Partner Forum.pdf

Paul Shawah
Vice president of product marketing, Veeva Systems
CLM captures valuable data for marketing teams to optimize their promotional message and mix—very different from the predictive analytics that inform the field. When connected to CRM, predictive analytics can put targeted information directly into the hands of reps as part of their workflow. To maximize the power of analytics, data across many sources is distilled into an actionable utility that provides specific suggestions on the best channel and action to take with each customer. The result is increasingly more relevant customer engagement—and something far greater than “predictive analytics.” It’s analytics transformed into recommendations easy to access, easy to act on and intelligent. It has the power to enable life sciences companies to finally break out of the past and become truly customer centric.

Stephen Hoelper
Vice president of sales, marketing and product development, MediSolutions
Reduced decision-maker access, shifting regulations and more complex products have created a growing urgency for companies to employ a CRM strategy that uses predictive analytics. When combined with industry trends such as evolving standards of care, reimbursement changes, and forward-thinking movements in patient and physician experience, predictive analytics can provide insight to drive digital sales pitches. In order to best inform a sales strategy, CRM systems should incorporate data such as social-media usage, research, CME and pharma marketing content. This collective information can help determine fluctuations in a physician’s buying process, behaviors and timing, which can assist in targeting the right prospects with the right message at the right time.

Steve Bodhaine
General manager, Encuity Research, an inVentiv Health company
Following in the footsteps of their consumer counterparts, pharma marketers now use data-driven CRM to transform industry data into actionable insights that enhance sales. These on-demand solutions allow companies to view in real-time metrics on physician behaviors, competitive influences and effectiveness of rep visits. Companies can then shift course in days rather than months, using analytics to refine messages that improve physician interaction, both at launch and later. Such insights become even more powerful when combined with custom qualitative research that gives companies comprehensive macro and micro views of the physician landscape. With more than 400 launches expected in the next three years, tools like these are important in accelerating commercial success.

Emily Tower
VP of digital strategy and analytics, AbelsonTaylor
When considering predictive analytics, the question remains: Will it make a better rep? What data do we really have? Does attendance at ASCO and a visit to NIH predict interest in emerging oncology treatments? Reps already have access to data outside the call, and certainly outside their CRM. Can next-generation CRM find a way to fold in customer preferences and behaviors to generate a predictive model that tells the rep which doctors are most likely to adopt a new treatment or well-positioned to accelerate their writing of an existing product? If it can, then yes, CRM can fulfill its own promise of creating the “best rep.”