Why Do You Think I’m a Woman?

At least once a week I receive an email from a very prominent retailer notifying me about a new collection of high-heeled shoes, sales on little black dresses or the latest in summer maxi-dresses. Over the years I have bought men’s shoes, blue jeans, a suit and many dress shirts from the retailer. I have never bought anything there for my wife, nor do I even know what a maxi-dress is.

When the email contains men’s items, I frequently click on the links. When I go to the Website, the featured content is always for women, yet I know they know who I am, because they welcome me back.

So why do they think I am a woman?

I’m likely receiving offers for little black dresses in email and when I go to the website for two reasons. This retailer is not doing any audience segmentation at all, or the retailer is basing their segmentation on faulty demographic information and not using behavior information.

Content marketing, email marketing and marketing automation programs fail for a few primary reasons:

  • Technichal and delivery mistakes
  • The story isn’t compelling enough
  • The message,  offer and CTA aren’t appropriate for the recipient

To judge appropriateness, companies, just need to look at the behavioral data, based on past interactions, is this person likely to click, engage, or share?  When and why?

The retailer should note that I am only clicking on and even purchasing men’s items. They should be able to match their online marketing to my in-store behavior.  I know they can connect the two, because they email me my receipt.


  1. You’re making the assumption only women buy women’s clothes. I’m not going to judge you but maybe they’ve just got a really advanced algorithm that determined men with your taste also buy other things? (Come on, you had to expect someone to give you crap with a headline like that.)

    1. you’d think they would at least target my size . . . or know that I don’t do open toed . . . even in the summer.

  2. There is also an assumption that all of the data needed to provide that type of experience is 1) available across all the different groups involved in enabling that experience 2) allowed to be shared between all of the players (retailer, credit card, ad server) to the extent you need for this to happen and 3) analysis to take all these data points and make it actionable in a timely manner (latency)

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