6 Steps to Take To Improve Customer Retention
The cost of acquiring a new customer is, in most industries, higher than that of retaining a customer. Depending on which study you choose, it can be anywhere from five to twenty-five times more expensive than retaining an existing customer.
I believe that, even after such a brief introduction to the topic, it stands to reason why customer retention strategies have become an integral component of success, for small business right up to large-scale enterprise, for a wide range of different industries. These companies are continuously attempting to improve their retention efforts in order to keep as many customers as possible and stay ahead of the competition.
How to calculate customer retention rate
The definition of what customer retention rate (CRR) is, is the percentage of customers who remain customers after a given period. There is a very simple formula that can be used to precisely calculate how many customers you manage to successfully retain within a given time period. Here it is:
[(E-N)/S] x 100 = CRR
• E represents the number of all your customers at the end of the period (e.g., December 31, 2021, if you are measuring retention rate per year).
• N represents the number of new customers that you acquired during the given period (new customers acquired during the selected period need to be subtracted in order not to skew your results).
• S represents the number of all your customers at the start of the period (e.g., January 1, 2021).
• CRR is your customer retention rate.
Statistics for the average retention rate differ greatly among industries. What is considered a high retention rate for one industry can be considered a low rate for another. Hence, it is sensible to look at the average retention rate in your industry so that you instantly understand how successful your retention strategies are compared to the benchmark.
How Simplity approaches retention rate projects
Although, so far, we have been discussing a single percentage as a representation of the retention rate, improving this number can be a difficult process. At Simplity we approach retention rate projects thoroughly and we know from experience that in order to achieve the best results we need to follow at least the following six steps.
1. Customer matching
First of all, we need to make sure we have full control over the customer data and we need to conduct a customer matching process in order to get a single customer profile. Such a process can differ from client to client. In examples such as an e-commerce business we usually need to match customer actions conducted through various channels (e.g., on the website, in email, or via a phone call) to the one customer who conducted all these actions. Or, in the case of a bank, which recently acquired another financial entity, we need to match customers who had products in both companies.
Customer matching is useful for enriching the customer data, which is helpful in the next steps.
2. Assessing customer lifetime value
We need to understand the value your customers bring to your business in order to understand which customers are worth retaining and how much money can be invested in their retention, while the outcome remains profitable.
There are two ways how this can be approached. Firstly, we can use your historical customer data (mostly transactional) based on which you can sort your customers from most to least valuable. Unfortunately, this approach does not tell you anything about future customer lifetime value (CLTV). Therefore, a second, better method is to leverage a machine learning algorithm to predict the value your customers will bring to you throughout their lifetime. This way, you sort your customers in a more informed way. Then, based on your marketing budget, you can easily specify a cutoff point to understand which customers are still in scope for retention.
3. Predict propensity for churn
Because all high-value customers will not stick around forever, it is ideal to leverage another predictive algorithm, which will calculate your customers’ propensity for churn. As the name suggests, the algorithm predicts a customer’s likelihood of leaving you. It can classify your company’s customers, but on very different rules to the above.
4. Customer segmentation
When you combine the previously mentioned predictive algorithms you will get plenty of customer information and data to be able to segment your customers. The number of segments that can be created depends on the number of customers, quality and quantity of data, and the difficulty and length of retention tests you will want to conduct. In order to keep it simple, let us consider dividing the customer base into four quadrants.
5. Improving customer retention
Quadrant 1 (high propensity for churn & low CLTV) – represents customers who will most likely leave your company. Since their CLTV is low, they have the lowest priority for retention activities.
Quadrant 2 (low propensity for churn & low CLTV) – represents customers who will largely not want to leave your company. Therefore, retention campaigns might not be needed. Nevertheless, the CLTV of these customers is low so it might be useful to try to improve their CLTV through different kinds of campaigns.
Quadrant 3 (high propensity for churn & high CLTV) – represents the most valuable customers but with a high chance of leaving your company. You have the highest chance of increasing profits by retaining this segment.
Quadrant 4 (low propensity for churn & high CLTV) – this segment contains some of your best-performing customers who will also likely not churn from your company. Although the priority for retention campaigns in this segment is low, you should pay close attention to this segment’s shopping experience and react to any potential issues. Despite this segment usually being the smallest one it generates most of the revenue.
6. Test & learn
At this stage we already know which customers a company should try to retain. Nevertheless, we will rarely know right away which actions will work and which will not. This is where continual experimentation plays a role, and the process is called “test & learn”. Some of the things that can be tested are conveying a message through different channels, use of incentives (and their value), frequency of sending marketing messages, etc. We can suggest industry-specific recommendations during an initial consultation.
Impact on profit
I hope your company has already started experimenting with a retention strategy since a mere 5% increase in customer retention can produce more than a 25% increase in profit (source: Fred Reichheld of Bain & Company [PDF]). In case you have not started, or you come across some data-related problems, feel free to get in touch and I’m sure we can help you define your tactics and improve your retention rate.
You can also watch our on-demand webinar How to Improve Customer Retention covering the topics mentioned in this blog post. Watch the webinar