The transformative power of artificial intelligence is just beginning to be realized in pharmaceutical marketing. While machine learning and AI have been around for years, it’s only recently that we’ve found ourselves in what I often describe as a technological Wild West. (Interesting sidenote affirming my choice of words: AI summarizes Wild West as “a complex and multifaceted period blending adventure, danger, and the pioneering spirit of those who shape the frontier.”)

Expanding into new territory is always challenging and perilous, especially for heavily regulated industries. With new AI capabilities and tools cropping up regularly and every industry trying to figure out the best way of harnessing them, pharma marketers have been advancing into AI cautiously.

Social media analysis is one of the first areas where the industry began successfully using AI tools. This involves extracting information and deriving insights from user-generated content across all major social media platforms globally. Using AI models enables pharma companies to identify trends with unprecedented scope and speed and gain real-time insights into public sentiment and patient needs.

As pharma marketers continue assessing AI and its significant opportunities, following are some important ways AI can be used to enhance DTC marketing.

• Getting Personal: Personalized marketing is a key area where AI-based research models provide great value. Using AI tools to evaluate a variety of data – including social media engagement, click-through, and bounce rates – gives DTC marketers a deeper understanding of the patient journey and the touchpoints and issues that impact it. Ultimately, this information can drive more sophisticated targeting strategies and more relevant, personalized messaging. It also helps marketers anticipate market shifts more quickly and be more agile and focused in responding to them.
• Growing Sentimental: Using AI to analyze unfiltered customer feedback on social media and review platforms gives DTC brands the ability to proactively address patient concerns and urgent issues. For example, a Facebook user posting a question about a new drug may immediately get hundreds or even thousands of comments addressing the query. An AI-powered tool can evaluate the posts in real time, assess opinions expressed, indicate misperceptions, and flag commentaries that require a proactive reply.  AI-assisted sentiment analysis can also identify what social media groups and influencers are developing around a specific disease state or drug. This enables pharma marketers to provide more relevant content, helping to increase conversion rates.

• Correction Please! AI models are also useful in stopping the spread of misinformation and disinformation. By rapidly evaluating huge data sets and targeting the origins of bad information in real time, AI enables pharmaceutical companies to respond to misinformation both quickly and directly at its sources. This, in turn, can help companies correct the record and establish greater trust in their brands. Imagine if AI had been further developed during the pandemic to respond to the disease and vaccine misinformation prevalent at that time.

 

While the sophistication and accessibility of AI tools are thrilling, DTC marketers still need to balance traditional market research with AI-led models. Traditional market research generates large volumes of in-depth information, but that data is very time-consuming to analyze and limited in scope. AI-driven research is fast and broad in scope, but still subject to bias and misinterpretation in some areas, e.g., it can misinterpret sarcasm or context-specific nuances, which may skew results. The best approach for DTC marketers is to identify and verify where AI-driven research can most effectively complement traditional research and develop an integrated strategy that optimizes both.

While we don’t know what the next election will bring, we do know that privacy and governance in AI will be on the table. Pharmaceutical companies and their agencies must develop their use of AI within a strong data-governance framework, always asking themselves what the ethical boundaries of AI are and how data privacy and online patient information can be protected. Without this focus on privacy and governance, the industry risks major setbacks and penalties in its adoption of AI. Protecting the autonomy and privacy of the individual remains paramount.

Ultimately, the goal of using AI in DTC marketing is to help consumers better understand their health, the diseases that affect their health, and the options available for preventing, managing and treating those diseases. With imagination, skill, and proper guardrails and compliance, AI could well usher in a transformative new era in DTC marketing.