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How to stop guessing which customers to target — and start knowing
See why a rich, longitudinal view of your customers is the key to truly effective campaigns.
If you’re a retailer, there are two ways to decide who to market your products to: Make an educated guess. Or use data analytics to reveal exactly which customers are most likely to buy.
Unfortunately, many brands spend a lot of money on their customer data while still, ultimately, relying on guesswork.
Here’s the problem.
Let’s say you’ve built a campaign to sell socks. You might send a query to your customer database platform (your CDP) that says, “Show me all my customers who’ve purchased socks in the last 30 days.” Or you might ask for “everyone who’s browsed socks in the past two weeks,” or “anyone who hasn’t yet purchased socks from us this season”.
Using your intuition as a skilled marketer, you might deduce that those lists would generate some good potential customers to target. And maybe you’re right.
But the query that would really change everything is this: “Which of my customers are most likely to buy socks today?”
The problem is, most CDPs aren’t built to provide that answer. At least, not quickly and not with great precision.
Why? Because, in order to predict which customers are most likely to buy socks, advanced algorithms must analyze billions of data points — to identify which behaviors are associated with customers who’ve bought socks.
And doing that requires a longitudinal view of your customers.
Hold up. What’s a “longitudinal view”? (And why do you need one?)
Most CDPs show you what your customers look like right now — what they’ve browsed, purchased, put in their cart, and clicked on during the past 24 hours, or, possibly, as far back as the last 90 days.
That’s a “360 view” of your customer.
A longitudinal view, on the other hand, shows you every customer behavior and characteristic from as far back in time as possible and lets you zoom in on any moment to see, for example, what your sock buyers looked like immediately before they purchased socks from you — and, equally important, what your non-sock buyers looked like in that same moment.
With a longitudinal view, every piece of data is on the table. You have infinite 360 snapshots of your customers, and you’ve given yourself the foundation for increasingly powerful machine-learning insights.
Clario was built for the long view.
We designed Clario to find, compile, scour, analyze, and retain every last bit of customer data you have—no matter how messy or incomplete it may be — because the only way to make meaningful marketing predictions is to analyze all of your data, not just the last few days’ worth.
For example, by analyzing all of your customer data, going back several years, Clario might detect that the customers most likely to buy socks are people who purchased socks more than two years ago, or who purchased both shoes and pants in the past six months and browsed socks at least twice over the past year, or who have never purchased anything from you but have visited your sock page at least once a month for at least four months.
Without a longitudinal view of all your customer data, even the best algorithms will never find those patterns.
If you want to predict which of your customers are most likely to respond to your campaigns — so you can invest your marketing dollars wisely — you need Clario.