As of last night’s dotMailer update, a new set of segmentation rules are available for users of our Customer Insight Module. These changes make it even easier to create powerful targeted communications based on the recency, frequency and monetary value of your contacts’ engagement with your brand.
New date rules for segmentation
Over the last few dotMailer releases we’ve been enhancing the way you can segment on date rules. We’ve already updated them for contact data fields and for behavioural data, and now this has been extended to data added via our Customer Insight Module.
I won’t go into all the available rules here, but the most requested one added in the recent update was:
Transaction.PurchaseDate occurs within the last [X] days
This is one of 26 ways you can now segment your contacts on based on dates in Customer Insight data.
A full set of rules is available for date fields can be found in our support documentation for segmentation.
Customer Insight; not just for retail data
In case you missed it; our Customer Insight Module is how you store data against a dotMailer contact when you need more than one value stored in the same field; this can be used to store, for example, purchase histories, or for event attendance, or for downloads from a website.
Our Magento connector includes the ability to import contact purchase history into dotMailer automatically without any additional development work.
Creating RFM segments
Below are a few examples of how you can use these new rules to do RFM (recency, frequency, monetary value) segmentation on your email contacts.
To create a segment based on recency of engagement, you might segment to find contacts with at least one interaction in the last X days. For example in the below screenshot I’ve segmented to find all males who’ve made a skincare or haircare purchase in the last 90 days.
To create a segment based on frequencyof engagement, you might segment to find contacts with a set number of engagements within the last X days. For example in the below screenshot I’ve segmented to find all contacts who have made between 3 and 6 purchases from the Boston store in the last 180 days.
To create a segment based on monetary value, you might segment to find contacts who have spent a set amount in a given time period. For example in the below screenshot I’ve segmented to find all contacts who have spent over $200 on purchases; but only including those transactions for which no discounts were applied.
Automating emails based on customer behaviour
Combining these segmentation methods with our automation tools you can now create customer experiences that are even more targeted based on their purchasing habits.
For more information on the updates, head over to patch notes! Later in the month I’ll do a write up on some real-life use cases – keep your eyes peeled!