When hype turns to pragmatism – AI and Performance marketing

Over the last 18 months, a gloomy narrative set in that AI was a massive threat to many industries, including performance marketing. The narrative was that it will make some disciplines completely redundant. The reality is far more nuanced than this, and the concern is symptomatic of a wider question that has haunted the industry for some time. The thought seemed curious and a little poorly defined a few years ago. You could (for example) theoretically see how Google Ads might eventually get to the point where large budgets with detailed objectives could be managed almost single-handedly. The rise of Universal App Campaigns was an early sign of this, with later additions such as Performance Max and Responsive Search Ads continuing the trend.

What was much harder to imagine, was that in a couple of years we would have technology rapidly developing that challenges the idea you need creative production, data engineering or project management time at all o manage these end-to-end campaign activations. These are (were?) prized teams, invaluable to the best performance teams working on the biggest campaigns.

My view on this, is that performance teams reside between 3 separate levels of maturity when it comes to AI.

Mostly, they are stuck somewhere between the primitive and educated levels. Ad platforms themselves are a simple way that teams have been able to take that first step away from complete non-automation through simple AI tasks being performed to audit accounts and performance. Being unable to progress much further can be because they are forced into it by clients who themselves have not evolved yet, fear the costs, or simply don’t know how to progress in some areas.

What does this mean for future positions in or around performance marketing teams?

Perhaps there could be a new type of department on the horizon to try and move teams away from the primitive level of task organisation and completion. These ‘AI Teams’ would specialise in prompts for AI tools, integration of the software’s APIs into projects involving data, and focus on how to utilise the software through a deep understanding of client and internal needs. The wider problem is trying to get on top of it quickly as it rapidly develops.

The other obvious area that AI is going to rapidly develop is ad space itself. Microsoft has recently revealed that it plans to give users opportunities to place ads into its Bing AI chatbot, creating a new space for performance marketing teams to consider when planning activations. This is not surprising, and potentially a highly lucrative new channel by itself depending on how these ads are targeted. Bing recently crossed the threshold of 100 million daily active users which has been at least partially attributed to the growth of its AI capabilities.

If you have ever seen a ‘top 10 uses for ChatGPT’ post online, you will know just how many AI tools there are. Not all of them can be good. This has the distinct air of the heady crypto days where a new coin was launched every day trying to get in on the action. As some of us realised then (and many more do today) this was mostly hot air. Could AI tools be in a dot-com bubble scenario today?

Performance marketing teams are right in the middle of understanding what AI means for them. Whilst opportunities will undoubtedly arise from the software becoming more established and understood, so will the threat of some expertise becoming automated to the point at which it no longer requires extensive human resourcing. A great opportunity from a business perspective, but maybe not so great for some employees.

Written by Benjamin Pearton, Head of Activation & Analytics at SYZYGY.