• 4 minute read
  • Nov 1, 2021

Cookie cutter: what the end of third-party cookies spells for media sales vendors

Third-party cookies are on the way out, cutting off a major route to effective targeting for advertisers. But that doesn’t mean the end of effective advertising, and advertising sales.

Whether you are on a diet or not, the constant reminders of - and pleas to consent to - cookies as we navigate the internet are something we all became quietly resigned to in recent years.

However, the era of third-party cookies looks to be coming to an end soon. Firefox has been stating its intentions to block third-party cookies by default as long ago as February 2013, while Safari implemented full third-party cookie blocking in March of last year.

Finally, when Google Chrome announced their intentions of phasing them out by late 2023, the writing was on the wall: as of September 2021, these three browsers between them constitute over 85% of all browser usage (Chrome 67.56%, Firefox 7.93%, Safari 9.67%) - with third-party cookies blocked on all three, they’ll be as good as gone.

The move away from third-party cookies has largely been driven by growing public concern over internet privacy, which accelerated in the wake of various debacles including the Facebook-Cambridge Analytica scandal. 

Although they have been identified as a significant privacy threat since way back in 1997, as recently as 2019, 81% of surveyed Americans said they believe they have little or no control over data the government (84%) or private companies (81%) collect about them.

In the EU, one of the goals of 2018’s GDPR regulation was to enhance individuals' control and rights over their personal data, while in Asia, which accounts for approximately 50% of all Internet users, privacy regulations in various countries are also picking up steam.

While all of this is good news for the average citizen, it is bittersweet news for advertisers, and media sales vendors, who have been major beneficiaries of third-party cookies for the better part of the last two decades.

But it doesn’t have to spell disaster. There are already a number of ways of mitigating the loss of that kind of tracking.

 

1. Contextual advertising

Even if you can’t track audience members, it’s still possible to make reasonable assumptions about their interests based on what content they are interacting with. For example, an audience reading motoring content is likely to be the right segment to target with car ads. 

 

2. Direct request data

With contemporary audiences more privacy-conscious than ever, you have to earn their trust before you can request data from them. Ensure that your compliance messaging is prominent and transparently states how volunteered data will and will not be used. You also need to be extremely clear that you won't sell any data to third-party advertisers.

Offer value in exchange for data, and outline the tangible benefits, e.g. adding volunteers to prize draws, extending event invitations and giving them early-bird access to new products. 

 

3. First-party data

  • Behavioral data: Taking a deep dive into your own analytics will help you build up a picture of audience behavior: what content types get the biggest audience, what times of day, or days of the week, drive peak audience traffic, and what gets clicks and views.
  • Subscription data: Subscriptions and registrations are another way to gain insight into individual people, and to develop a profile of your audience as a whole.

 

4. Zero-party data

  • Survey data: Periodically use questionnaires, quizzes and contests to glean more voluntarily-acquired information from your audience. 
  • Audience feedback: Sometimes your audience will provide you with data off their own bat, in the form of user feedback. This can come in the form of customer inquiries or even complaints, comments on articles, or responses on social media. 

 

5. Email and newsletter marketing

Subscribers, members, newsletter signups and other people that have consented to receiving marketing communications can be reached out to through their inbox with personalized or targeted advertising.

 

6. Lookalike audience targeting

This is where AI and machine learning can help by modelling audience types through mass analysis of audience behavior. This enables targeting of people who are more likely to be high value to advertisers.

 

7. Location targeting

The ability to know the location of a person (or more accurately, device) is not going away with the third-party cookies, making this a strong remaining targeting axis for advertisers.


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