Measuring customer retention takes a lot of data to make insights tangible for action in your marketing efforts. First and foremost you must have good data capture. Then you can use some basic equations to really start to calculate your retention rate and work to create a predictive model to fight it.
Capturing information about your customers involves a detailed measurement system. This should combine both digital and manual processes of data collection, but to even begin measuring retention you need to be able to define when a customer interacts with your product, service, or brand, and most importantly when they leave. The definition of leave is going to be different for everyone depending on your business. There is a challenge in this measurement if you are a service-based company that might experience months between customer interactions. You might experience “silent attrition”, where they leave but you have no way of knowing since it is not part of your business to talk to them frequently. And they surely won’t call you to tell you they have moved on! For others, if you are reaching out to your client base with any type of client communication, there should be a way to get some data to help you understand the activity of your customer with your business. This includes the record of every email, tweet, link, click, and phone call made to that client. Every measurement you can gather will help you understand your client’s behavior and assist in analysis.
The hardest part of this all the data collection comes in determining attrition. Without a direct tie to a status, like a service subscription or membership, it might feel like drawing a line in the sand when it comes to defining customer attrition. The only way to truly bring relevance into the situation is with data. You might experience months between customer purchases, but you won’t know that unless you can really see patterns or have historical data to back it up. Without data points you can not determine interaction with marketing, referrals, or other triggers that might indicate a customer is just not at the point of service yet, but engaged with your brand. The bottom line is though, if you don’t have enough data, the attrition point moves up and becomes shorter. If you have no interaction points after a sale or consultation, you can consider them gone the next day. We’ll explore this in more detail in another post soon.
Moving on, once you have a collection of data you should be able to calculate churn or attrition from a simple equation as follows:
How to Define Your Customer Retention Rate
This measurement should be done on a daily basis to understand how each day plays into your overall rate. There are too many factors when it comes to leaving that can throw off the measurement if you look at it on a larger scale. At a daily level we can see volatility that can lead to more insights as well. Once you have this daily data, you might have to make some adjustments to see an average across the month and quarter but never leaving the daily measurement as a baseline.
Importance of Segmentation
It’s very important to consider a segmentation of your data to further include retention rates from various groups of your customers. Traditionally new customers have a higher drop-off rate than customers that have been around for, lets say, 90 days or so. That benchmark depends on your business and transaction frequency.
What it Will Mean
Tracking the retention rate is a great measurement, but unless you can understand what it means to your business, it won’t have a real value. Ideally you can tie a per-customer cost to your rate, and understand what it means to loose a customer in something more understandable.
It Will Never Be Zero
The goal of retention rate is to understand your turnover and monitor its performance over time. The goal is not to be at 0, but to be at a place that is supporting your goals for growth.
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