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In our recently launched white paper, The New 5 Ps of Marketing, we talk about how one of the reasons companies like Netflix, Spotify, and Amazon are knocking marketing out of the park is because they’re constantly collecting relevant data on their users.
They know what we click on, listen to, watch, abandon, purchase, add to wish lists, etc. And here’s the key: They’re collecting that data themselves.
Which means they know where it comes from, how accurate it is, when they collected it, etc. They never have to guess if it’s correct, up-to-date, or has been properly managed. They never have to question its sources. Because the whole process—start to finish—was within their control.
These piles of data collected and controlled by a single company are what we like to call data moats. And they’re a game changer for marketers.
The data moat strategy is a relatively new one—and one that most companies still aren’t prioritizing. Because for a long time, marketers have been focused on third-party data. We’ve been using demographics to predict buying intentions. We target moms for laundry detergent and bachelors with cigars. We target teens with college prep and twenty-somethings with mortgages.
Marketers, in other words, have built a massive industry around demographic customer insights. But while that data still has some value as we think about overall trends and target audiences for messaging, we now know that behavior is more predictive than demographics. And third-party data—data we haven’t collected, connected, and tracked ourselves—is often incomplete or just plain wrong.
Which is why best-in-breed CDPs focus on collecting and connecting your first-party, proprietary data and, importantly, not only providing a way to categorize customers by their demographics, but by tracking their behavior.
Because it’s far less effective to target all moms with your laundry detergent ads and far more effective to target people who are known purchasers of laundry detergent. Male, female, single, married—it’s not the person’s gender or status that drive them to become customers. It’s their behavior and affinities—two things a good CDP with built-in data science and machine-learning should help you track in real time.
Here’s the thing: Most marketers know that third-party data isn’t delivering on its promises. According to recent research, 82% of brands and retailers believe third-party data is unreliable.
This ongoing mental shift away from full reliance on third-party data is probably why we’re seeing an industry shift toward proprietary data and huge year-over-year growth in CDP use across a variety of industries. It’s also part of the reason companies that adopt a best-in-breed CDP are seeing incredible business results.
Is your business collecting first-party data from your customers? If not, what’s holding you back? Our data experts would love to chat with your about your business’ data challenges and how a CDP might be the answer.
Contact us to set up a demo, or grab your copy of our latest white paper to learn more about proprietary data and the other foundations we believe are essential for marketers today.