These days, everybody’s talking about personalization—and with good reason. Companies who get it right are raking in the revenue. Like Amazon, which attributes 35%+ of their sales to their personalization engine.
But here’s the catch: Personalization isn’t necessarily what marketers think it is.
As our CTO, Aaron Raddon, pointed out in his recent MarTechSeries article:
“Segmentation was supposed to solve the ‘personality’ problem by customizing the customer experience, but it only provides the illusion of personalization. We’ve all had the experience of interacting with a brand that seems to know us, only to receive a completely off-target offer from them that shatters the illusion.”
I recommend reading Aaron’s full article—Why Your Mickey Mouse Marketing Tactics Aren’t Working—but if you’re looking for a quick snapshot, here’s a summary.
Segmentation isn’t true personalization
Segmenting customers into demographic, interest, or even behavioral groups is undeniably a better way to market than just throwing messages at everyone to see what sticks. But segmentation still isn’t the same as true personalization.
The problem with segmentation is that it’s still too broad. Changing my Facebook relationship status to Engaged doesn’t mean I want wedding planning services. Clicking on a kitten video doesn’t mean I’m adopting a cat. Buying a doll for a friend’s collection doesn’t mean I want you to chase me around the internet with doll ads for a year.
As Aaron says, “It’s hard to have a one-to-one relationship with your customers when you’re treating them as one drop in a larger bucket.”
Personalization requires a segment of one
So, getting to the kinds of results that industry leaders like Amazon and Netflix enjoy takes more than just segmentable customer data. It requires you to treat customers as a segment of one. Instead of using an interest or two to lump them in with a larger group, you use their real-time behavior to understand them and their goals as an individual.
For example: I have a dog and love watching dog videos. From a segmentation perspective, this puts me in the target group for dog food ads.
But here’s the catch: My dog has a complicated mix of food allergies. They’re so complex that I actually make her food by hand. I have not purchased dog food in over five years and will not be purchasing any anytime soon. Companies spending their ad dollars targeting me with dog food are wasting money, time, and an opportunity to target me with something more relevant.
If those companies were paying just a little more attention, they might notice that I watch videos about home recipes for dogs, search for and read articles by veterinary nutritionists, and visit sites about home feeding. Even just knowing one of these things about me could clue someone in that I am a good target for dog-related ads, but the right ads for me are for dog cookbooks and nutritional supplements—not dog food.
A segment of one requires data science and automation
So, how do you avoid wasting your dog food advertising budget on people like me? How do you actually create segments of one when you have hundreds, thousands, or even millions of customers?
The only way is through a CDP with built-in data science that understands my individual customer needs and context in real-time—and, importantly, allows you to automate your personalization.
If you’re in the market for just that, check out the Guide Personalization at Scale: 1:1 Marketing to the Million.
And don’t forget to check out Aaron’s full article for more thoughts on true personalization.
