At the Speed of Light: AI’s Game-Changing Impact on Media Analysis

Everything in healthcare moves at lightning speed – and our ability to stay ahead of what is coming is essential to our clients who are working steadfastly to provide critical life-saving therapies to patients. With the explosion of digital content, new channel consumption and the rapid dissemination of information, our need to move faster, stronger and better is only amplified.

Among the many strategic tasks we perform for clients, media analysis is key, as it’s an important ingredient to a brand’s success. This type of analysis helps a brand understand how the public perceives it, identify key trends and insights, measure campaign effectiveness, monitor emerging issues and reputation management, and benchmark against other brands trying to take leadership in the category.

Media analysis might be one of the oldest practices carried over into modern-day marketing communications that has never lost its importance, but it can definitely cut into clients’ billable hours – and time is MONEY. Some clients may even want to skip media analysis to focus on creative – but doing that is like building a house without a blueprint. Could AI help change how we undertake modern media analysis?

From Dreaming to Doing: Becoming the Solution

With our company’s recent RC Labs initiative, I was constantly flooded with thoughts about how I could tap into the power of AI to change how we were working – to eliminate mundane data curation and skip to the actionable insights that would feed our creative muscle for clients. That curiosity led me to join the Communications cohort of the RC Labs program in April 2024.

Building a Media Analysis Tool

Within RC Labs, I spearheaded the creation of an AI assistant named "Media Coverage Analysis Assistant." Along with colleagues and our tech sponsor, we designed this new assistant to sift through vast amounts of media coverage, coding articles for sentiment, spokesperson inclusion and key message inclusion – essential qualifiers in media coverage assessment.

Overcoming Challenges: The Learning Curve of AI

Like any new technology, AI presents multiple challenges. My team and I faced issues with inputting large quantities of data, which led to poor outputs from the AI assistant.

Another significant challenge was teaching the AI assistant the nuances of specific client needs. We understand every project and client we work with is unique, so we need to leverage this tool in a way that complements, not complicates, our skillsets as communicators and partners.

It was no easy feat, but after learning from other employee AI assistants, collaborating across our long virtual hallway, and making several rounds of revisions, we were able to successfully hone how to code for some pretty specific qualifiers we were asking. This iterative process even led to the creation of two different assistants to complement the full effort, underscoring the complexity of the task. Given the collaborative nature of this process, we continue to learn and use the technology more efficiently, ultimately allowing us to play a better role in helping our clients serve patients every day.

AI in Action: A Product Approval Case Study

The AI assistant proved its worth during my first product approval for a client. It analyzed more than 50 media articles in a fraction of the time it would have taken manually. Typically, it takes a team member around two hours to code 20 articles. For larger batches, it could take several employees nearly five to eight hours, especially if a quick turnaround is needed. This tool has the potential to save clients nearly 10 hours in reporting efforts not just once, but every time we do it.

Embracing the “Work Smarter, Not Harder” Mentality

Integrating AI into my workflow has fundamentally changed how I think about efficiency. RCIS Workspace, our enterprise generative AI workspace, and our partner Writer. ai, a leading provider of enterprise generative AI, are now my go-to tools when tackling large-scale analyses, including media analysis. That shift has allowed me to work more efficiently and effectively, whether in brainstorming, content development or research. My hope for the future is that we can continue to learn and use these tools to help deliver on our patient-first mission to improve and save lives by helping our clients bring innovative therapies to patients in need.

As AI evolves, Real Chemistry continues to innovate in how we work to let our people do what they do best – CREATE solutions that connect us to a healthier world.

For more information about AI at Real Chemistry, reach out to us here.