One of the biggest challenges of companies across the globe is customer retention. A lot of resources, hard work & planning goes into bringing customers on board & customers’ attrition makes companies do the extra exercise of bringing new customers to fill the void alongside targeted expansion activities. Churn rate analytics is the solution which can prevent this leakage of customer loss

Consider the situation in the picture.The person is trying to fill the bucket, but there are leakages & hence outflow of water. No matter how much effort is put by the person to fill water either by rapidly filling water in high frequency or in large quantities using larger filling containers, the bucket will not get filled completely. Even if by any means man achieves to fill the bucket completely, it will be for seconds since water outflow won't let the filled bucket to be sustainable. Now replace man with company, bucket full with water as target customer base, water inflow be incoming new customers & leakages as consumer attrition, no matter how much effort is put in bringing new customers, customer attrition will never let the company reach its full potential

What is churn rate?

Churn rate is defined as percentage of lost customers or revenue in a certain time period
It is of two types.
Customer Churn Rate=(No. Of customers churned in a period/No. Of customers at the beginning of period)*100
e.g - For the telecommunication industry a customer has many options to switch to other alternatives. Suppose a company has seen 1 out of 20 customers cancelling the subscription to prepaid recharge option & switching to other players last year, then the customer churn rate of the company is 5% per annum.

Revenue Churn rate(also known as MRR churn rate/recurring revenue)=(Revenue churned in a period/Revenue at the beginning of period)*100
Revenue churn rate measures rate at which company loses revenue due to loss of customers or downgraded subscriptions(i.e subscribing to cheaper services/products offerings by the same company)

Importance of churn rate:

It is useful for a company to compare churn rate with other competitors & see their performance in retaining customers compared to other companies in the same industry.It is important for a company to have low churn rate, because high churn rate implies high attrition, hence company with high churn rate needs to spend money to bring new customers on board just to maintain the vacuum created by customers leaving the company. Hence, it is important to understand the churn rate because it impacts profitability & growth for a company.

Customer Churn Categories:

Contractual churn: Scenario in which customers decide not to carry with their expired contracts with companies,i.e not to renew services from existing service providing company.
e.g-A customer may have subscribed to a OTT platform for 3 months, after 3 months the customer may choose not to renew the subscription for instance due to lack of time to use OTT platform, hence it comes under category of contractual churn

Non contractual churn: Cases where customers leave potential purchase without completing the transaction. This is highly likely in e-commerce websites or retail stores.
For example, a customer may put the product in cart & initiate the payment, but at last moment he might not continue with the payment for reasons like low account balance, skepticism about product etc. and this comes under non contractual churn

Voluntary churn: It is the scenario where customers cancel their existing contract with the company.
e.g-A customer who has subscribed for 30 days of internet prepaid services of a company may choose to terminate the contract due to poor network, customer service or other factors. It is the most harmful form of customer churn for any company.

Involuntary churn: This is the case where a customer willing to continue service offering from the company has to discontinue due to failure of payment for faults on the company’s side like server errors, disabling of payment update system etc.
e.g-A customer who has defaulted on his credit card payment may not be able to continue his subscription despite his willingness to continue because he can’t afford to pay. It is the least harmful type of churn for any company.

Importance of understanding churn category

Customer churn types may be different but understanding the type helps to know the underlying reason for churn. Cost of acquisition of a new customer is always higher than the retention cost of an old customer hence, it is important for an organization to understand the underlying cause of churn so that it can work on causes which are under its control to rescue customer attrition.

What is Churn Analytics?

It is a technique to measure customer loss rate, understand if a company/product/service is losing customers & if it is losing, reasons for customers quitting.It also helps pinpoint customer segment as well as timing of their attrition using predictive analysis

Why Churn Analytics?

The graph above shows the difference in total number of customers of companies with different churn rates over a period of time. As we can see a difference of just 2.5% translates into 4 times more customers for the company having lower churn rate. This is snapshot of 80 months data only, extrapolating this over a longer period will create gap exponentially between companies having different churn rates. Hence, it is important to minimise churn rate & churn analytics can help understand underlying causes of churn and will predict in advance the churn of customer helping companies to plan & take action in advance to minimise churn rate.

Benefits of Churn Analytics:

This is the snapshot of one of the dashboards of customer churn. As seen the information provided by it are

Customer status in terms of customer who are active, inactive, lost or new to the company
Churn risk on the basis of income-Risk % of churn of customers on the basis of income can be also easily identified.Company will need to focus only on the specific income groups to prevent churn saving valuable time as well as resources.
Churn risk on the basis of spending as well as time frame-Bottom left part illustrates risk profile of customer churn along with timeline. The segmenting or segregation of customer on the basis of spending groups alongside
Individual customer churn risk %-As seen in the bottom right part for each individual customer churn risk % is mentioned alongside customer details like gender,spending. It can help company identify customers at high churn risk % and if necessary can create customised offering for them

Let’s look at another dashboard to understand the benefits of churn analytics. Summary of insights a company will be getting from this dashboard created from churn analysis & few of the benefits for the company can be summarised as follows