In a way, machine learning is a consequence of the evolution of AI. The latter element is growing in more than one direction. More than one business area is taking advantage of the benefits of artificial intelligence. Yet what kind of impact can this have on pharma? Let’s have a look at the possibilities.
What is Machine Learning?
For many people online, “Machine Learning” may sound more like a buzzword. This notion started spreading around as the idea of “big data” started to become a topic.
We’re entering an era in which many activities will be driven by the data that they are “fed”. In this sense, the computer can mimic some logical and human actions.
All this is based on observations and real-world interactions. What AI allows in this scenario is the ability to learn and improve from experience automatically. All this with minimal programming.
In the case of machine learning, when you give computer systems access to great amounts of data, this technology can learn from itself. What the machine does is look for patterns within the data to make future decisions.
This is driven by various processes of data observation. After processing the data, the goal is to generate an automatic process with little to no human intervention.
The main catch of Machine Learning for Pharma
Many business categories are adopting new technologies in an era defined by big data. In fact, many actions are driven by analytics and technology, through this very same data.
In pharma, like many business areas, the possibilities are more and more varied. Moreover, healthcare as a whole has data generated from a variety of sources. Among them, we can name the R&D process itself, along with other players in the sector such as retailers, patients, and caregivers.
There are many possibilities for pharma through the implementation of the model of machine learning. Among them, we can point to possibilities such as:
- Creating a predictive model of biological processes;
- More data that will help patients to enrol in modern models of clinical trials;
- An improved monitoring model of patient conditions in real-time;
- Improved capturing of medical data from several sources to improve investigation quality.
However, these are, for the time being, possibilities that may come to light as this technology evolves. In the present day, there’s no denying that AI and Machine learning are benefitting many areas in pharma.
Sales and marketing teams can benefit from the features of machine learning. Among the most relevant advantages we can point to:
- The increase in productivity;
- The simplification of many sales processes;
- Enhancement of cross-team cooperation;
- Providing information that can better prepare sales teams in many contexts.
Some pharma companies have already tried implementing machine learning in their workflow. Many are beginning to see the potential that this technology will have, as it evolves.
However, in what sense can this be a potential ally for pharma sales? How can pharma reps benefit from this technology? Let’s analyze this at a deeper level.
The influence of Machine Learning on Pharma Sales
The possibilities provided by machine learning are endless as this technology evolves. Among them is the option of using this technology to create a personalized relationship with several stakeholders.
“Sales reps” have on many occasions been seen as representatives of a pharma company. For years, their task was with handling customer relationships with a particular focus on sales.
However, due to the growing trend for remote work environments driven by new technologies, old sales tactics are not doing the trick like they used to. The needs of many stakeholders that pharma reps interact with are different now.
What does this mean for sales reps’ jobs in the coming years? How can Machine Learning benefit and transform their work for the best?
Pharma Reps can become advisors
The secret to the success of pharma reps’ jobs is all about relationship building. The concept in it is timeless. Yet the ways to do it not so much.
Not only do sales reps need to be knowledgeable about their products, but now they need to know about the state of the market with their competitors. They are also indirectly required to know a little more about illnesses and diseases, as well as procedures to handle these conditions.
In a sense, they have to also know specific details about the stakeholders they interact with. Elements such as who they are, what they work on and their knowledge in medical matters are relevant to this relationship.
So how can machine learning help them with that? Simple: by providing them with a summary of personalized data.
AI can analyze a great amount of data focused on several individuals. Several factors may come to mind. Including a physician’s prescribing habits, the demographics of the area the physician serves, and what pharmaceuticals other physicians within the same speciality are using.
Through the relevant details surrounding that person, it can provide a personalized recommendation. Pharma reps will become more aware of the type of content that impacts a particular individual.
This will leave them more prepared and confident in case of a remote or in-person meeting. Not only that, but they can also instruct a marketing or content creation team to create elements that cater to their audience’s needs.
It can act as a guide for pharma reps
In general, salespeople tend to act independently. But considering the new era, we’re in, even they can’t be indifferent to the impact and importance of big data.
Of course, AI comes off as a great advantage to them in this sense. By providing them with personalized advice on how to proceed with different physicians, they can save a lot of time in meetings on procedures with potential clients.
In a way, the AI technology can act as a guide for each sales rep. All this by providing new data based on previous performances and the needs of each stakeholder.
Machine learning can save time for reps
Paperwork is the type of procedure that nowadays is very time-consuming. However, in the case of pharma reps, this takes time away from developing proper relationships with physicians.
This is another solution that machine learning can provide for them. By entering the data into CRM (customer relationship management) system, they will be able to organize data faster. Not only that, but the system will also process these details into an AI tool that has machine learning capabilities.
Machine learning can benefit pharma reps in more than one sense. However, for the relationships to prosper, the content will be key in this game. And video content will hit the spot for many physicians.
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