Valassis Digital Blog

Why You Need More Than Just Cookie Data

February 8, 2017 | Courtenay White

I recently had a conversation with client who was having trouble justifying a targeting strategy that wasn’t cookie-only. The thought was, why would I waste ads by targeting a whole neighborhood of consumers who are likely to buy my product when I can mine cookie data to find out exactly who is looking for what I’ve got? Why go beyond the cookie if the cookie tells me everything I want to know?

The answer is two-fold:

  1. The problem is that as a marketer, you likely do want to learn more. In order to really reach a consumer on their terms, in their language, on their favorite device, you have to go further.
  2. Scale—with cookies alone, you simply won’t reach enough consumers.


A Day in the Life of Abby

Let’s use my friend Abby as an example. She’s a young professional and a new dog owner. Here’s an imagined snapshot of Abby’s typical Tuesday.

Let’s say you’d like to capitalize on Abby’s new canine affinity because you’re promoting a new line of organic puppy chow. If you’re cookie-only, immediately the problem becomes clear. Cookies tell us that Abby is interested in pet care, but that’s where the story abruptly stops. To a cookie-only solution, Abby is a consumer who exists for about thirty minutes every morning. In fact, if Abby has her cookies disabled on her desktop, she may never cross your radar at all if you’re cookie-reliant.


What Cookies Can’t Tell Us About Abby

However, if you’ve chosen a strategy that leverages cookie data and then some, you just got a pretty solid look at Abby’s lifestyle. And that’s just from a single day of data—imagine learning about Abby over weeks, months, or even years.

By using cookie data in addition to things like device ID, IP address, in-app data, and even offline data, we can really understand Abby’s wants, needs, and preferences—where she stops for coffee, the types of indulgences she enjoys, how she spends her money, the neighborhood where she works, her buying patterns, and shopping preferences.

It’s also important to note that we see Abby in front of a desktop only once. Now, my friend Abby is a personal trainer, so this makes perfect sense. She spends minimal time in front of a computer during the day, but relies heavily on her mobile device to browse the web, plan her schedule, and communicate with clients. In fact, I seldom see her without her iPhone. I can’t imagine the number of times she could be reached during the day on the mobile web.


Don’t Forget About Scale

So that’s great. By looking beyond the cookie, you’ve found and gotten to know Abby, but as I said earlier, a single Abby does not a successful campaign make—no matter how enthusiastic she becomes about your brand.

Cookie pools limit (remember how we may have missed Abby altogether?), but more data means more consumers. Strong lookalike models that power precise marketing at scale are built on layers of data—loads, in fact. Though cookies can be a part of successful lookalike models, they can’t ultimately power a strong lookalike model. Relying solely on cookie technology severely limits the ability of marketers to generate the scale necessary to identify, reach, and capture ideal audiences.

Not only does this mean that you can find consumers interested in your products, it means you can identify active buyers, the other kinds of purchases they make, which retailers they prefer, and the locations they frequent. In short, it’s the precision you want at the scale you need.


Want to know more about how consumers’ signals are sensed and interpreted throughout the day? Check out our infographic.

About The Author

Courtenay White

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