Updated: Nov 21, 2021
The covid pandemic has created a big change in the consumption habits of customers as well as the way businesses operate. In the pharmaceutical industry, leaders are also facing a rapidly evolving commercial landscape. To overcome the disruption of customers and products during the pandemic, it is necessary to change the approach to customers. Innovative strategies and technologies to navigate product, customer and pandemic-driven disruptions across the industry will be the path forward.
There are many reasons for the issue. The introduction of new products, increased competition, or loss of exclusivity. Along with that is a huge demand for information from customers and distributors. Not to mention the ever-growing role of the patient in managing their care. In the context of the covid epidemic, changing the way to approach customers in the pharmaceutical industry.
There is no doubt, we must strengthen our commercial practices to address these changes. To meet our customers where they are and deliver maximum value, data and technology-enabled engagement models must be central to our approach. This article recommends three areas that will accelerate a strategic approach to successful customer engagements.
Orientation Customer engagement
The customer journey plays an important role in any marketing strategy, especially online strategies. With up to 80 percent of the customer journey taking place online, changing the customer approach model is imperative for pharmaceutical companies. However, moving from a multichannel to a true omnichannel model requires new tools and skills to help orchestrate, and improve, the customer experience.
By using data analytics and machine learning, we can up-level up our customer engagement strategies and meet our audiences where they are online with effective, high-impact messages through targeted channels. The coordination of touchpoints across channels and functions becomes increasingly important. Having a tool, or set of tools, to help orchestrate customer engagement breaks down silos between teams that touch the same customer—from account managers to sales representatives to marketing teams—and facilitates a deeper understanding of customer preferences.
Deliver a Strong Customer Value Story
The increasing role of the patient in their care is pushing manufacturers to move beyond providing patient education to offering patient solutions. Customer value needs to be specifically redefined by each type of customer, including patients, providers, and payers. Through strategies such as the alignment of brand strategy and customer strategy, access to hospital de-identified patient data, remote monitoring or diagnosis, and patient support programs, pharmaceutical companies can remain agile and provide a strong value proposition across customer sets.
Over the past several decades, many hospitals have adhered to the policy that sharing unidentified data is unethical. So far is showing the potential of this to better understand disease progression, treatment efficacy, and complications. There is a new focus on sharing data and targeting drug discovery to improve future care. Another example of delivering added value programs such as virtual resources that help make the first step on solving patient problems journey a little easier.
Artificial intelligence helps pursue actionable insights
A series of assessments, aggregating requests with appropriate tool support. Artificial intelligence (AI) is the backbone to deploying true omnichannel customer experiences. By offering a 360-degree view of customers, machines can drive modeling for regional approaches, and ultimately provide actionable insights for pharmaceutical companies to fold into their commercial models.
However, AI integration is not a one-size-fits-all approach and each company operates differently. The efficacy of the technology, and how exactly it can serve life sciences, commercial teams, will differ between companies. So, the first step we must take is to understand AI and the value it can bring to our specific organizations. Then, we will be well-positioned to identify the exact problem we are looking for AI to solve so we begin the process of implementing it into our operations. We need to correctly identify the problem to start the implementation process as well as develop the next strategy.