The problem we see with most brands is that they take an “everything to everyone” approach to retention marketing, which means they try to appeal to all their customers with the same generic campaigns and messages, rather than tailoring their marketing efforts to specific customer segments. We find that this approach leads to poor engagement and low retention rates, as folks aren’t likely to respond to messages that aren’t tailored to their interests. And thus, we see the importance of segmentation!
Segmentation: Understanding Who Your Different Customers Are
The problem we see with most brands is that they take an “everything to everyone” approach to retention marketing, which means they try to appeal to all their customers with the same generic campaigns and messages, rather than tailoring their marketing efforts to specific customer segments. We find that this approach leads to poor engagement and low retention rates, as folks aren’t likely to respond to messages that aren’t tailored to their interests.
Thus… we see the importance of segmentation!
How to segment your customer base: demographics, behavior, psychographics, etc.
The easiest way to start to segment customers is to use a “separate the best from the rest” approach - with your “best” customers getting targeted with upsell opportunities, like premium products, exclusive deals, or loyalty rewards. On the other hand, everyone that falls into "the rest" can get offers that are more price-conscious, such as discounts, free shipping, or limited-time promotions. This can help to drive sales and engagement among lower-value customers, who may be more sensitive to price and less interested in premium products or loyalty programs.
How to use customer data to identify key segments
The “best” way to segment your customers is to use Cotera, but I promised my co-founder when we started writing our blog that we would stay away from shilling our own product, so I digress. The simplest approach is to separate them by how often they purchase - your “best” customers are probably in the top 20% of buyers. I asked Chat-GPT to easily write out how to find the threshold in excel for the top 20% of customers, given this table:
Table of Top Customers and Their Most Recent Purchases
Select the data range and click on "Insert" -> "PivotTable".
In the "Create PivotTable" dialog box, select "New Worksheet" and click "OK".
In the pivot table field list, drag the "Email" column to the "Rows" area and the "Timestamp" column to the "Values" area.
In the "Values" area, Excel should automatically summarize the data by counting the number of orders for each customer. If it doesn't, click on the dropdown arrow next to the "Timestamp" field and choose "Value Field Settings". Then, choose "Count" as the summary function.
Use the PERCENTILE function to find the 80th percentile. You can use a formula like this: =PERCENTILE(B:B,0.8) assuming that the order counts are in column B.
Round up the 80th percentile value to the nearest integer, since you need a whole number of orders for the threshold.
Woah! It works!
By this calculation, any customer that has made 3 purchases in the last year is in the 80th percentile of customers.
You can easily use this data to create different customer segments in your marketing automation tool - anyone with three or more customers will be classified into “Champion Customers” while everyone else can fall into “regular customers”.
Understanding What Drives Your Customers
The importance of understanding what motivates your customers
It can be an immediate level up if you deeply understand your customer base. This can mean understand which path they took to purchase, which products are likely to drive repeat orders, which channels they prefer to use to engage with your brand, and what factors drive their decision-making.
At Cotera, we call this process “lever finding” - looking at the differences between customers that match our “Champion” bucket, and those that do not. This can involve:
Which campaign they used to find us
Which product they initially purchased
The order value of their first order
and so on..
Imagine you have two customers:
In a vacuum Joel and Jane are just two customers, but let’s say that you start to look into more, and you see a pattern - customers who are more likely to be in the “Champion” bucket (3+ orders) tend to order Product X more often in their first order, while customers who purchase Product Y tend to fall into “worse” segments.
Knowing this vital info has suddenly given you a “lever” that you can choose to pull to get more customers into the “Champion” category - customers who haven’t interacted with your brand in and haven’t purchased Product X might get an email with a discount code, while you may try to tailor your advertising to encourage more folks in your acquisition funnel to try product X.
Personalization: Creating Custom Campaigns to Drive Engagement
The benefits of personalized campaigns for customer retention
The last bit of the puzzle is personalization - you not only understand who your customers are (segmentation) and what drives them (levers and understanding), but now it’s time to ensure that you’re serving them the right content at the right time (personalization).
These days, AI is everywhere. I used Chat GPT to write out a simple way to calculate percentiles in this very article, just above. It can also help you serve the right products for your repeat customers to purchase. You can use a recommendation engine to suggest products based on their past purchase history or browsing behavior.
For example, let's say you’re an outdoor supply company like REI, and you have a customer who has purchased several pairs of running shoes from your website. An AI-powered recommendation engine could analyze this customer's purchase history and browsing behavior, and identify that they are likely interested in other running-related products, such as running shorts or hydration gear. By suggesting these products to the customer, you are providing a more personalized and relevant shopping experience, which can help increase their loyalty to your brand.
We’ve even see companies use AI in their abandoned cart emails - identifying the items that are in someone’s cart and giving them more items that they can purchase can ensure that you’re maximizing the value that you’re getting from a customer at the time of sale.
Applications
So, now that you know what steps it takes to build an effective retention strategy, let’s walk through how you might apply that to your own business. Like we said before, the key to setting up a strong foundation for successfully retaining customers is understanding your customers in a deeper way. Lucky for you, platforms exist that help you do exactly that but without the hassle — and Cotera is one of those very tools.
All the things that make it complicated for you to segment your customers and personalize marketing strategies accordingly are what we aim to take care of. It may feel easy enough to make these distinctions in the beginning, but the hardest part is keeping up with the way segments and preferences change over time.
Retention strategies are not meant to be static, but keeping track of any changes and making constant iterations is not an easy task — at least not on your own. You’ll sometimes find that as you continue to analyze the effectiveness of your retention strategies, what worked a month ago may no longer work now. Customers are constantly changing, and the only way to keep track of these changes is to monitor your data. Our goal is not only to do the segmenting and personalizing for you, but to also ensure you don’t miss a single change or instrumental insight along the way. Only then can you always be in touch with and provide personalized value to every one of your customers — and to finally stop stressing about churn.
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