’Tis the season to be jolly, but if you’re watching, say, the 2019 remake of “The Lion King,” you might experience the phenomenon known as the “uncanny valley,” a feeling of unease or even revulsion when encountering an entity that is almost, but not quite, human.
The phrase, coined in 1970, has been mostly used to describe our response to increasingly realistic androids and digital depictions of humans. Now, armed with technology that harvests every detail of an individual consumer’s behavior, marketers are marching directly into their own version of the uncanny valley, without considering the lessons learned from King Mufasa.
Unease generated by too-close-for-comfort targeting is especially evident in social media. Many Instagram and Facebook users are convinced that the platforms are eavesdropping on their conversations and sending them ads related to a recently uttered word or phrase. Say “comfortable shoe,” and next thing you know, an ad for AllBirds pops up in your feed. Even HBO’s “Silicon Valley” has incorporated the idea of marketers using private chatter for marketing initiatives.
Although experts say they rely on precise targeting algorithms that use location and specific store visits to gauge interest, the eavesdropping belief still holds strong.
Even outside of social, there are limits to just how close a brand can get to a consumer without seeming creepy. We’re all used to emails that address us by name, or ads that re-target our recent product searches. But when marketers reach too deeply into data to personalize, they run the risk of repelling consumers instead of engaging them.
So what are the uncanny valley lessons for brands and marketers?
Understand it. The uncanny valley is real. Awareness is the first step in avoiding it. Getting too close to consumers doesn’t help your brand;
it actually poses a risk by making them uncomfortable.
The difference between manipulation and marketing is that the former attempts to change the perception or behavior of consumers through underhanded or deceptive means. Don’t use such tactics and instead be upfront about your goals. When Amazon recommends a book based on your previous purchases, for instance, it does so by telling you it’s basing the suggestion on that criteria.
Define the line. Determine where the valley lies for you and for the people you are trying to reach. There will be different thresholds of closeness for different brands. A lifestyle brand with an exercise tracker is going to be able to offer health suggestions much more easily than a quick-service
restaurant, for example. A single brand will have different experiences cozying up to consumers depending on which product it’s advertising. Once you’re aware of the valley, figure out how deep and wide it is for your product and determine how close is just right.
If someone buys coffee and your algorithm suggests that such shoppers also purchased a particular brand of creamer, for instance, making that connection is not much different than an in-store sign. If you’re using that person’s purchase history to make an individualized suggestion, then you’re risking making them uncomfortable.
Don’t overdo data. Consumers want personalized messages, but not to the extent they feel their privacy is at stake. Respecting data is key. Lizzie Foo Kune, senior director and analyst at Gartner, aptly points out: “If your marketing and advertising is too personal, and too real, your consumers are going to find it unnerving,” she writes. “As you use more data to personalize communications, you’ll find consumers become increasingly sensitive to their privacy preferences.”
Again, a person’s comfort with such suggestions is personal. It’s better to not make the suggestion if it’s likely to repel them.
Time it right. Once you know how personal to get, you also need to know when to personalize. Something that might be a great message at midday might be a total turnoff at midnight. This can be as simple as refraining from pushing cereal products after 11 a.m. local time. Discretion shows you can be trusted with personal
information.
It is more complicated than ever to use data to market to consumers. The risk is exposing your marketing as naked calculations based on data inputs, so keep such machinations under wraps. If there’s a greater than 10 percent chance that a consumer will figure it out, don’t do it. Let the valley remain unexplored—both for the sanity of your customers and the safety of your brand.
