How to create the best retention strategy

by Mustafa Bozkurt, on Nov 2, 2018 3:51:29 PM

How to create the best retention strategy

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:

The best retention strategy

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.

Churn model

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 best retention strategy

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.

The best retention strategy

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.
Topics:Data Analytics

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