How AI-powered contextual advertising will replace the third-party cookie
By Chris Bolte, SVP revenue strategy & business development, Yieldmo
We may be in denial, but deep down we all know that cookies are being replaced.
At Yieldmo, we saw the writing on the wall for cookies long before Google announced its plans to phase them out. Already, over half a trillion impressions pass through our ad serving systems every month, and 50% of those – 250 billion – are without cookies.
Over the past two years, the percentage of available cookie-based inventory has dropped by 8% on Android and 73% on iOS and, by our numbers, less than 10% of the traffic on the Apple platform is addressable today.
Yet, old habits die hard, and cookies seem too delicious for advertisers to quit after depending on them for more than two decades. The vast majority still have their systems set to exclusively focus on the cookie-enabled audience while setting the cookieless crowd to 'turn off or ignore'.
With decreasing supply and high demand, the cost to advertise to cookie-enabled users is getting exponentially more expensive, especially relative to cookieless users. Two years ago, cookie-enabled mobile inventory was 300% more expensive than cookieless — today, that price disparity has increased to almost 400%.
Clearly, it’s time to move on. More adaptable, forward thinking advertisers are taking advantage of the efficient pricing and supply trends of the cookieless market and experimenting with solutions that will deliver effective advertising to customers in a cookieless environment - all while adhering to strict privacy laws.
One such solution delivering phenomenal results is contextual advertising — but this is not contextual advertising as you might remember it.
The old is new again, but re-engineered
What makes the new generation of contextual advertising succeed where previous approaches have fallen short? The simple answer is the evolution of technology, notably the advancement of machine learning and artificial intelligence (AI).
The forward-thinking tech of data science, machine learning and patented data architecture, combined with an entirely new class of signals (none of which were available in the first contextual era) gives advertisers the power to curate ad inventory according to the specific KPIs of a campaign.
When pairing legacy contextual targeting solutions with programmatic, inventory often became commoditized, treated the same across multiple partners, with the price the only differentiator.
Now inventory can be judged on a granular level, comparing not only the quality and relevance of the content but also using attention and environmental information to gauge how consumers react to an ad’s placement and, ultimately, predict behavior that drives outcomes.
But you don’t need to get into the weeds of inventory and placement to understand the greatest strength of AI-powered contextual solutions — the ability to gather, filter and analyze huge swathes of privacy-compliant consumer data.
AI-powered contextual solutions can be the make-or-break factor for marketers playing a cat and mouse chase with ever-tightening data regulations. Advertising can and should be effective without invasive tracking, period. And we’ve found that it is.
The re-engineered contextual advertising using AI contextual solutions is focused on the data and how you use it. At the page level, ad level, user interaction and price.
It then uses sophisticated machine learning and artificial intelligence to determine, in real-time:
- What is the best page for the advertiser?
- What is the best ad for this page? Video, native, etc.
- What are the best ad elements for this page and this ad?
- What is the best/most effective price?
The loop is then closed and re-evaluated, incorporating new, more recent signals to refine the process, ensuring that advertisers achieve the best performance possible.
This may seem simple - and it is, in the context of one or two advertisers on one or two publishers. But at scale, the magnitude of the challenge is huge: billions of data points per second, like a Milky Way of data that’s beyond human comprehension.
Luckily, technology has kept pace with the challenges of contemporary online advertising, with AI and machine learning turning this constantly shifting galaxy of data into simple, actionable insights — without a cookie in sight.