AI and machine learning are here for the biopharma industry. Over the past several years, leaps forward in technology and the democratization of deidentified health data have made finding and messaging potential patients and prescribers much more feasible. But AI also presents the biopharma industry with an important tool to learn who, exactly, your patients are – and based on that knowledge, determine the best way to message them.
Personas and segmentation are tools as old as marketing itself, and in the age of data, they’re driven increasingly by objective insights. If you are in the business of selling trucks, it can be fairly straightforward to track down the demographics of truck buyers – sex, income, location, etc.
But when it comes to patients, it’s much more difficult – particularly when you consider patients with uncommon or rare conditions. What does someone who is likely to suffer from, say, a specific rare genetic disorder look like, demographically speaking? On the occasion where you can present that person with messaging, how can you ensure that it is a message that is likely to resonate?
While biopharma treatments are absolutely not lifestyle brands designed to pique the day-in day-out interests of marketing recipients, it is undeniable that a message tailored to the potential patient’s interests should be better-received and more likely to be acted upon than a generic one.
It is for this reason that Swoop, with intelligence by IPM.ai, uses its HIPAA-certified deidentification platform to help biopharma clients build demographic patient profiles along with providing active patient-finding solutions. We have the ability to run evolutionary AI techniques on an unlimited number of demographic combinations, and as such can provide two services:
- One, demographic-based ad buying with actual audience quality that does not run afoul of health data targeting regulations, and
- Two, extremely detailed, yet still anonymized, demographic profiles of your ideal patient population
The value of AI in this endeavor is strong: rather than relying on human intuition, which can provide a useful jumping-off point but can only evolve so far, machines can run countless combinations of demographic elements that may not make logical sense but that correlate strongly with a propensity towards a condition.
While a human may logically know that males over the age of 50 are more likely to get prostate cancer, AI can tell you objectively that males over the age of 50 in the Southwest who fish and do not bicycle and who are white but not with a postgraduate degree are more likely to fall into your Ideal Patient Population.
With this information, not only can you better tune your demographic-driven ad campaigns, but you can tailor your creatives to a more detailed and accurate persona.