Overcoming Pharma Marketing Challenges with AI

Pharmaceutical Executive: How is AI helping to overcome the challenges pharma marketing teams are facing?
Ted Sweetser: There’s a brewing issue in the viewability space. For anyone not aware of what that term means, viewability consists of the metrics around validating that a person has seen an advertisement, the time that they’re seeing, and the quality of the placement where a given ad is served. This is something that’s been up in the air since last year when Oracle shut down Moat, which was one of the three major viewability providers. There’s been a lot of talk about the way performance functions in this space for ages. That left IAS and Double Verify as two vendors of this service.

People have objected to things like cutting out large amounts of media inventory that was specifically related to news. Some felt this painting with too broad of a brush in determining what shouldn’t qualify.

There is innovation in this space. There are services leveraging a lot of AI, and one of the more popular trends in recent years of using AI is agentic models that can behave autonomously and crawl across the full span of the internet at a much faster pace and making brand safety decisions that are specific to the needs of an individual brand’s objectives. These models promise to do all sorts of interesting things in regard to shifting what we think of as media and where an impression can be served, hopefully for the better.

It's certainly a big change. It really matters for pharma because, aside from direct response messaging, a huge amount of the spend is going into branding, which has different KPIs than just trying to get a number of clicks on a page. You want to make sure that your message is hitting enough of the population with enough frequency to reinforce the message your brand is putting out there.