Once upon a time (around 2012), in a far-off land called Minnesota, a very angry man stormed into a Target brandishing a handful of coupons. Target had been mailing the man’s teenaged daughter coupons for things like maternity clothes and cribs, and he was furious—what was Target thinking, mailing a teenage girl things like that? He learned later his daughter was indeed pregnant, and that Target had figured that out by looking at the purchases she had made with her credit card. The end.
The invasiveness and insensitivity demonstrated in the now-infamous Target story makes it a sort of prototypical “Big, Bad Data” cautionary tale for anyone thinking about offering up personal information to a big company.
To many companies, Big Data is a godsend—and that’s how you might have seen it discussed all over the Internet recently, including on this blog. Everything is a data point, and every data point gives us valuable information about who uses our products or services, what they enjoy, what they struggle with, and even which of our competitors they also purchase from. Knowing how to collect and intelligently utilize enormous data sets gives you a leg up in your industry, no matter what industry that is.
But that’s not exactly how individual humans view it, and you, as an individual human, know exactly what I’m talking about.
It’s not just learning from Target that your daughter might be pregnant. It’s realizing that Facebook has amassed mountains of information you didn’t even know you had to give and sold it to the highest bidder. It’s the nagging feeling that your Amazon Alexa is secretly listening to and recording all your conversations. It’s the absolute horror of knowing there’s probably some guy at Google who knows your entire search history.
Facebook, Amazon, and Google might be extreme examples—they are three of the world’s most powerful companies—but they set the stage for how Big Data is viewed by the public in general. Sometimes, using Big Data can feel manipulative, and people don’t like to be manipulated.
But at the same time, how could a company not try the most it possibly could out of Big Data? This is the age of the Digital Transformation we’re living in here: everyone else is using data, and if you want to have a shot against your competitors you’d better hop on board.
It’s a fine line to walk—collecting as much data as you can to further your business while not letting it become a concern for customers—but it is essential to optimizing your customers’ experience. Data comes with a lot of power—and, yes, a lot of responsibility.
Humans are finicky creatures. We want things to be personalized for us, but not too personalized—that makes us uncomfortable. A 2017 survey by YouGov found that around 80 percent of consumers would agree to provide personal data to a company in exchange for a discount on a product or for the sake of convenience and ease of use. At some point, though, things go too far.
It’s like the Uncanny Valley: the more real and human a robot looks, the more we relate to it—but only up to a certain point, after which we start to get creeped out.
So, where’s the line? At what point do things just start to feel too personal? In Global Marketing Alliance’s 2018 panel on data usage and personalization, marketing industry leaders discussed the difficulties of navigating this question.
Some customers will find any personalization to be too much personalization, even something as simple as seeing their first name in the subject line of an email. Other customers will find that sort of thing eye-catching and enticing. It can be tough to satisfy both types of customers, but the panelists generally agreed that customers start disliking personalization when it stops actively advancing the user experience. At that point, it starts to become invasive and annoying.
Netflix, for example, learns to recognize patterns in the shows and movies I watch and is able to offer me new suggestions for what to watch next with moderate accuracy. I like that.
But I also learned recently that Netflix doesn’t just personalize what comes up on my homepage—it even personalizes the thumbnails that I see. Now, it’s not like they’re keeping that a secret: they have a whole post about it on their Tech Blog. And yes, it’s kind of cool that they’re able to do that, but at the same time… it feels a bit much, maybe even a little manipulative, and no enormous improvement to my user experience. For me, it’s crossed that line into Uncanny Valley territory.
So, using data turns out to be like any other aspect of trying to sell a product: it’s all about the customer. If you’re going to ask them to hand over information about their spending habits, their interests, and their personal details, you have to make it worth their time.
Here’s another example: HMI’s own proprietary software, Snap2Claim. Say you run a manufacturing company that uses an incentive program that rewards distributors or contractors in your channel for selling or purchasing your product. You could have them manually input all the information from their invoice, which is time-consuming and tedious. Or they could simply take a picture of the invoice and submit that online through Snap2Claim.
Not only is it easier for them, it gives you valuable information: what the average sell price of your products is, what other products contractors buy, and more. And better yet, what better way to enhance this transaction than rewarding them for it? Your program participants willingly hand over this information to you, trusting that you’ll use it to improve your services for them and not sell it to some malicious third party, while also receiving points or merchandise rewards.
Data insights are powerful tools—to wield them is a gift we must use wisely.
Want to hear more about Snap2Claim and the other services HMI provides? Or just love talking about data and the digital transformation? Drop us a line at 888.220.4780 or book a meeting!