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Proving Cookies Wrong

Cookies Get It Wrong
A Real Look at the Inaccuracies of Online Tracking

We talk a lot about cookies. 

Most of all, at El Toro we’re transparent in communicating that cookies and other forms of online tracking are plaguing the world of advertising. The fraud and inaccuracies that accompany cookies are simply detrimental to ad targeting. Why? Cookies track everything you do and everywhere you go online. This tracking creates a cookie profile with assumptions all built based on the entirety of what can be assumed through your online activity.

Have you seen for yourself the faultiness behind cookies and online tracking?

Don’t worry, we did the work for you.

Look for Yourself

Visit the Oracle Data Cloud Registry

Oracle has made this available to the everyday consumer and at no cost. 

Here, consumers can get a deeper insight into what their data profile looks like. 

We mention online cookie-based profiles a lot. Now, you can see your very own data profile. See for yourself just how accurate your cookie profile is. 

We want to show firsthand just how inaccurate cookies and online tracking are. 

For this, we’ll give you insight behind some of our very own employees and what their cookie-profiles look like. Lucky for you, a number of those from the El Toro team offered to help us out here.

 

Chris from the Development Team

       

Things aren’t always completely out of whack. Chris, for example, was one of the only people to have a cookie-profile that was around 50% accurate.

Chris is a single man living with a roommate. 

Knowing that, when looking, we were surprised to see the number of people living in his home with him and his roommate according to his data profile. Amongst the details he found, Chris is said to be both married and have an elderly parent living with him as well as a teenager. 

Not only this, his profile said he had a least one veteran in the home. Needless to say, neither Chris or his roommate are veterans.

Meghan from the Sales Team

   

Meghan is a Louisville native, born and raised. Meghan and her family have lived here their entire lives and are proud Louisvillians. 

Meghan’s online 3rd party data profile says otherwise. 

Over a year ago Meghan visited Austin, Texas. 

Now, according to Meghan’s cookie profile, she’s evidently a resident of Austin, Texas, despite owning a home in Louisville, Kentucky. 

When targeting based on cookies or online-tracking, Meghan is a target for those aiming their ads at residents of Austin, TX.

Ari from the Marketing Team

       

Things get a little more imprecise with each new profile we looked at. 

Ari lives with her fiance here in Louisville. 

The profile started out with some minor inaccuracies. Mostly that Ari lived in Indiana. While geographically nearby, it’s still false. 

The first obvious flaw of Ari’s profile was the demographics she was labeled with. Ari was marked as a wife, despite only recently becoming engaged. This marks her out all possible engagement and wedding based advertising, a major industry. While this isn’t terribly wrong, other aspects were terribly wrong for the fact that she was also labeled the male head of the household. 

Ari is in her mid-20s. Perhaps the most humorous flaw in Ari’s cookie-profile is that she was labeled as having grandchildren in the home. 

Ari’s cookie-profile, used for online ad targeting, would target her based on being a wife, the male head of household, and being a grandparent. All of which are incorrect. 

Tina from the Development Team

           

You’ve heard from Tina before, check out her interview.

Tina’s geographical location was accurate had it not listed her as living in multiple spots across the country. While Tina lives here in Louisville, KY, her cookie-profile disagreed. 

Tina was marked as living in Northern Ohio, Pennsylvania, and California.

Tina loved her cookie-profile. In fact, Tina was the only one to say “I want to live in this cookie-land.”

Tina’s profile thought quite a lot of her, especially her household income. While we won’t give away Tina’s pay, we don’t really need to. Have a look at her income indicators yourself. Tina would be pulled in audiences built based on incomes ranging from $30,000 a year all the way up to $499,999 a year, a major discrepancy.  

Bart from the Ad Operations Team

           

Evidently, when online tracking can’t figure out your attributes, they just give you all of them.

Bart from our Ad Operations department had perhaps the most outlandish cookie profile. 

Bart did not simply have incorrect attributes. Bart had all of the attributes.

When it came to Bart’s age, his cookie profile tagged him with practically all of them. Oddly enough, Bart was labeled as being in all age ranges, all except his actual age range. Bart is in his mid-20s. However, according to Bart’s cookie profile, Bart is 30-34, 35-39, 40-44, 45-49, and 50-54. 

Bart is a single guy with no kids. His cookie-profile, on the other hand, tells a different story. Bart, despite being single and in his 20s, has a slew of children. Bart was labeled as having infants (ages 0-2), toddlers (ages 3-5), children (ages 6-10), and even teenagers (ages 11-18).

Lastly, if only for the humor alone, Bart’s shopping behaviors were as wild as his age range and number of children. Bart owns a Honda, which he purchased within the past few years. His cookie-profile sees his spending habits as a little more lavish. Bart was labeled as owning not only a Honda but a Buick, Cadillac, Dodge and Fiat car as well.

What We’re Looking At

Cookies are turning obsolete among most browsers, specifically Chrome, Safari and Firefox

However, that doesn’t mean you’re completely off the grid. Data is compiled from past online activity or is obtained through an opt-in gesture. Either way, there’s still scraped together data behind the majority of consumers. 

What goes into this data? Any of your online activities. Things like your clicks, your scrolls, and the websites you visit all go into building your online profile. 

This 3rd party data profile is what is available to marketers for building audiences. Marketers can take one or a number of these consumer attributes for the purpose of building an audience segment. 

The only problem here, as you’ve seen 75% of the time this information is incorrect.

Cookies Fall Short

The data you find here in just these few examples shows the inaccuracies of cookies. These incorrect attributes are the aspects being used to target these people. We’ll say it again, these attributes are false. When advertisers use cookie profiles or cookie derived attributes for targeting, they’re wasting their advertising on incorrect data. 

There’s no need for arguing in regards to the validity of cookies. 

Let the data speak for itself. 

Have a look for yourself, visit the Oracle Data Cloud Registry.

It goes without saying, El Toro operates 100% cookie-free.

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