Social media, streaming television and, to some extent, even second-screening, are a marketers’ dream.
There’s far more data about audiences available through these outlets than there has ever been at any point in the past. This makes it possible to shoot out an ad to single mothers of two making over $30K living in Louisville, Kentucky at 2 pm if you had a particular reason to do that.
But when does the use of data mining cross the line from useful and even creative to super creepy?
Getting ever more personal with advertising
Most digital advertisers know you can get pretty personal when it comes to data gleaned from Facebook or even Google, but what many may not realize is that there are so many other information streams. For example, wearables are kind of a new frontier when it comes to data mining marketing. This goes way beyond simple retargeting marketing.
You could literally sell a pair of high end running shoes to someone whose fitness watch indicated that they’ve taken up long distance running. If someone’s smart home suddenly acquires a lot of security tech, it could indicate where the holes are, and your marketing team could push ads that would fill the gaps.
It’s a blessing and a curse for customers. On one hand, the benefits of data mining advertising can’t be undersold. There is absolutely an argument to be made for the time it saves when an algorithm can pluck the right product out of a giant catalog before the shopper even realizes they need it. There is a load of value in searching for a broad category of items and having the perfect one appear on the first page of results.
However, it’s also difficult to convince some shoppers that the uses of data mining are purely Capitalist in nature. Plenty of them feel like they’re being watched at all times, sometimes even worrying if their microwave and Amazon Echo are conspiring against them at night.
When good data goes bad
The concern of Internet denizens over their privacy isn’t a wholly unfounded one.
After all, companies like Netflix and Spotify have been using (anonymous) consumer data in a recent string of advertisements. For example, Netflix tweeted “To the 53 people who’ve watched A Christmas Prince every day for the past 18 days: Who hurt you?” Spotify ran clever billboards saying things like “2018 Goals. Eat vegan brisket with the person who made a playlist called ‘Leftist Elitist Snowflake BBQ.’”
For someone, those ads were oddly specific. Creeper at the window kind of specific. And that’s a problem for all companies that use data for marketing purposes. At least in the case of the Spotify billboards, permission was obtained from the owners of the playlists mentioned, but people outside of those circles didn’t necessarily know that and may have been left scratching their heads.
Sometimes, it’s ok to keep a few of your secrets under your hat. And when it comes to data and how deeply advertisers can go these days, suspending disbelief is kind of the key. Customers know, of course they do, just how much information they give away on a daily basis. But they don’t want to think about it. They don’t want it thrown up in their faces all the time. Or any of the time, perhaps.
Using consumer data carefully
It’s one thing to accept the Terms of Service blindly and another to be faced with the consequences.
If you attempt a data-based ad campaign like those of Netflix or Spotify, you’ll want to very carefully consider your own audience. The backlash can be severe and swift, especially if your audience thinks you’re making fun of them or being mean instead of simply snarky. There’s a fine line here.
However, all marketers can use data in some capacity, and you should. After all, using data mining for your campaigns is full of benefits, including:
- Increasing understanding of ad performance. Without data, you’re never going to know how your ad is doing. Even if that advertising spot is running on network or cable television, you can get some idea of its performance by measuring the traffic spikes to your website around the time it runs live. So many people second screen while watching television these days that this behavior is a good predictor for advertising effectiveness.
- Gaining audience insights. Along with how well your ad is doing, data mining can help you figure out who your audience is or help you calibrate your ads to attract the audience you really want. Do you want to speak to mid-income nuclear families in the Midwest? How about single females over the age of 55 in Florida? Keep mining that data and making changes to your message until you hit the nail on the head. You’ll get surprisingly fast feedback from smart campaigns
- Calculating ROI. When you know who’s watching and whether or not they’re buying, you can easily calculate the ROI of your ads, no matter where they’re running. This has always been a bit of a bugger, but it’s becoming less of a guess as the data gets more and more precise. Knowing the return on your marketing helps you to better place your ad spend where it’ll generate the biggest impact. Simple as that.
- Big Brother isn’t watching, but Big Data is. Even so, it’s not the worst thing that’s ever happened, as long as advertisers and others who have access to these deep data mines use that information contained therein responsibly. Instead of treating it like a joke and risking turning future customers off entirely, mine that data quietly and slip it in where it counts.