It’s hard to overstate the potential benefits from the marriage of pharma with artificial intelligence (AI). Already, pharmaceutical companies are deploying AI algorithms in R&D, discovering treatments for rare diseases, vastly reducing costs and time horizons, and enhancing drug discovery successes. Whereas pharma marketing departments have been slower adopters, pharma stands to reap huge rewards by marketing teams getting on board with AI.
AI mimics the human mind, while outstripping any one specific human mind—it’s the human mind, 1000-fold or more. That’s why we hold AI to a higher standard than humans.
In automation, an AI algorithm can perform repetitive tasks with a selection of responsive “if-then” inputs (instrumental within patient screening, medical chatbots, AI assistants).
In machine learning, a different type of AI algorithm returns improved data the more input it receives. Amazon “learns” your buying habits this way.
In pharma marketing, AI is a game changer. In minutes and without the flaws of human error, it can: 1) interpret vast quantities of data, responding to ongoing data changes; and 2) deploy far-reaching strategies based on those interpretations—making them immediately responsive whenever changes are detected.
3 AI Marketing Tools for Today’s Pharma Brands
1. Social Listening
In 2014, we helped a large retailer use AI software to crawl customers’ social media conversations on Facebook and Twitter.
So if one member of the company’s email list happened to solicit recommendations from their Facebook followers on the best refrigerator to buy, the retailer could map that user to their email address and fire off personalized, automated emails touting refrigerators on sale. The company’s web sales conversion ratio shot up from 3% to 18% almost overnight.
Imagine applying similar AI in pharma. “Social listening” is capable of uncovering brand complaints and concerns, as well as user and physician trends, brand attributes, pharmaceuticals’ side effects—endless possibilities. Imagine using AI to immediately message users or doctors citing your drug’s advantages comparative to the side effects of a competitor drug frequently mentioned online, as one example. Without AI’s social listening, trawling the internet for such trends becomes impossible.
2. KOL Mapping
Annually, pharma spends vast resources wooing appropriate KOLs. But who is an appropriate KOL? How do you identify your KOLs? It’s costly and damaging to make the wrong choice.
Machine learning can swiftly and cost-effectively find legitimate, stringently brand-aligned KOLs for any pharma brand. For a COVID-19 application, for example, your algorithm could locate doctors with >100 treated COVID-19 cases and >80% positive outcomes, preferring certain treatment modalities—just as a very simple outline. AI also allows KOL-cultivation proactivity.
3. Marketing Copy Auto-Generation
AI-generated marketing copy frequently outperforms human-generated copy. Yet, pharma spends billions pitching to physicians on Medscape, Epocrates, or Doximity, despite paltry actionable metrics from such platforms.
Conversely, Chase and Associated Press use AI copy, AP alone has generated more than 30,000 AI articles. AI pharma content optimizes triple engagement metrics among physicians and patients, and what’s more, this kind of success is flawlessly repeatable.