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Target Customers Based on Gender With Our Segmentation Filters

Both Shopify and SMSBump filters offer you many and great ways to create very narrow target groups and to send only relevant offers. 

 

Yet there was a feature missing - since Shopify is not recording any data on the gender of your customers, there were only workarounds that could help with determining this - such as the types of products those people had bought. 

 

Well this is about to change! 

 

We’ve developed our proprietary algorithm which analyzes the characteristics of your customers and can confirm with over 90% certainty that a client is either male or female.

 

How to set it up?

The first thing that you need to do is to navigate to the Lists & Segments section in the menu. Once you are there go on and create a new segment

 

 

 

Set the Type to be a Segment and then give your segment a name. Select a name that is going to be straightforward, so when you select it in your text marketing campaign you would know right away whom you will be sending those messages to.

 

 

In this case I will be creating a segment targeting just the women who are my customers so I called this segment “Female Customers”.

 

 

Once you are done just click Create and you will receive a popup informing you that your segment is saved. 

 

 

Now it's time to set up the filters. The filter you are going to need is called Contacts gender and you can find it in the Customer attributes section

 

 

In our case I wanted to create a segment just with female customers, so i will select Female, but feel free to select any gender you need. 

 

Just like the rest of the filters, you can pair this one with additional ones via the Add filter button to create a very narrow target audience. 

 

Once you are done with your segmentation filters, simply click on Update Rules and you are done! 

 

 

Once the segment is created, it gets automatically populated with all your customers that fit the selected criteria. 

 

 

 

We’ve tested our algorithm against some very international stores and so far it has proven that it successfully predicts the gender of the customer in over 90% of the cases. Just like in this case - even by the name we can be pretty sure that Kate is most probably a woman :) 

 

 

 

Yes, it was that easy to set up a gender-applied filter to your segments. 

 

Let us know if there are other customer characteristics you would like to target, so we can bug our devs until they develop them! 


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