Technology
Jason Grow for Al Jazeera America
Editor's Note: This is the first installment of The Decoder, a column that's part of the Living with Data series exploring how our online data is tracked, collected and used. Do you have questions about how your personal data is being used? Curious to learn more about your daily encounters with algorithms? Email The Decoder at thedecoder@aljazeera.net or submit your question via the form here. Screen shots and links are helpful clues!
“I already own those socks. What are they doing on my Facebook page?” That’s when it hit her. “Oh, my God. I’m being stalked by socks on the Internet!”
Maybe you’ve noticed ads following you around too. Sometimes it’s a favorite clothing brand, other times that pair of perfect trendy shoes you covet but can’t yet bring ourselves to buy. For The Decoder recently, it was a certain ring and a dress. For Ebba Hierta, it was those socks:
Last fall I became seriously creeped out when I was stalked by a pair of socks. I’d looked at them at an online retailer, and then they followed me all over the Internet, even after I bought a pair from L.L. Bean. And not just ads from the retailer I looked at. The same socks from other retailers also popped up. And different socks too — new socks that I had not found in my own search for the ideal pair of cotton ragg footwear. I tried to outwit my pursuers and occasionally looked at an item online that I had no real interest in, things like a crossbow and camo clothes from Cabelas. Or motorcycle equipment from a Harley shop. Sure enough, these things began stalking me too. The whole thing is unsettling. What’s going on? And why don’t these companies respect that I’ve already bought the socks?
— Ebba Hierta, Martha’s Vineyard, Massachusetts
Hierta, a library director, considers herself a “fairly tech-sophisticated person.” Her instincts for testing the system were great, but in the end she didn’t get very far. She lamented, “If I knew better how it works, I could try to stop it and better protect myself.” She wanted to learn more about what was going on behind these ads, but she didn’t know where to look. She came to me, The Decoder, to help her out.
What all of us — myself included — see when we get that creepy stalker feeling are retargeted advertisements. Retargeted ads are designed to capture the attention of the browser-window shoppers of the Internet. While we continue our research around the Web, they are tailored to direct us back to just the right pair of socks.
To start decoding, I opened up a few sites like Facebook and The New York Times and saw not one but two prime examples of my own retargeted ads.
One appeared in at least four places (The New York Times, Facebook, Bustle, MyFitnessPal), and then I lost track. It was for Ringly, the Bluetooth-connected cocktail ring that vibrates to alert the wearer of important incoming calls. The onslaught might be overkill, but as reminders, these ads are pretty effective. I’m still thinking about the ring (in Dive Bar). As AdRoll puts it, this might just convert me from a window shopper into a buyer.
But the other ad I encountered was for a product I had already bought, just as Hierta had her socks. Two sizes of this Hired Ed dress are in a Modcloth cardboard box next to my desk, waiting to be tried on. Like Hierta, I’m annoyed that this dress competes for my attention in my news feed against videos of friends’ babies unwittingly twerking.
Clicking on the ad (something I rarely do) takes me to the ModCloth link:
http://www.modcloth.com/shop/dresses/hired-ed-dress?utm_sku=114497&utm_campaign=remkt-ALL&utm_medium=remkt&utm_source=tellapart
You can learn a lot by looking at URLs. After “hired-ed-dress,” there’s a lot of extra stuff that tells ModCloth how I got the link. At the very end we see the source: TellApart.
TellApart advertising technology company that specializes in retargeting. Its website describes the strategy: “There are many reasons why the overwhelming majority of your site visitors do not complete a purchase ... TellApart delivers highly personalized display ads that are perfectly targeted with the intent of re-engaging those lapsed shoppers.”
TellApart also happens to be behind the ads you keep seeing for that hip pair of Warby Parkers you’ve been eyeing. TellApart promises, “Our personalized approach ... predict[s] the items each customer will find most delightful and curate[s] experiences that help them discover those products. Done well, these perfect messages result in ‘wow’ moments for shoppers.” But when they are not so perfectly executed, these ads make me think, “Wow, those glasses are watching me like a Dr. T.J. Eckleberg billboard.”
Understanding how these ads work might make us a little less creeped out. So how do TellApart and other retargeting advertisers “unlock the power of customer data?”
If you are a website owner — like L.L. Bean, Ringly or Modcloth — ad tech companies like TellApart provide a few lines of code for your website. Whenever someone visits your site, the code drops a browser cookie that will mark you anonymously as someone who has visited this site. After that, whenever you load Facebook or any other website with ads, the advertising networks will look at the cookies on your computer using the information about which websites you’ve visited to choose which ad to display.
Search Engine Journal advises would-be marketers to “put a frequency cap on your retargeting campaign to make sure they aren’t seeing your ad too often or too little.” They also describe burning, a programmable way to call off these ads once an individual has converted — adspeak for buying the product.
So when Hierta keeps seeing those ragg socks she already bought, it’s likely because there is a disconnect between her data and how it’s being used. That could mean the marketer or their agency isn’t setting the campaign parameters to account for her conversion.
If these ads annoy you, your best line of defense is to install ad blocking software in your browser. You can also shop using incognito or private browsing mode. (Just remember to quit your browser when you are done.) And you can adjust your browser preferences for accepting cookies from websites. You might even consider quitting online shopping altogether. For Hierta, who lives on an island with limited shopping opportunities, that’s not a practical option.
But these strategies risk keeping us in the dark about the effects of Big Data in our lives. Ads seem innocuous, and many of us have started to ignore them. But these ads might be one of the clearest signals we have about where our data flows and how it might be used in other contexts. Hierta worries about this approach, writing, “Somewhere all of my Web browsing is still being recorded ... Then it just means I don’t see it.”
Hierta would have missed an important opportunity if she had been ad-blocking. “Those socks were the first big aha moment that I had about the way I’m being recorded by every click I make. Those clicks are showing up in somebody’s database and showing back up in my life.”
There are more constructive ways to respond, but they take a little effort on your part. Many of these companies like Facebook and Google offer the opportunity to describe your preferences on settings pages, but they are sometimes hard to find. I’ll explore more about what these personal profiles reveal and what they still obscure in a future installment of Living With Data.
Decoding takes a little effort, but next time I encourage you to ask “Why am I seeing this?” and take a closer look.
This series starts with you. Share your personal stories, your questions and your encounters with data.
Do you have screen captures of weird ads or algorithmic flukes? What were you doing, what caught your attention, and what’s your best guess for what’s going on? For example, what sites were you visiting just before the strange ad showed up? Submit with your name (you’ll be anonymous if you prefer), email address and phone number so I can follow up with you for details.
For inspiration, future columns might cover anything from puzzlingly personalized junk snail mail to ad campaigns that are based on your predicted breakup, predatory loan targeting and Uber passenger ratings. Anywhere there’s data, there’s something to be decoded!
Editor's Note: This is the first installment of The Decoder, part of the Living with Data series exploring how our online data is tracked, collected and used. Do you have questions about how your personal data is being used? Curious to learn more about your daily encounters with algorithms? Email The Decoder at thedecoder@aljazeera.net or submit your question via the form here. Screen shots and links are helpful clues!
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