As Chief Technology Officer and Head of Data Science, Ian Liddicoat leads the optimization of Adludio’s world-beating marketing analytics.
Creativity in digital advertising went through a period of decline during the 2010s, with the quality of campaigns delivered on mobile having especially suffered. This was in part due to the industry’s dependency on identity solutions and user tracking.
However, the imminent deprecation of third-party cookies combined with the increasing availability of smart technologies has led to a rebalance. The result is that the industry is reacknowledging the central place of creativity in advertising.
Indeed, creativity has always been one of the industry’s greatest weapons—just one that relied too much on the subjective analysis of the creative objects that appeared to drive success. Although dynamic creative and A/B testing allowed advertisers to achieve a level of optimization, this has largely been focused on the success of one ad unit versus another rather than something far more granular.
Thankfully for advertisers, data science and AI in particular now cater precisely to this level of analysis and optimization.
The Emergence Of AI
Of course, it’s become a bit of a cliche in the industry to speak of the ‘mainstream emergence of AI.’ Nevertheless, its influence on digital advertising cannot be understated and this is only set to continue.
Having long-powered, real-time bidding and search engine optimization, recent developments in AI have taken the capabilities of the technology to the next level. In particular, deep learning technologies, computer vision, neural networks, large language models and re-enforcement learning have all developed in ways that are ideally suited to understanding and optimizing creative output at the object level.
For instance, computer vision can identify a range of creative objects within images and videos at the individual frame level. These models can be used alongside generative AI techniques to create content that can achieve greater levels of engagement or attention with a higher level of confidence.
These technologies are able to derive a real-time understanding of how exactly individual creative elements are driving attention and engagement, utilizing this information to inform campaign targeting with specific audiences. Meanwhile, deep learning and neural networks can work together to link this engagement to business-specific outcomes, such as brand awareness or incremental sales.
This combination of different AI methods provides marketers with the ability to deliver the best-performing ads possible but also deep insight as to why one combination of objects, calls to action, texts and so on is more effective than another. AI also allows us to understand the impact of this data in the context of external factors such as seasonality, public holidays or retail events. It is this “creative intelligence” built up over time and applied to a specific audience that can enable advertisers to achieve long-term, incremental performance.
Embracing The Change
AI’s ability to drive creativity and ensure it’s being optimized toward real business outcomes will have far-reaching implications for the current state of the ad design industry. In particular, some legacy creative agencies—which may not have invested in data science and engineering—must now carefully consider how to respond to the rise of AI without having the historical data or expertise in place to unlock the power of creative intelligence.
Some agencies are responding by building in-house teams and solutions. While this approach allows for more control over the technology, it also takes both time and money which companies must consider.
For this approach, education of the organization is required from top to bottom on available solutions as well as on the many different subsets of AI. Furthermore, it’s important to note that AI’s breakneck speed of innovation can mean that expertise can become quickly outdated and must be kept up with. Meanwhile, data structures need to be realigned in order to readily integrate AI.
Many agencies may find that more junior members of the team—having grown professionally with a range of AI tools at their disposal—can help here as they may more intuitively understand its applications compared to their older colleagues. Agencies should also encourage the independent testing and integration of AI technologies into their day-to-day work and empower the distribution of this knowledge across the business.
Others are opting for third-party AI tech solutions which take less time to implement but come with less control over optimization and the insights garnered. Nevertheless, this approach also demands a degree of understanding of technology in order to choose the right partner. Therefore, agencies must begin to evangelize the use of AI across their organizations to not just benefit creativity but to drive forward the business as a whole.
The Transformative Power Of Creative Intelligence
AI is fast becoming a driving force behind the digital advertising ecosystem. It’s critical for brands and agencies to press on to achieve a better understanding of all the applications of these technologies.
Though AI will have a meaningful impact right across the digital space, just as it is having in society, the area where I believe the most considerable impact will be made is creativity. Here, AI is capable of not only informing ad design but also ensuring that meaningful business outcomes are achieved in the long term.
There is little doubt that rapid advances and adoption of AI techniques will usher in the era of the AI-empowered designer—where the detailed insights generated through computer vision, machine learning or neural networks will enable designers to work from a higher and higher baseline of creativity in the truest sense.
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