With AI/ML-driven technologies and the increasing healthcare data (estimated to reach 2,314 exabytes by 20201), the Life Sciences analytics business is progressing every day. Patient claims and electronic medical records (EMRs), social media, and digital platforms are all producing new databases. Stakeholder preferences are changing as well, with pharma sales professionals finding it more difficult to reach out to healthcare physicians (HCPs).
According to a recent survey, one out of every two HCPs would limit in-person sales contacts by the end of 2019, creating several chances for digital and connected healthcare communications. Patients are becoming more digitally connected with wearables and implantable health devices, as well as being exposed to direct-to-consumer promotions (DTC) such as digital commercials, TV ads, and so on, on the other end of the spectrum. As a result, pharma marketing and brand leaders are rethinking their old engagement methods and replacing them with timely, relevant, and consistent content delivered across convenient and preferred channels.
The pharmaceutical sector is likewise coming closer to patient welfare, with pharma companies prioritizing patient health results over all else. Pharma marketing and brand leaders seek to make their communications more relevant to their clients in order to explain treatment benefits and outcomes. Pharma companies are tracking patient journeys to assist HCPs in making informed decisions by combining patient-level and real-world evidence (RWE) data backed patient analytics. The capacity to analyze the entire cost of therapy and patient adherence behavior, according to most pharma companies, will go a long way toward improving patient lives through guided interventions by HCPs.
Pharma marketing techniques are becoming more proactive rather than reactive as a result of incorporating predictive intelligence into the broader analytics framework. Marketing and brand leaders are carefully analyzing the chances of campaigns succeeding and adapting them to the performance metrics that matter most. This explains why firms all across the world are increasing their investments in predictive intelligence. According to a recent report, 58 percent of healthcare executives spent more than 15% of their budgets on predictive intelligence in 2018, with savings of more than 15% expected over the following five years.
Here are the top 3 benefits of predictive intelligence for pharma marketing:
Influencing Patient Adherence: Pharmaceutical corporations are employing predictive patient analytics to sway patient behavior in their favor. Pharma businesses are now extracting 360-degree patient journey insights using a potent mix of patient-level data, advanced analytics tools, and domain expertise for solving patient analytics concerns. HCPs will be given these insights to help them understand how their patients are likely to behave during a treatment plan.
Incremental Promotional Effectiveness: On their multi-channel promotional activities, pharma corporations are carefully predicting promotion response patterns. Customer engagement levels may now be estimated across numerous promotional efforts using AI/ML algorithms, and an actionable engagement score can be generated to hyper-target opportunities and dangers. These algorithms can also account for multi-stakeholder effects, such as the influence of promotions to one stakeholder on another. These insights are also being sent as next-best-action triggers for more productive sales conversations by cloud-based integrated marketing solutions. This aids in efficient details, a greater impact on brand performance, and increased sales conversions. Pharma companies profit by optimizing their brand’s share of voice, customer share of prescriptions, and return on promotional efforts by accurately creating, testing, and deploying multi-channel promotional campaigns.
Intelligent and Targeted Messaging: Smart and focused marketing strategies rely on predictive insights. HCPs prefer individualized and relevant content, as well as proper communication channels, according to a recent McKinsey survey. Predictive AI/ML algorithms applied to a variety of healthcare data sets reveal dynamic customer profiles with individual preferences. These personas are leveraged for targeted messaging on drug efficacy, treatment adherence and health outcomes. By identifying patterns in the data, personalized campaigns are being optimized to become much more impactful and measurable. Marketing Analytics can now answer some critical questions: who to contact, what to offer, when to offer, how to offer. Furthermore, pharma marketing and brand professionals must effectively plan, implement, and analyze their prospective messaging efforts at scale. Pharma businesses are finding it easier to manage their marketing campaigns across worldwide marketplaces, thanks to the increased processing power available to leverage big data and the industrialization of analytics.
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