Churn
Donnell Simon
It's important to pay attention to customer acquisition costs. If most customers churn before you have made back the money spent on acquiring that customer, then your customer acquisition costs are too high for your business model.
Churn rate in business refers to the number of customers or subscribers that leave a provider in a given time period. This is the opposite of growth rate, which shows the number of new subscribers or customers in that time frame. Churn rate can also refer to the number of employees that leave a firm in a given period.
Ideally, a churn rate of zero would be the best churn rate, as that would indicate a business is not losing any subscribers; however, that is never the reality. A business will always lose subscribers for one reason or another.
In this case, it is important to compare the churn rate of the business to its industry's average churn rate, taking into consideration if the business is new or mature. Knowing an industry's churn rate versus that of the business is the only way to understand if a churn rate is acceptable or poor. Every industry has a different business model and, therefore, will have different acceptable churn rates.
A high churn rate indicates that a business is losing significant customers, certainly more than it is bringing in. This would mean that the business is doing something wrong, whether that be delivering a poor product, having poor customer service, or a host of other negative reasons that would explain why it is losing customers fast. A high churn rate would most likely mean a company is suffering significant losses.
To help inform the current policy discussion, this brief provides estimates of churn for people enrolled in Medicaid in 2018. We use 2017 and 2019 as look-back and look-ahead years, respectively, so we can examine what happens to people a full year before and after an enrollment date or disenrollment date in 2018. We also provide estimates of churn by eligibility group and compare rates in Medicaid expansion versus non-expansion states. Overall, we find that 10% of full-benefit enrollees have a gap in coverage of less than a year, and rates are higher for children and adults compared to aged and people with disabilities. Churn rates also vary substantially by state, ranging from 5% or less in some states to 15% or more in others. Churn has implications for access to care as well as administrative costs faced by states. Detail on the data and methods underlying this analysis are in the Methods section at the end of the brief.
Some enrollees may be at higher risk of churn than others. Working individuals whose monthly income fluctuates may be more likely to experience churn in states that have adopted frequent electronic data matches during the year. For example, adult enrollees without disabilities, most of whom are working, may have irregular work hours, overtime, or multiple part-time jobs that can lead to month-to-month changes in income. In contrast, elderly adults and people with disabilities, particularly those who qualify for Supplemental Security Income (SSI), are less likely to experience monthly income changes or other changes in circumstances. Most states conduct data matches on a periodic basis to identify changes in circumstances between annual renewal periods. If the data checks identify changes in income or other factors that affect eligibility and the individual is unable to resolve the discrepancy within the specified timeframe (often limited to within 10 days from the date of the notice), the person can be disenrolled from coverage.
Churn can result in access barriers as well as additional administrative costs. When individuals who remain eligible for coverage are disenrolled, they may experience gaps in coverage that could limit access to care and lead to delays in getting needed care. Research indicates that enrollees who experience fluctuations in coverage are more likely to report difficulties getting medical care and are more likely to end up in the hospital with a preventable condition. In addition, there are administrative costs associated with disenrolling an enrollee and then subsequently processing a new application.
Rates of churn were higher for children and adults compared to aged adults and people with disabilities (Figure 2). We estimate that 11.2% of full-benefit children and 12.1% of adults were disenrolled and then subsequently re-enrolled within one year. Analysis also shows that rates of churn are higher for enrollees with partial benefit packages, but there are similar churn rates across expansion and non-expansion states (Appendix Table 1). However, there is considerable variation in churn rates across states, with 4 states (HI, AZ, DC, and NC) having 5% of enrollees or fewer disenrolling and then re-enrolling within a year, and 4 states (TX, WI, NH, and PA) having 15% of enrollees or more disenrolling and re-enrolling within a year.
The continuous enrollment requirement related to the coronavirus pandemic has all but halted Medicaid churn for the past year and a half, but disenrollments are expected resume once the requirement ends. In part due to the continuous enrollment requirement, Medicaid/CHIP enrollment has increased from February 2020 to May 2021 by 11.5 million (or 16.2%) to 82.8 million individuals. However, when the continuous enrollment requirement ends, states will begin processing renewals and individuals may lose coverage if they are no longer eligible or face barriers during the redetermination process, such as providing required documentation.
The Build Back Better Act (BBBA) that is currently being debated in Congress would phase out the continuous enrollment requirement beginning April 1, 2022. To continue receiving a phased-down enhanced federal match rate, states would be required to follow rules about disenrolling people that could help to reduce rates of churn. For example, states could only disenroll individuals who have been enrolled at least 12 consecutive months and must limit eligibility redeterminations to a set proportion of enrollees each month through September 2022. States could not disenroll individuals based on returned mail unless there were at least two failed attempts to contact the individual through at least two modalities (e.g., mail and text messages). States would also have to report monthly data on call center statistics (average volume, wait times, and abandonment rates) as well as rates of eligibility renewals, redeterminations, and coverage terminations due to changes in circumstances (e.g., increased income) or due to administrative reasons (e.g., failing to provide required documentation).
The BBBA would require states to implement 12-month continuous coverage for children and postpartum individuals. States have the option to provide 12 months of continuous coverage for children. Under this option, states allow a child to remain enrolled for a full year unless the child ages out of coverage, moves out of state, voluntarily withdraws, or does not make premium payments. As such, 12-month continuous eligibility eliminates coverage gaps due to fluctuations in income over the course of the year. A recent MACPAC analysis found that states with 12-month continuous coverage for children had lower rates of churn among children enrolled in Medicaid and CHIP compared to states without this policy. Currently, 34 states provide 12-month continuous eligibility to at least some children in either Medicaid or CHIP. The Build Back Better Act would require states to extend 12-month continuous coverage for children in Medicaid and CHIP and would also require 12-month continuous coverage for postpartum individuals, a change from the current requirement of 60-day postpartum coverage.
I often come across blogs, posts, and comments discussing how to calculate churn, but I haven't found any resources guiding the process of creating a churn report in HubSpot. I'm interested in understanding the intricacies of generating such a report in HubSpot and uncovering any limitations associated with it. To provide context, my current company doesn't currently track churn, and my goal is to establish a comprehensive report enabling the tracking of:
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]
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.
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.
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