How digital advertising is undergoing a transformation propelled by data science

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.
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