On this episode of Data Bites I present one of the most famous cases of ethics violations in the data profession. We discuss the problem of Hyper Personalization and how predictive analytics and segmentation can cause serious dilemmas for anyone going down this path professionally.
The case is the prediction of pregnant customers by Target. We would love to hear your thoughts about this historical case in the comment section below!
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Music for the show: Foolish Game / God Don’t Work On Commission by spinmeister (c) copyright 2014 Licensed under a Creative Commons Attribution (3.0) license. http://dig.ccmixter.org/files/spinmeister/46822 Ft: Snowflake
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Now, onto the show.
Welcome to data tour. I’m your host Jordan. And on today’s data bytes, we’re rounding out the week on analytics and data science. Now we’re going to do that with one of my favorite all time problems and ethics for data science. And you ought to stay tuned for what that is exactly. But before we get on to that, this whole week, I’ve been on a campaign to make sure that data couture becomes the podcast of the month over a podcast land. In order to vote for the show, head on over to data tour.org forward slash podcast land. Again that is dedicated tour.org forward slash podcast land, I really appreciate your help with this. Now for the state of bites, what is my favorite all time ethical dilemma? Well, for those of you who know me, you’ve probably heard me say this on countless times. But it is the problem of predicting pregnancy.
And so as you know, in predictive analytics, we have the capability to really know our customers know our customers buying habits. And sometimes those buying habits reveal something very personal about our customers. In this case, I’m talking about being pregnant. And depending on where you shop, if you shop at certain retailers, you’re able to know whether or not or least the company is able to know whether or not you’re pregnant, how do they do this? Well, they have lots of data, they can train up their models to know that certain customers certain segments of the population, namely, in this case, those that are pregnant, tend to have certain buying habits right up before maybe they know that they’re pregnant while they’re pregnant. And after they’re pregnant.
The business case for predicting and segmenting customers in this sort of way, is pretty straightforward. If you can get a customer before they’re born, they’re going to be a customer for life. Right? This is how cigarette companies that are for so long marketing, to the youth because thing, hook them when they’re young, they could keep them hooked the rest of their life. Well, you guys probably know that target did this very same thing in the early 2000s, they were very interested to be able to segment their customers in such a way that they can know, in their buying habits, whether or not they’re likely to be certain segments of the population. And one of those segments were the people who are pregnant or trying to get pregnant, currently have children that kind of thing. beyond simply wanting to get a customer for life, they also wanted to be very capable at spending their marketing dollars wisely.
Why would you market to somebody who’s probably going to buy a lot of diapers? Are the various other pieces that go along with pregnancy or early childhood rearing and education. Why would you market to that person for I don’t know men’s outdoor where it doesn’t make sense, right? In the past, marketing was kind of a scattershot, it was just let’s throw everything at everybody and hope we hit the right people. Somehow, that’s a huge waste of money for any marketing departments budget. So by employing this particular predictive algorithm and their marketing efforts, this company, in this case was target target was able to literally target those members, those segments of their customer base and hit them with the right marketing at the right time.
Now, this might sound great to you, they know me, they, they they know what I want, they know which deals I’m after. Well, here comes the ethical dilemma right around the corner. They got so good. This algorithm was so precise and so accurate after they worked on over time, that it could predict if somebody was about to be pregnant, or was attempting to be pregnant. And this became a problem very famously, when an ad came to a person’s house, and it happened to be a family and the family’s father got this ad from Target. And it was all about how Oh, you’re expecting a child. Congratulations. Here are all the deals we have for the various things you’re going to need while you’re pregnant, after you’re pregnant after you have the child, and so on. Well, the problem is one of the members of that household who did happen to be pregnant was under age. Now, you are probably not surprised to hear that the father was pistes also surprised the daughter was extraordinarily embarrassed, and so on. The ethical dilemma here is what right do we have to our own privacy? Whether that be day to day? Do I have privacy from anybody else around me? Or in the companies we choose to do business? How much privacy Are we allowed to expect? Of course, companies didn’t stop doing this sort of segmentation, they didn’t start predicting, or they didn’t stop predicting customer behavior in order to market to them effectively.
As a matter of fact, target kind of dialed back the pen point accuracy of the algorithm, as well as instead of directly sending Oh, here’s some marketing materials specifically for pregnancy. They happen to kind of hide it, among other things in the ads that they’re sending to people. So they’re still doing that, but in a much, much less creepy way. So I don’t know if they succeeded and doing the ethically correct thing. Because at the end of the day, this sort of marketing is commonplace, right? We’ve just become accustomed to it. However, I am curious what you guys think? Do you think it’s too creepy to have predictive algorithms that knows this? Well know our buying habits so well that they can predict things that we don’t even know were the case yet, like in the case of this under age woman who didn’t know she was pregnant yet, but targeted.
I’d love to hear your thoughts, your comments, your feelings about how this pervades our life and what we can do about it and some ethically sound way. Talk to you next time.
That’s it for the show. Thank you for listening. And if you liked what you’ve heard, consider leaving a comment or like down below. Stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. consider becoming a firstname.lastname@example.org forward slash data couture music for the podcast. It’s called foolish game. God don’t work on commission by the artist spinmeister us under a Creative Commons Attribution 3.0 license, writing, editing and production of the podcast is by your host Jordan Bohall.