Improving Sales Effectiveness: How to Turn White Noise into Recommended Strategies

When my children were small, we played white noise soundtracks in the nursery to help them drift and stay asleep. It was like a magic elixir that helped drown out distractions and allowed my wife and me to catch up on our ZZZZs. The term “white noise” technically refers to random noise with a uniform frequency spectrum, and in non-technical contexts, it is metaphorically defined as random talk without meaningful contents.

In the life sciences industry in particular today, the swell of data has grown so much and is coming from so many sources that it is turning into white noise. Every department—from sales and medical affairs to marketing and technology—routinely collects, organizes and analyzes data. It is truly mind numbing (and could have the same effect on the industry as white noise had on my children!). Not only is the volume of data growing, but so are the number of customer stakeholders and the proliferating channels used to engage them, creating a commercial landscape that has never been as complex.

Mining Data to Better Serve Reps

Historically, life science companies created cycle plans—largely based on the decile ranking of each customer’s script-writing potential—for sales teams, guiding them on the frequency of visits for each customer along with what products should be detailed in each position. However, this approach falls short on guiding the rep to an intelligent response based on less quantitative factors like customer preference, market events or patient needs. Addressing sales as purely a “reach and frequency” game does nothing to move the industry forward toward a coveted customer-centric commercial model.

To get there, the industry needs to arm its reps with all relevant customer information, including their information delivery preferences. In many cases, field reps still don’t have any context for meaningful conversations with doctors and doctors still don’t have time for small talk. Improving outreach is further complicated by the variability across the sales force. High-performing reps may understand what to do and can predict customer needs based on their years of experience, but others may need more coaching. Data is crucial, yet given all of the information gathered across channels and customers, the industry has struggled to distill and integrate it for proper field use. Simply put: There’s too much data for even the most experienced rep to absorb, comprehend, and act upon quickly. It’s all white noise.

Data Science Advances into Action

The life sciences industry has already taken the first step to arm its field forces with tablets loaded with the right apps to engage healthcare professionals (HCPs) in a meaningful face-to-face meeting. More advanced companies have gone further, turning their field teams into multichannel reps by combining the rep relationship with the reach and convenience of digital channels to deliver information HCPs value via the channel they prefer.

These new channels have opened up a new world of opportunity and have helped to unlock closed doors to sales, marketing and medical teams—creating even more data sources. Now, all customer-facing teams have a broader view of the customer, which is positive, but reps are left trying to figure out what to do with it. Plus, they have more channels to choose from than ever before. Again, the sheer volume is overwhelming. One person cannot pull from such a broad set of ever-changing variables to best determine what message to send through what channel and when to each individual HCP.

Today, there’s a new way to bring together information that drives customer attitudes and behavior, and then culls it into recommended steps for each particular engagement. A growing number of life sciences companies are leveraging data science to mine the wealth of data collected (i.e., customer response, formulary approvals, patient needs) and combine with business strategy to create very specific recommendations that are the most likely to drive an outcome. More importantly, they’re making it easy for reps to take action by putting recommendations—“coaching”—within the rep’s workflow. Data science combined with easy-to-consume insights at the reps’ fingertips is the answer to distilling the terabytes of data into a recommendation—to turning white noise into intelligent action.

Cloud technology allows data from external and internal sources to be extracted and then integrated into the rep’s customer relationship management (CRM) system to provide insight-informed suggestions reps can use to optimize customer engagement. By drawing upon data science engines, these systems enable the industry to take existing technology a step further. Data can be used to actually power rep forces, putting life sciences companies closer to reaching parity with other industries in satisfying customers. Consumer marketers at retail companies, for example, have long been using data analytics to not only understand consumer behavior, but recognize cause-and-effect relationships. Think Amazon’s recommendation engine, offering relevant choices each time a customer searches for, or orders, a product based on prior experience. The science gets smarter with more data. Now the life sciences industry can do the same in sales, with future application for marketers, too.

“Commercial teams can have incredible volumes of data at their disposal,” says Tim White, Senior Director and Head of Global Customer Interaction Management at Lundbeck. “A product that helps harness it all to take the best actions and deliver the right message through the right channel could be a huge benefit.”

The Rep as Driver

The role of the sales rep takes on an even greater responsibility when one considers the management of the various channels through which information can be delivered. Today’s data-integrated CRM platform would not be complete unless it also supported such multichannel engagements. The CRM must capture HCP activities throughout all channels and integrate that data into actionable insights for the rep. In this context, data science becomes even more valuable—the more customer touch points, the more analysis needed to make specific suggestions. For example, if a physician visits a website to learn about a new drug indication, a rep can supplement subsequent interactions with that knowledge. A suggestion might prompt the rep to email certain clinical information before the next visit, making the follow-on meeting more relevant and better preparing the rep to address any lingering questions.

To fully maximize the power of data science, highly specific suggestions on the best channel and action to take with each customer must be part of the reps’ natural workflow—like having a brainy sales coach available on-demand. The result is increasingly more relevant customer engagement. It also helps new sales reps develop faster and seasoned reps to better leverage new channels like email, which presents a significant learning curve for most reps.

Certainly, reps can—and should—still draw upon their own knowledge of the customer and their experience to decide if such automated suggestions are appropriate, but they can make that decision now from a more informed vantage point, distilled from the reams of data they were never before in a position to absorb. Reps can finally “close the loop” by either rejecting the data-driven suggestions with commentary or providing feedback on actions taken. All of this data can, in turn, be fed back into the system, creating a smarter data engine able to demonstrate customer patterns and results.

Empowering the rep to drive a system built to better to engage the customer makes perfect sense considering that the rep has frontline, personal knowledge of the customer. According to Jaideep Bajaj, Chairman of the Board of ZS Associates, “As physicians adopt multiple channels to interact with pharmaceutical companies, it is critical to understand their channel and marketing offer preferences to predict which cadence of effort will have the most impact. The role of the sales rep, therefore, evolves to orchestrator, who is aware of customer preferences, understands how the sales force interacts with the pharma company and can influence the cadence. Data science can provide valuable insights to sales reps as they meet customer needs in this multichannel world.”

Connecting the Dots

At the end of the day, the industry’s goal is to improve sales productivity by making the customer’s needs and wants central to the engagement process. Data science-driven CRM systems connect the dots to help commercial teams drive the right information to the right HCPs so they can make the most informed treatment decisions, helping to make the industry a true partner in the delivery of better healthcare.

The technology is here now. Companies can equip their customer-facing teams to make the best decisions, giving every rep the opportunity to be a top performer and improving sales effectiveness while creating a better experience for customers. To this end, data science has the potential to ensure fully coordinated experiences for every customer by recommending the next best action and channel. “We are always looking for ways to improve engagement and deepen our relationships,” concludes Joe Horvat, Senior Vice President of Oncology at EMD Serono. “Technology like this with the additional capacity to learn from rep feedback has tremendous potential to transform how the industry engages customers.”

Indeed, the recent advancements in data science combined with new tools that place its output directly into the hands of those who can use it most will allow the industry to finally benefit from the mountains of collected data. Rather than just converting into superfluous white noise, all of this valuable information can ring new bells of inspiration and innovation.

  • Paul Shawah

    Paul Shawah is Vice President Product Marketing at Veeva Systems where he is shaping products to enable modern multichannel communications between life sciences companies and physicians. He has been driving digital innovation in the pharmaceutical industry for decades.

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