Marketing literature on customer retention acknowledges the fact the best strategy to grow your customer base is not to lose any customers. But what is the best retention strategy? Here are a few examples of the data-driven approach:
Segmenting your customers
One of the keys to a successful retention strategy is segmenting your customer base. Creating different customer segments will help you understand your customers who make use of your product but have different needs and behaviours. The main purpose of segmentation is to summarise a lot of information about customer groups that share some similarities which then can be used for tailored strategies.
There are many ways to segment your customer base. Here is an example of fictional gym profiles:
Segmentation can help you to identify the most valuable customers of your company and find out what they need most. This is important because these customers are naturally the highest priority for your retention campaigns. The most important criteria for segments are:
they should make sense
they should be relevant to the business
they should be targetable and statistically different from each other.
Creating these segments can be done using internal data which is already available or data collected through market research of your customers.
Once you have segmented your customer base the next step is to create a churn model to identify potential churn candidates. The benefit of creating a churn model is that it helps to differentiate between customers with a high churn probability versus customers with a low churn probability. That results in a better allocation of scarce resources for customer retention.
These are the steps in developing a churn prediction model:
Data sources: Collection of all data about customers from different sources
Join & merge: Joining all datasets into a single source
Data preparation: Recoding, aggregating, collapsing variables & outlier handling
Dimension reduction & sampling: Removing variables with high correlation and low variance
Partitioning & model training: Partitioning of the data into test set vs validation set & training of different classification models
Model selection & deployment: Comparison of varying model predictions & selection and implementation of winning model on the total customer base
Retention strategy per segment
After having built the customer base and the churn model, it is time to combine the result of both analyses with the customer value to identify customers that would need to be included in a retention campaign.
Here is an example of the calculation, where the cutoff point is ≥ 20.00 €. This cutoff point is arbitrary and might be increased or decreased depending on expected costs and revenue of a retention campaign. In the below overview all of the findings from the previous sections are combined: segment sizes, segment values, a proportion of customers to be contacted for retention campaign and potential recommended retention strategies for each segment.
The retention strategy should be mainly focused on customers with high churn probability and high value for the company in each segment. As we can see already the number of customers to be included in the retention campaign might vary for each segment.
A customised retention strategy per segment has a couple of benefits such as:
The customer can be offered a tailor-made offer which is more relevant than a generic message
The Effectiveness of different retention strategies can be easily measured
The possibility to allocate resources to high value segments or high value consumers within a segment
Increase the overall retention rate
Developing a segment-specific retention strategy has more benefits than a non-tailored retention strategy for the total customer base. Starting with a segmentation and followed by a churn model companies can decrease the churn rate of their total customer base.
Crystalloids helps companies improve their customer experiences and build marketing technology. Founded in 2006 in the Netherlands, Crystalloids builds crystal-clear solutions that turn customer data into information and knowledge into wisdom. As a leading Google Cloud Partner, Crystalloids combines experience in software development, data science, and marketing, making them one of a kind IT company. Using the Agile approach Crystalloids ensures that use cases show immediate value to their clients and frees their time to focus on decision making and less on programming.
Established in 2006, our goal is to streamline the business experience by emphasising informed decision-making. We design ready-to-use data applications and custom-crafted solutions that offer your company a competitive advantage.