We in pharma find ourselves amid a significant evolution in scientific communication and education. With an ever-increasing understanding of more effective data use, we are learning how to better use data to personalize educational experiences. In this evolution, we are pivoting to a more customer-centric model, providing each customer with a truly omnichannel experience. While pharma has lagged other industries in this regard, we now have an opportunity to catch up by applying data at the individual level. Doing so will provide customers with experiences that, at minimum, are on par with their daily interactions with other industries.
In our industry, scientific content must sit at the center of any customer engagement model. That begins with a well-thought-out scientific content framework coupled with an ability to generate original scientific content that meets customers’ needs. Content should advance customers along their journey, a journey that includes adopting the brand into their algorithm, improving patient outcomes, supporting patient outcomes, and improving health system efficiency.
A new customer engagement model might begin with thinking about the customer’s needs and how that customer can interact across a portfolio of brands within a pharma company. From there, we can build an engagement strategy and data plan that supports this approach at the portfolio and brand levels. Taken together, they will guide a scientific content framework that is aligned to the portfolio and brand strategy and generates content quickly.
The overall content framework would drive experiences created for customers that move them ahead on their journey from awareness to adoption. Sometimes, there can be a tendency to establish brand strategy, then move to tactics and adjust the content to the tactic. Other industries have evolved to a place where strategy drives content, and content then drives tactics. While this is an evolution of the current customer engagement model pharma companies generally use, it is not a completely disruptive model that would be difficult or risky to implement.
Matching the Industry to the Individual
One of the most important aspects of an evolved customer engagement model is integrating not only across brands and indications but across customers as well. Easier said than done, certainly. Due to industry complexity, this type of model can only succeed if it brings together healthcare providers (HCPs), patients, caregivers, health systems, and payers as much as possible—again, easier said than done.
An effective future customer engagement model must pivot toward a truly customer-centric posture. That means using disparate data sources to better inform decision-making while focusing more on content without interfering with the ability to follow a well-defined strategy to execution. While the pharma industry moves toward higher customer centricity, individual pharma companies continue to organize themselves by brands. In general, we treat all customers the same with exceptions here and there where we attempt to differentiate our communications by specialty. Even in these cases, when an HCP goes to a brand site, the content is generally the same for all HCPs. In some cases, communications are differentiated attitudinally, but attitudinal segmentation has traditionally been difficult to execute.
With consumers, we have traditionally segmented by communication preference as well as by attitudinal segmentation, which creates even more challenges than communicating with HCPs. Why? The industry has often been inconsistent in how it communicates with HCPs and consumers. One example for how to evolve to this more customer-centric engagement model: start by looking at primary care providers’ needs in general and then looking at relevant brands as opposed to starting with brands and then looking at specialties. We must look for consistent customer needs across therapeutic areas.
It Doesn't Count...Unless You Count
Even today, data and metrics frequently become an afterthought to strategy and experience creation. To help us make informed decisions, any future engagement model must define the data strategy before data is even in hand. We must think beyond market research and include more unstructured data to better inform customer experiences.
Any engagement model a pharma company deploys must seamlessly address translating strategy—customer engagement, the brand, and the company—into execution. It’s not as easy as it sounds. Many times, the strategy doesn’t make it all the way to execution. In cases where outcomes do not materialize as planned, it’s then very difficult to parse: “Was this failure due to poor strategy or poor execution?” Strategic planning remains critical to ensuring everything remains connected.
The Goal: A New Model
What your future model will look like is, of course, up to you and your teams. Regardless of its specific makeup, any strong model will provide customers with a seamless experience across a company’s portfolio and with its brand. Those deeper experiences will come from data-driven decisions, science-driven content, and touchpoints that build upon each other to meet the ultimate goal: greater loyalty.