August 1, 2017/Derek Choy/Big Data

Big data can sound, and is, high-tech. If you’re a pharmaceutical sales rep, big data might even sound a little threatening. (Based on the cliche depiction of big data—a swirling vortex of binary code swallowing up any shred of humanity that stands in its way—it’s an understandable reaction.) But here’s the truth: in a reality where success depends on enhancing the value of every rep-HCP interaction, big data is the pharmaceutical rep’s biggest ally. With the ability to synthesize reams of data into specific insights about individual HCPs, big data offers a level of personalization that savvy pharmaceutical teams are using to enrich human connections, not replace them. Here’s how.

Leveraging Machine Learning to Build Authentic Connections with HCPs

The plight of the modern sales rep—too much data, too little time—is well-trodden territory by now. Yet even with physician accessibility at an all-time low, pharmaceutical reps are still expected to keep providers up to date on the latest product launches, clinical data and patient outcomes (often in the time it takes to power walk from one area of the hospital to another). Generalities, averages and assumptions have no place in this sales environment. To deliver value, interactions must be responsive, targeted and concise.

This is where decision support engines can help. Machine learning algorithms can strategically process a given HCP’s recent actions, interests and challenges to bring new selling opportunities to the surface.

  • What events has Dr. A recently attended?
  • What information has Dr. A sought out independently?
  • Does Dr. A have patients who will be affected by a recent formulary change?
  • Which direct emails has Dr. A opened? Are there any topics Dr. A habitually ignores?

By preemptively answering questions like the ones above, machine learning does more than condense pre-call planning. More importantly, it tunes the rep’s awareness to the top-of-mind concerns for that specific physician and, in the form of suggestions and insights, provides the detailed messaging points required to address them. When reps consistently deliver highly relevant information focused on patient outcomes—instead of broad-based sales pitches—genuine trust and fortified HCP relationships will follow naturally.

In the event that a given suggestion or insight contradicts the rep’s judgment, he or she can dismiss it and provide feedback to fine tune the decision support engine. This not only improves future suggestions served up to the rep, but it also influences actions on other channels like direct email. In this way, big data can break down the traditional barriers between personal and non-personal communication, allowing reps to use their on-the-ground expertise to drive positive change across multiple dimensions of the HCP’s brand experience.

Giving Marketing the Insights for True Multichannel Coordination

When communication channels are truly integrated, multichannel marketing coordination is finally possible in a way that serves the brand and the rep. Thanks to data-driven tools that can guide and track rep activity in the field, upper-level brand marketers now benefit from a degree of perspective and control that was never available before. With a control panel that documents rep feedback, along with engagement metrics from other channels, Marketing can build out and refine inclusive brand strategies that use every channel to its best advantage.

Our case studies have shown, for instance, that HCPs are three times more likely to open an email sent by a rep than HQ—even when the content is the same. With the ability to suggest when reps should trigger a direct email, Marketing can increase the probability of physician response simply by changing the channel.

With full data visibility, brand marketers and sales teams can also organize and control the cadence between interactions to eliminate redundant messaging and tailor content to follow the progression of a natural conversation. It’s a more human form of engagement that leaves physicians feeling less like sales targets and advances their perception of the brand.

Human by Design

In order for machine learning tools to foster authentic connections between reps and HCPs, taking a human-centric approach to algorithm design is absolutely critical. When we first launched our software back in 2011, adoption rates made it readily apparent that any algorithms developed without real-life behavior as the primary consideration would underperform, often significantly. So, we learned. We revised our strategy—going on ride-alongs, interviewing reps and conducting user acceptance tests to build a tool that accurately represents the way reps think and behave. Encouraging reps to provide feedback on suggestions that don’t “feel right” not only places control in their hands, but also ensures that data-driven tools continue to learn from and reflect the intricacies of human relationships.

As long as a patient’s well-being can be positively affected by the drugs they are prescribed, the success of the pharmaceutical industry will depend largely on the strength of relationships and trust between reps and HCPs. For this reason alone, artificial intelligence will never take the rep’s place in the sales process. In fact, it’s giving them the tools to secure it.