The AI Tools Preferred by Digital Pros

The public release of OpenAI’s first tools last fall kicked off massive public interest in the ways artificial intelligence can enhance, improve, or simplify aspects of our daily lives. Within the world of MarTech, an explosion of tools and solutions for better-than-ever performance have flooded conferences, industry pubs, and LinkedIn feeds, leaving behind plenty of uncertainty regarding which solutions may benefit your campaign’s efforts.?

While the public's focus has been largely on AI works-in-progress like ChatGPT and DALL-E, digital marketers have already been testing AI-driven solutions to improve their campaign performance and enhance their goals. Machine learning has been a core feature of programmatic buying since its inception, priming digital buyers to embrace technological innovation and eagerly test and learn. So while we watch to see which exploratory AI tools become commonplace and which fizzle out, read on to see which AI-fueled marketing tools have already dazzled digital pros:

Upgraded Contextual:

In a world where AI offerings have exploded alongside the hypotheses of the impact of a cookieless future, contextual targeting is uniquely positioned as the only proven targeting solution that 1) respects the new privacy paradigm and 2) easily incorporates advancement in natural-language processing to improve its precision. This adoption of large language model technology is also far easier to test than trying to prove Google’s chatbot could have feelings.?

Google Performance Max & Meta’s Advantage+:

Both of these solutions are providing a straightforward, simple application of AI’s ability to recognize patterns and probabilities en masse. They apply automation technologies across bidding, budget optimization, audiences, creatives, attribution, and combine them with either the full range of Google inventory (Performance Max), or the Meta Suite of social platforms (Advantage+). With both tools, Brands set their KPI and upload a variety of creative assets and “signals” – audiences, CRM lists, and other first party seed audiences to model from. Initial results are promising, with Coegi clients reporting efficiencies such as a 30% lower bounce rate on driven traffic when compared to campaigns not being supported by AI. Similarly, initial tests of Advantage+ in the CPG vertical saw far-faster conversion results without heavily increasing average frequency.

Attention-based Measurement:

Another benefit of AI’s pattern recognition is its ability to predict which creative and ad placements will drive engagement before anything goes live —?giving us the ability to better collaborate across media and creative teams and offer directional attention metrics to test and benchmark with. Incorporating this logic into creative rationale and testing will only become more important as generative AI tools enter the marketing space; while it’s easy to be wowed by tools like Midjourney, we don’t yet know if their creations can actually persuade consumer action.?

Like any new marketing tactic, exploration of these tools should be balanced with an understanding of your brand’s ultimate business goal. Connect with a Coegi strategist for a custom recommendation, and sign up for The Loop for more insights like these.

Written by Coegi's Director of Innovation, Savannah Westbrock .