Two years ago, Digiday wrote that the use of AI was limited to niche areas of advertising. It was promising — but limited. It was exciting — but also somewhat hyped.
In 2019, the payoff of AI in ad tech seems closer than ever. VC investment into AI hit an all time high in 2018 ($9.3 billion), and many AI ad tech companies started proving their tactics.
The use of AI in marketing stacks is both farther reaching and closer at hand than many imagine.
AI offers new ways to use data
“Despite the disagreements about specific industry or domain application and adoption, the rumble on the tracks (from all directions) seems to liken AI not to a specific tool for a few specific jobs, but as an entirely different (and in large part unimaginable) paradigm of work, research, and productivity,” writes Emerj CEO Daniel Faggella.
Within ad tech alone, Faggella cites a handful of new solutions that bring machine learning to the industry. These include AdBrain, YieldMo, RocketFuel and dstillery. This last one, for example, promises “custom AI audiences” for both brands and agencies. The search is based on millions of attributes and hundreds of millions of members — and it’s all automated with the AI tool.
In other words, AI simply makes marketing efforts simultaneously more efficient and higher performing — something ad tech as a whole has been working to perfect for years. AI is the next step in a natural progression of efficiency and performance.
Just like ad tech, AI should make advertising more effective; but it doesn’t negate the need for the humanity of CMOs and the creativity of agencies. “AI is not going to rupture media agencies,” says Maxus CPO David Gaines. “Technology like this will be how we evolve.”
The role of AI in the media landscape
The key is to not let those metrics-driven adjectives overtake creativity and connection.
“Advertising and technology have always gone hand in hand, and it’s a double-edged sword,” writes Fredrik Limsater at The Drum. “Tech empowers more visible campaigns, but in turn clients expect more agility, speed and efficiency. Those that invest in new tech to expand the reach of their work must extend that innovation to their creative team.”
By way of example, Limsater cites Dynamic Creative Optimization (which should do away with A/B testing for display ads). “Creative teams will need to keep pace with number-crunching AI as it identifies new personas and creative variations are required to speak to those increasingly defined segments,” he concludes.
Long story short: AI in ad tech can provide advertisers with valuable and actionable data for better and more targeted campaigns. “When you have the analytics layer for AI, this intersection of human judgement and machine automation creates a far more personalised and relevant experience for consumers, on behalf of brands,” writes Pippa Chambers at AdNews. The difference between AI-enabled ad tech and static funnels is that the former makes better decisions earlier in the funnel as it learns more about audiences and consumer behavior.
Data made these decisions possible in the first place; AI uses this data makes these decisions simpler and faster.