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Pharma companies now need to identify areas where AI can be applied to the digital initiatives of every pharmaceutical marketer as they strive to reach physicians with precision and usefulness, writes Gaurav Kapoor.
In the last decade, pharmaceutical companies have more than doubled their digital marketing expenditure. As physicians increasingly turn to new sources of information, the foray of pharmaceutical companies into the digital space continues to be deeper and more expansive. The need of the hour is to identify areas where artificial intelligence (AI) can be applied to the digital initiatives of every pharmaceutical marketer as they strive to reach physicians with precision and usefulness.
Over the last few years, the role of the traditional medical representative detailing model has transformed. Medical sales reps complement new digital channels to help physicians interact with product science experts or medical science liaisons to facilitate a better understanding of drugs. Customer Relationship Management (CRM) system powered by AI has almost become a necessity as the industry grapples with shrinking pipelines, patent cliffs, and the increasing cost of maintaining a sales force. Medical reps play an essential role in shaping a digitally enabled personalized journey for physicians. As physicians engage with product data, clinical trial updates, and real-world evidence through various channels, physician preferences and requests captured in a CRM coupled with engagement behavior tracked across the channels become the basis for the design of marketing campaigns.
Employing AI competencies to automate and govern marketing campaigns is a part of a new and emerging philosophy to provide a unique and coherent experience enabled by advanced technology. Marketers can address requests or proposals quickly using customer insights garnered from their journeys and touchpoints. The use of machine learning to identify patterns and respond with an appropriate solution will continuously improve the quality of the next best actions. The challenge for marketers is to optimize the brand engagement journey for any physician or patient as they traverse various channels before any action is taken. Advancements in AI and machine-learning have helped numerous industries account for factors such as the number of touchpoints before making a decision, preference of active or passive media, and choice of channel for content interaction among others.
AI can help apply a degree of control on inbound and outbound interactions that can help realize the value of micro-moment marketing, especially for physicians who have to balance patient care with continuous knowledge enhancement to improve treatment plans. The change of experience between jarring content bombardment and seamless interaction with personalized information on the right channel is often subtle and unnoticed. Marketers need AI-enabled solutions or platforms to use scores derived from sophisticated propensity modeling to provide relevant and custom information that matters to physicians and patients.
One component of personalized marketing campaigns is the use of programmatic advertising/media buying. The ever-evolving regulatory landscape in local markets will pose challenges to the use of programmatic media buying. Marketers have to work in tandem with regulatory experts to fine-tune the algorithms that drive the buying process to factor in the concerns around brand safety, data privacy, and regulations. The examples of misplaced ads in Google and Facebook are a good reminder of the intricacies involved in using programmatic advertising effectively without drawing any noncompliance warnings from health authorities. Connecting AI to programmatic advertising will help deliver the right content at the most appropriate time based on the known preference of the physician. The application of AI will also help pharmaceutical companies realize better ROIs, with bid and ad alternation in real time, without compromising on personalization efforts.
The key to any successful marketing campaign finally comes down to the quality and relevance of content shared. Using AI in content creation is another area for pharmaceutical companies to consider as the number of drugs and devices sold in markets across the world increase. The use of machine learning and AI to create content sized for a particular channel and addressing the needs of the target audience has proved to be a successful model. Intelligent tagging of copy and design elements to repurpose content has helped reduce costs significantly apart from decreasing the time to creating new content. AI will be integrated to content management systems to improve search results, metadata management, and consequently search engine optimization to boost the visibility of newly created content. The use of AI to make near-real-time content recommendations to medical reps or medical science liaisons based on content analytics can help improve the outcomes of their engagements with physicians. As AI systems gradually operate with greater autonomy over time, content creation will shift from science to art. The utilization of AI to develop content will define the contours of a long-term brand association that is needed for pharmaceutical companies to remain relevant.
The analyses of multichannel marketing campaigns require a well-established analytics platform that can measure the success of activities designed for multi-format engagement. Analytics helps create segments to deliver persona-focused information by using data to develop propensity scoring models and further refine personalization as the campaign learnings update persona information. The factors that help shape the resulting communication are geography and demographics information; call center activity; managed care data; and CRM information in framing focused, relevant, and personalized messages at every stage of the customer journey. The diversity of parameters that influences a prescription can be evaluated and competitor brand analyses along with a physician or patient’s online and offline behavior across various channels to decide on the next-best action to affect continuous content interaction and decision making. Analytics-supported segmentation helps the sales and marketing organization to redirect their resources quickly and with purpose to support everything from new product launches to asset optimization of mature products.
Segmentation prioritization has become an area of significance for companies that have not had a blockbuster drug in recent years and are struggling to cope with diminishing market share in their respective therapeutic areas.
The future of multichannel marketing for a majority of innovators in the pharmaceutical industry has to factor in narrow profit margins due to patent expirations, the presence of agile generic manufacturers, regulatory compliance, and outcome-based revenue models among other parameters. Technology can and will play a role in the financial health of companies in the face of new challenges. However, the onus on marketing executives will be to identify the right combination of technologies for brands to generate value for their target groups while contributing to the bottom lines of their companies.
For a pharmaceutical company to create the next-best patient-centric paradigm, it must help the physician in their content engagement journey, delivering information through the right channel at the desired time in the most effective format. AI adoption will not only help improve predictability but also significantly enhance any pharmaceutical company’s endeavor to streamline processes and maintain compliance.
Patient and physician strategy, not channel strategy, should be the focus of marketers. AI adoption, then, is almost a necessity to hone the effectiveness of marketing activities as the pharmaceutical industry is challenged to meet the ever-changing demands of their external stakeholders and data privacy regulations. Ultimately, as the use of AI penetrates all aspects of the sales and marketing organization, a single view of the target audience will emerge, an integrated view created from data and analytics combined from various channels.
Gaurav Kapoor is Executive Vice President and co-founder of Indegene. He is responsible for innovation in product commercialization consulting and solutions for the life sciences industry.