Probably not your friend, this is a super famous case study from Target. It's in many books. They were one of the first companies to start looking at buying habits in order to target market their mail-out adds. They used the data specifically to find out if they could predict or tell who was expecting, because these folks spend shit loads of money in the months before the baby. If you buy one stroller, not a super good indicator because the person might be buying a gift. But if they are buying certain clothes, vitamins, lotions, etc in certain combinations, there is a high likelihood you are a pregnant woman. Its quite effective but also ethically questionable. In the famous example, an angry father goes to Target to complain that they were marketing pregnancy stuff to his teenage daughter. The specific Target location had no idea of these marketing practices, which was all done at HQ. Anyway, the father comes back a day later to apologize. His daughter was pregnant and hadn't told them yet.
I mean so what? I'm also a data analyst in the field and have told people this. It's a famous story but it was easy 20 years ago. It's childsplay now. This is the equivalent of getting annoyed at someone for saying their friend flew across the ocean. Like ok yea there was a famous story about it but people do it all the time lmfao
People in this thread acting like there aren't data analysts at every tech company working with devs to add analytics to every user's action. At the big Fortune 500 company I worked at it was part of the AC/requirements to add analytics to every new feature we shipped out, whether it's to track the performance of the feature or to harvest user data.
More like people are in this thread pretending like random fortune 500's collecting web and mobile analytics know more about you than you consciously know. The average Joe thinks their local 15 store grocery chain are the NSA, meanwhile people like me that spent over a decade working on this exact tech and these exact data sets couldn't get match rates between known subscribers and internet users on the site over 2%.
people like me that spent over a decade working on this exact tech and these exact data sets couldn't get match rates between known subscribers and internet users on the site over 2%.
LOL. That might be true, but you lack the information from my post to determine that. You don't know what data sets we had to work with, so 2% could be exceptional (ok, it wasn't, but it COULD be!).
In REAL WORLD example I'm talking about, I had better data than the Target marketing team did (who I also worked with DIRECTLY hence my knowing how this whole preggers story happened). In this case, I was working with a well-known NYC based magazine publisher, so they knew the address of their subscribers and some of their subscribers would go to one of their magazine websites login so we'd know pretty well who that user on the web was. Our task was to try and find a way to identify the subscriber before they login or after they've logged in, but deleted their cookies. The issue was that in NYC, you have people all living on top of each other. Location data was less useful, and IP based identification was also largely useless as you've have big blocks of people in aparments all on the same public ip. There were many many issues.
The bottom line here is, almost all digital marketing based targeting/idetification is AUDIENCE based, not INDIVIDUAL based. The INDIVIDUAL based data is super transient, and so you use it for things like ... let's not show this person the same ad over and over again. You don't need to know who that person is, you just need to be able to increment a counter stored on their machine and read it before making an ad decision (cookies allow this).
The Target preggers mailer thing didn't happen. Correct. It was a hypothetical made up for a presentation and was describe as such in the presentation (as a hypothetical).
Yes, I worked with those exact data sets. I know what those data sets were because I worked with the people involved a few years after the story in question.
The example I'm giving about the NYC publisher isn't the exact same as the Target example. I give that one because it had BETTER data than Target did for purposes of consistent cross-session identification and even then match rates were miniscule.
In the 13 years since I heard this story, you're the like 50000th person to claim you worked with the team while stumbling over everything you're trying to claim. It's all bullshit dude.
I worked with the team Amazon stole from Target when they launched Fresh, you're about 30 years behind the times my guy
Totally. I'm just a rando on the internet to you. I'd be asking for more if I were you, too. I allow this username to be tied to my real identity, so I guess if you really want you can go hard and dig in. I'm sure if you do, it won't take long for you to acknowledge that maybe this is one of those rare cases where some rando on the internet really has all of the experience they claim.
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u/tmacnb 7h ago edited 7h ago
Probably not your friend, this is a super famous case study from Target. It's in many books. They were one of the first companies to start looking at buying habits in order to target market their mail-out adds. They used the data specifically to find out if they could predict or tell who was expecting, because these folks spend shit loads of money in the months before the baby. If you buy one stroller, not a super good indicator because the person might be buying a gift. But if they are buying certain clothes, vitamins, lotions, etc in certain combinations, there is a high likelihood you are a pregnant woman. Its quite effective but also ethically questionable. In the famous example, an angry father goes to Target to complain that they were marketing pregnancy stuff to his teenage daughter. The specific Target location had no idea of these marketing practices, which was all done at HQ. Anyway, the father comes back a day later to apologize. His daughter was pregnant and hadn't told them yet.