In this contributed article, Jack Newman, partner - data and technology, Kinesso, outlines reasons for optimism for data-driven marketing in the wake of Google's stay of execution upon the third-party cookie.
"A Pig, a surgeon and a patient walk into a room"... Why I’m optimistic about data-driven marketing in the wake of the latest twist in the third-party cookie deprecation saga.
Change is usually difficult to sell, let alone uncertainty. As the frontier carrying a multitude of different ‘cookieless’ solutions from all corners of the ad tech industry edges forward in many directions - be it universal IDs, consortiums, clean rooms, or sandbox proposals – I’m reminded that change and uncertainty are not unique to our industry.
Many have claimed that cookieless has felt like heart surgery for digital advertising. It’s then somewhat ironic that heart surgery itself is on a similar trajectory, with common themes and parallel timeframes when it comes to replacing the old with the new.
In 2022, around the time when the initial proposals to remove third-party cookies from Chrome were originally planned to come into effect, Michael Bennet underwent the first ‘successful’ heart transplantation from a pig’s heart to a human. Fast-forward to today and surgeons are using scientific advances to grow a human heart from a sample of human cells meaning pig-to-human transplantation will be redundant soon.
In many ways that feels metaphorical. Our industry has spent the last few years effectively trying to retrofit a pig’s heart, in various forms, to replace the third-party cookie. Meanwhile in the background machine learning, predictive analytics, and AI have been advancing. It’s this convergence of short-term ingenuity and the inevitability of what the future holds that provides the backdrop for optimism.
Much like the innovations in cardiology, using seed samples and cutting-edge science, new techniques are set to eclipse current third-party cookie replacement proposals doing exactly that. This creates an inflection point that could provide the possibility for brands to recompose the market share of their categories.
There are brands that have effectively ignored signal loss resulting from third-party cookie deprecation in other environments, namely Safari and Firefox, and there are brands who already apply data science to try to maintain a holistic and representative approach to addressing and measuring communications to audiences.
Survivorship bias theory tells us that utilising incomplete data sets can lead to poor decision making which perpetuates over time. It’s from the first cluster of brands that market share will become available.
However, for the marketer ready to capitalise on the possibility and opportunity from the likes of causal based AI methodologies, they will be able to fill the gaps in their understanding with increasing levels of accuracy as these models improve – taking aggregated data from multiple disparate sources and layering on mixed media modelling and digital econometrics in real time.
This will also help them shift away from vanity metrics currently present in digital measurement and attribution that the third-party cookie has facilitated. This should help to break down siloes between owned and paid, martech and ad tech, and create a convergence that looks at the whole picture and shifts the focus towards incrementality by assessing all the variables simultaneously.
That shift from correlated to modelled will be daunting but will collide with another cause for optimism – in that concurrently Large Language Models (LLMs), coupled with generative AI, will also be able to be plugged in alongside the causal models, giving marketers the ability to query these complex data sets using natural language. Which means the marketer can pose, or even automate, optimisations and experiments across a newly fragmented ecosystem at speed. That should provide the basis to create arguments to justify increased investment for certain channels or campaigns and further fuel increased performance and growth.