Embracing the (already) Cookieless Internet
The advertising landscape continues to be altered by restrictions on third-party data, increasing data privacy legislation, and the disproportionate share of ad spend that goes to the tech giants. These transformations have forced the modern advertiser to evolve.
Traditionally, advertising goals centred around getting clicks - now, it is all about achieving deeper ad personalization and relevancy, reaching consumers with trusted content, and measuring ad efforts accurately. However, industry transitions have added an extra layer of complexity for marketers, for example, Google announced the deprecation of third-party cookies by 2023, changing the traditional forms of identity and measurement, which marketers have relied on for the better part of three decades.
Although this may sound like an enormous challenge for advertisers, the truth is that a significant share of internet activity is already taking place in cookieless environments, most notably on browsers such as Safari and Firefox. Over 50% of today’s consumers are not addressable via third-party cookies - and that number will continue to climb. This makes it clear that marketers who are not tapping into cookieless inventory today are missing out on reaching more than half of the internet audience.
So, the question is, how can marketers begin to embrace the cookieless landscape and remain competitive during this monumental shift?
The Solution
First, we must accept that the once-dominant third-party cookie will not be replaced by a single solution. Instead, a mix of complementary solutions will make up the recipe for success. To thrive in this new landscape, marketers will need to adopt a multi-signal approach inclusive of first-party data, cohorts, and contextual data. Let's explore the importance of each:
First-party data is an extremely important signal in the industry for addressability post-cookie and is already a gold standard to have. This form of data comes from consumer behaviours, interests, or actions observed on a website – it provides a real-time view of the open internet and is a proven, dependable, and scalable data source.
Cohorts attempt to cluster first-party audiences and execute on a sub-segment level. By creating these customer cohorts and analyzing content consumption, brands can estimate potential audience size.
Contextual is based on the idea that we can interpret consumer interests situationally, for example, based on the content that a user is currently consuming.
Now, you may be asking yourself - how do these all work together? Well, this is where the power of artificial intelligence (AI) comes into play. The integration of AI and machine learning provides marketers with the ability to classify data much more accurately, getting a granular idea of audience and content insights - transforming unique, real-time data into behavioural patterns. For this step, and to be successful, finding a partner with the right technology is key for brands, agencies, and publishers. After all, the solution must be capable of ingesting, understanding, and acting on this complexity in real-time.
A Sophisticated Future
The evolving digital advertising landscape is an opportunity for marketers and publishers to shift their focus today and take on a multi-signal approach to replacing their cookie-based media spending. The marketers poised to win tomorrow are likely to be the ones that build deep, trusted, and direct relationships with consumers while also mastering numerous available data points. In addition, these practices provide a much more privacy-focused standard for consumers. The time is now for savvy advertisers to succeed without third-party cookies.
By Laura Main, Managing Director, Canada, Quantcast