Artificial Intelligence is Pharma’s Next Frontier in Customer Relationships

Knowledge of personal preferences can bolster the level of trust between life sciences companies and healthcare professionals, upgrade marketing messages, and ensure successful long-term strategies. At a time when targeted therapies are being embraced to improve patient outcomes, a company’s customer outreach game plan should be similarly individually orchestrated.

With today’s limited resources—both human and monetary—how can life sciences companies possibly roll out individualized customer approaches? With the help of a long-dreamt about IT capability: Artificial Intelligence (AI).

Putting perpetual data streams and rapidly advancing tools and technology to work, life sciences companies can train AI algorithms to drive business decisions. We call this Micro Intelligence: The ever-learning capabilities of AI combined with the ability to inject such knowledge at the right moment inside the systems of engagement to deliver a well-orchestrated approach to customers.

By applying constantly learning algorithms through Micro Intelligence, organizations can handily pinpoint the next steps to take with established customers, identify new customers to target, determine the preferred communication channel, and create the most effective content and talking points. The amassed knowledge culminates into a harmonized plan for engaging customers during future interactions, a plan that is orchestrated across the company’s various business units.

Often unbeknownst to them, customers deposit breadcrumbs—or hints of their preferences—that life sciences leaders can string together to establish an informed and intimate relationship. Outside of the rare top-performing sales professional who can instinctively read customers and dig deep into their backgrounds all while remaining sensitive to their current context, giving today’s HCPs precisely what they want often alludes the average customer-facing employee.

Data about the customer’s behaviors, past interactions, and current interests holds the knowledge to unlock the best approach to achieving the organization’s goals. The output is highly granular and contextual, but make no mistake, machine learning is rendered useless without a solid set of data.

The key is to calibrate the intelligence with the user in mind, and within the context of an overall push to orchestrate messaging across the organization. Internal users are prompted with new task suggestions based on their role, whether that’s identifying the next logical step for a field representative or guiding a marketing professional to use the best messaging channel for a particular HCP encounter. Micro Intelligence prepares various constituents to take action—action intended to drive results and regain trust.

Customers engaged through an orchestrated model will begin to share more breadcrumbs, enabling the company to establish a deeper relationship and provide more value. And through the mechanism of continuous learning, each action and encounter will serve to shape future behaviors.

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