Being attentive to your customer segmentation is essential.
Why? Because it allows you to do two things:
Understand how your online store is structured in terms of customer renewals and the kind of orders you're receiving: this allows you to better target your audience by building lists that are adapted.
It helps you understand what are your best customers' profiles, as well as which products they're the most interested in - and which products make them loyal. This will allow you to discover new growth opportunities for your e-commerce store.
There are many tools available to enable you to perform this type of customer segmentation, and these are segmentations that we perform every day at la hutte.
If you have Shopify store, the customer segmentation tool that is already built-in within Shopify allows you to - perhaps in a basic way, but in any case reliable - to make an initial segmentation that will certainly be useful!
To illustrate Shopify's ability to segment your customer base, we will now gt closrtowards a RFM segmentation, using tools that are freely available and free of charge. Get closer, because the analysis will not be complete (it requires a reworking of the Shopify data by Excel), but we will have all the data to perform it!
Carrying out an RFM segmentation on your customer base means analyzing your customer base according to three parameters:
Most of this data is already included in Shopify - the only problem is that the tool doesn't obviously make this data available for use. That's what we're going to do today, without having to use any additional tools.
It's as simple as that.
Go to the Shopify administration interface and click on Customers in the left menu.
Here you have the whole list of all your customers, in the sense of Shopify - i.e. these people may (or may not) have placed an order but they all left their e-mail address on your online store (newsletter, abandoned shopping cart - or creation of a member account!).
By using the search bar and adding filters, we will be able to use the different data that Shopify already has on your customer base, and thus start working on this segmentation.
By default, Shopify already sets up in your administration interface the most useful segments you can use (the first ones in the screenshot that follows) :
"New" are the people who have not yet placed any order (so, newsletter, account creation, abandoned shopping carts, etc.). The criterion is Orders = 0 :
"Returning" are people with more than one order on their counter - including those who have ordered at least twice (these are the people we are most interested in) :
"Abandoned Checkouts" are people who had an abandoned basket during the last month:
By clicking on "More Filters" you can display the entire list of filters that you can use in the Shopify segmentation tool:
For several purposes (reminders, requests for product reviews, identification of profiles, etc.), it is interesting to identify the most recent customers of your online store.
To do this, the filter we will use is "Order date", and insert the dates we are most interested in. How to identify the most relevant period? First of all, it is a matter of using common sense, and using the average consumption period of your products (one month, two, three, etc.).
On your Shopify administration and in the basic reports available to you, you have access to your rate of orders from "returning" customers - those who have placed more than one order.
To identify them precisely, we will use the "Number of orders" and "Order date" criteria, in order to be able to identify the people who have 1/ ordered during a given period and who have 2/ more than one order (or two/three orders, depending on the particularities of your company and the dates chosen). They are your most loyal customers.
Not only are they loyal to you, but they are also active: they are the customers you should take the most care of.
Please note: by using this segment, and then comparing it with the list of "Returning" people who have more than one order to their credit, you have the possibility to identify, on the contrary, people who have ordered more than once on your store, but who have not placed an order in the current period.
Why is this important? Because these are usually customers with a high loyalty potential - and who had started to be loyal - but stopped, for one reason or another.
This segment, of "ex-loyalty" customers who are no longer active, should be one of your priorities in terms of reviving them, to try to reactivate them and make them active again.
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