What is cookieless advertising? Well, simply put it means a digital advertising strategy that doesn’t rely on third-party cookies to track user behaviour in order to deliver targeted ads.

And before you ask, third-party cookies are small pieces of code placed on websites by advertisers that track users across the web, collecting data on their browsing habits, preferences, and interests.

Third-party cookies have been used to build retargeting lists, for better personalisation, and for individual user tracking and measurement. However, the reason that third-party cookies have attracted a lot of media attention in recent years is because these cookies are harvesting a huge amount of personal data including IP addresses and device information, and scarily in some cases even logging information about the user without their consent or knowledge, with the risk of distressing outcomes.

Stephen Almond, Executive Director for Regulatory Risk at the ICO highlighted the risks involved, "Gambling addicts may be targeted with betting offers based on their browsing record, women may be targeted with distressing baby adverts shortly after miscarriage and someone exploring their sexuality may be presented with ads that disclose their sexual orientation."

Combine all this very personal data and companies can build a comprehensive profile of their users which they can use to their internal advantage, and potentially sell to others.

Appetite for this activity is thankfully changing, and stricter data protection regulations such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the USA are giving more rights to our online privacy. As a result, many browsers now block third-party cookies by default, and significantly Google is ending third party cookies for all Chrome users in 2024.

The landscape of digital advertising is monumentally changing, and as marketers we need to be aware.

What’s the alternative?

In a new “cookieless” era, we need to find alternative methods to target and reach desired audiences effectively and ethically. Let’s look at some alternative methods:

Zero party data

This is data a user gives voluntarily, perhaps through a survey, poll or even product onboarding. (There are dedicated interactive platforms such as Jebbit or Outgrow that have been specifically designed for this purpose.) Zero party data is still owned by the user, and they will be able to clearly understand what you will use their data for.

Loyalty programmes are also a great way to get your customers to volunteer information about themselves which you can use to understand more about them. In the 2024 Consumer Trends Index, it was reported that 91% of consumers are happy to trade personal and preference data in return for a loyalty reward from you, so if your customers are willing and you have a solution that would suit this then why not give it a go!

First-party data

Advertisers can rely on their own first-party data collected directly from users who have engaged with their websites, apps, or other owned channels. This data is typically more reliable and compliant with privacy regulations, and is collected through means such as website registration, email analysis (i.e. opens, unsubscribes, clicks), or a sign up through another platform. Allowing your user to sign up using their Google profile for example gives you the permission to access more information such as their email address, username and perhaps even location.

Contextual advertising

Instead of targeting users based on their browsing history and behaviour, contextual advertising focuses on the content of the webpage being viewed at that moment. Ads are matched to the context of the page rather than the individual user. For example, let’s imagine you’re a data centre operator wanting to attract a CTO to your data centre services, then you’d want to place advertising somewhere they’re likely to be visiting frequently, like CIO Review.

Probabilistic and deterministic modelling

Probabilistic modelling involves analysing patterns and correlations in data to make predictions — as you might have guessed — it’s based on probability. While deterministic modelling uses known data points to make accurate predictions, it’s sometimes referred to as “authenticated data”.

In short, you can use statistical modelling techniques to make an educated guess about a user’s behaviour without tracking them. (For a deeper dive on this – check out Digiday’s explainer.)

Universal IDs

Industry initiatives like Unified ID 2.0 aim to create a common identifier that can be used across different platforms and publishers, providing a more privacy-friendly way to track users across the web.

What now?

My crystal ball for 2024 isn’t giving me much feedback and no one really knows any specific details about when we will see definitive changes. But let’s get ahead of the game and start preparing now. And in the meantime, if you’re wondering if you can use your customer’s data then remember you can always ask them!

At TBT Marketing we stay ahead of the curve and are here to help you navigate the ever-changing digital marketing landscape. Get in touch today to see how we can help you and make sure your projects and campaigns continue to deliver maximum impact while respecting your target audience’s privacy.