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What are the Benefits of Predictive Intelligence in Life Science?

By Life Sciences Review | Tuesday, November 03, 2020
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The life science analytics sector is using predictive intelligence to improve the healthcare data


FREMONT, CA: The life science analytics sector is developing every day with the help of AI, or ML-driven technologies, and the enhancing healthcare data is expected to increase more in the future. The new databases are rising from digital channels, patient claims, and electronic medical records (EMRs). The stakeholders' preferences are also developing as the pharma sales reps are finding healthcare physicians (HCPs) more challenging to reach.


According to market researchers, most HCPs will control the in-person sales engagement, opening various opportunities for digital and connected health messaging. The patients are becoming more digitally connected with the help of implanted health devices and wearables and being unprotected to direct-to-consumer promotions (DTC) like TV Ads, digital ads, and many more. Pharma marketing and brand leaders challenge traditional engagement methods and increase them with consistent, prompt, and relevant messaging with practical and preferred channels.


Pharma marketing strategies have become more proactive than reactive by applying predictive intelligence in the entire analytics infrastructure. 


The marketing and brand leaders are cautiously evaluating the likelihood of campaigns to accomplish success and tailor them to best suit the parameters driving performance. It is one of the primary reasons organizations across the globe are pulling up investment in the sector of predive intelligence. 


Check Out: Top Pharma and life Science Analytics Consulting Companies 


1. Influencing Patient Adherence


The pharma companies are utilizing predictive patient analytics for influencing patient behavior in their best interests. The pharma companies are deriving 360-degree patient journey insights with an effective mix of patient-level data, domain expertise, and advanced analytics techniques for solving patient analytics problems. Such insights are being offered to the HCPs to help them understand how their patients will behave during the treatment plan. 


2. Intelligent and Targeted Messaging


The predictive insights are utilized for smart and targeted marketing strategies. The predictive AI or ML algorithms implemented to several healthcare datasets are discovering the dynamic customer personas with diverse preferences. The personas target messages on drug efficacy, health outcomes, and treatment adherence. 


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