Learn how machine-learned creative intelligence enhances targeting precision and drives deeper insights into media investments, empowering advertisers to optimize campaigns for specific audiences over time.

It’s generally accepted that the digital marketing industry made some mistakes during the 2010s, thanks mainly to its over-dependence on third-party cookies and user tracking. Broadly speaking, the creativity associated with digital advertising campaigns went through a period of decline, particularly when it came to the quality of campaigns delivered on mobile.

Indeed, in the clamor to deliver ads at scale, digital advertisers pumped out huge volumes of low-quality, ineffective campaigns to consumers who regarded them as, at best, irrelevant, and at worst, annoying.

Today, however, the imminent deprecation of third-party cookies, combined with a range of innovative solutions, has heralded a new dawn for digital advertising. In particular, AI-powered technologies offer a new opportunity for the industry, where quality can once again take center stage, underpinned by the smart use of data.

While elements of data science and AI-driven capabilities have existed in the digital advertising space for a considerable amount of time, recent advancements have opened up more innovative and valuable methods than ever before. Most notably, in the deterministic optimization of campaign creative, which has been built from the ground up to pursue brand-specific outcomes.

The ideal creative

AI has powered real-time bidding and search engine optimization for some time. However, recent applications of techniques such as machine learning, deep learning, computer vision, neural networks, and large language models have all evolved in ways that are ideally suited to the optimization of digital campaigns and content. This progression suggests we are now on an inexorable path towards the use of generalized models or AGI that use a range of techniques to achieve an optimal outcome but from a single, natural language command.

While creativity has always been one of the most important elements of any successful ad campaign, the industry has historically found it difficult to establish what really makes one collection of creative objects more effective than another. The barrier to building this understanding no longer exists.

With the assistance of a range of AI methods, advertisers have the ability to not only deliver the best-performing ads possible but also unlock rich insight as to why one iteration of objects, calls to action, text, interaction types and so on works more successfully than another. Moreover, AI also enables the understanding of this data in the context of a range of external factors, whether that be weather, seasonality, public holidays, retail events or local context. It is this understanding and machine learning of the relative contribution of these factors that offers huge scope to the modern marketer.

Better targeting and machine-learned, creative intelligence.

Alongside a better understanding of the impact of creativity, AI provides advertisers with the opportunity to gain deeper insights into which media investments are helping to deliver the desired business results. Indeed, by understanding how individual creative elements are driving attention and engagement, this data can subsequently inform campaign targeting for specific audiences. The application of machine learning also enables marketers to steadily optimize this activity over time.
These new capabilities seem likely to have some far-reaching implications for the ad industry. Some agencies have responded by investing time and money in building in-house teams and their own AI solutions. 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.
Legacy creative agencies — which may not have invested in data science and engineering until now — must now consider their strategy carefully.

Embrace the change

For those advertisers who have not yet embraced AI, as the rest of the industry seemingly has this year, it’s high time to start investigating how the incredible capabilities of AI-powered tools could transform creative design, production and optimization.
This will require board-level commitment to the science of AI and professionals with data science and data engineering expertise as well as specific skills such as prompt engineering.