“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Stefanos Kapetanakis, GVP, Data and Technology, at Publicis Health Media.
Primary care as your parents knew it no longer exists.
There is a rising consumerization in healthcare, and many patients are opting for convenience over commitment, with more (and more flexible) care options than ever. Patients jump from one physician to another based on their needs. A recent survey found that 35% of millennials don’t even have a primary care physician.
Patients are wielding their power as consumers, and the healthcare industry needs to adapt to address their needs and expectations. Artificial intelligence might just be the key for healthcare marketers to unlock the new patient economy.
The rise of AI: from the value chain to marketing
For years, artificial intelligence has held promise as a potential diagnostic tool in the health space. The technology hasn’t delivered just yet. So far, it has primarily been used to streamline menial tasks across industries.
But recent developments suggest industry stakeholders are beginning to acknowledge AI’s ability to improve other processes. A recent GlobalData analysis revealed that, in 2015, just four pharma companies were working with an AI vendor. But by 2020, that number rose to 27 – an increase of 575% in just over half a decade. In fact, over the past seven years, there have been almost 100 partnerships formed between pharmaceutical companies and AI providers.
The goal for many of these partnerships is to apply machine learning to streamline R&D processes like drug discovery.
While AI is present in the rest of the value chain, its marketing potential remains mostly untapped. Consumer packaged goods have used AI to sell people what they want, but AI usage in the pharma space hasn’t reached that sophistication. The power of personalization is still unexplored. If harnessed, patients would be better served and their care path could be greatly shortened.
Unwrapping the marketing opportunity
Currently, the pharma marketing model relies on a product-specific approach. Direct-to-consumer marketing can often focus on products that have been traditionally successful for the population at large but aren’t applicable to large swathes of patients.
Additionally, the number of promotional channels, coupled with increased competition, has made it difficult to measure the impact of marketing efforts on sales results. This has clouded the ability to even predict which channels lead to the best outcomes.
Now, with AI and machine-learning-driven healthcare solutions built on extensive industry data, sales and marketing teams can precisely analyze results while adapting to health’s turn toward consumerization. Marketers can understand exactly which messages, promotional channels and sales strategies are most likely to engender responses from customers – and when those responses occur during the marketing pathway.
Already, emerging technologies are disrupting the way healthcare industry sales and marketing teams approach their go-to-market strategies. They’re enhancing their experience-based decisions with data-driven insights that allow them to identify highly specific patient populations, customize digital engagement and apply multi-indication analysis.
The path ahead
There are solutions further down the pipeline that hold even greater promise. Some industry disruptors already use AI-fueled clustering linked to consumer data to create highly personalized product recommendations. The marketing application would be to identify the optimal next message to more quickly move the patient through their journey from symptoms to treatment.
In marketing, this clustering technique could be used to serve the right content in various channels by individual patients. These recommendations would also become better informed with more data inputs. That would make them more relevant, while still providing anonymity and confidentiality to consumers.
Automated AI can also help tackle patient non-adherence. Algorithms will eventually understand behavioral patterns that cause it, giving marketers an opportunity to promote personalized solutions, potential alternative care and methods of relieving patient anxiety and uncertainty.
Meanwhile, consumer journey mapping, which also uses AI, could help uncover the changing nature of the consumer’s relationship with brands. With this insight, marketers could then maximize engagement by positively disrupting the journey and fulfilling expectations. They would be able to optimize processes, including content sequencing, resource allocation across digital and non-digital channels, and consumer targeting.
With AI technology, pharma brands and marketers can adopt a consumer-focused strategy that leads to maximum engagement, optimal return on investment and a faster journey to the brand.