the International Accounting Standards Board in May 2017. It will replace IFRS 4 on accounting for insurance contracts and has an effective date of 1 January 2023. The original effective date was meant to be 1 January 2021. In November 2018 the International Accounting Standards Board proposed to delay the effective date by one year to 1 January 2022. In March 2020, the International Accounting Standards Board further deferred the effective date to 1 January 2023.

The UVA method is an accounting and decision-making tool, based on calculating the cost of sales. Unlike management accounting, which calculates product margins, the UVA method calculates the result generated by each sale. The UVA method relies on a very detailed analysis of all costs related to products, customers, orders, and deliveries. It introduces the notion of a single measure unit, which applies to all the operations in the company. The method relies on an equivalent-based approach.

References

  1. "Customer Churn Rate: Definition, Measuring Churn and Increasing Revenue". ReSci. 2014-10-30. Retrieved 2017-06-08.
  2. "Customer Retention | Applied Analytics". Deloitte Czech Republic. Retrieved 2021-03-07.
  3. Lalwani, Praveen; Mishra, Manas Kumar; Chadha, Jasroop Singh; Sethi, Pratyush (2021-02-14). "Customer churn prediction system: a machine learning approach". Computing. 104 (2): 271–294. doi:10.1007/s00607-021-00908-y. ISSN   1436-5057. S2CID   233947001.
  4. Dechant, Andrea; Spann, Martin; Becker, Jan U. (27 August 2018). "Positive Customer Churn". Journal of Service Research: 109467051879505. doi: 10.1177/1094670518795054 .
  5. "The Power of Category-Level Churn Analysis". ciValue. 2020-07-27. Retrieved 2021-03-07.

Further reading