Data Scientist – a dream you should have
Successfully face today's technology challenges: a quick guide to Data Science solutions
If you've been looking for an article that goes beyond the standard definitions of Machine Learning, Artificial Intelligence, and Marketing Analytics, then you've come to the right place. This blog offers so much more.
During the next few minutes, you'll not only learn about how a Data Scientist operates in a company operating in a specific market, such as pharmaceuticals, but you will also get a glimpse of new technology solutions developed to create tangible value for customers.
A day as a Data Scientist – what to expect?
The Data Scientist and his/her Team must have extraordinary observational skills starting with visualization, analysis, and exploration of data to develop strategies and create models for interpreting the said data, by leveraging the use of programming languages and eventually AI.
Trueblue's Data Scientist Team works every day to meet the specific needs of our customers and proactively identify the possibility of anticipating future issues through data analysis. This allows us to provide solutions that combine artificial and human intelligence, ensuring predictability, proactivity, and, as a result, higher customer satisfaction.
This is consolidated by a rigorous testing process and a parallel and constant internal alignment aimed at gathering feedback from various business stakeholders, thus ensuring a 360-degree view and collaborative approach.
Our approach – Creating value with innovative solutions
The approach described above has enabled us to simplify some/most business processes of pharmaceutical companies. Let's take a closer look at them together:
– Smart Customer Engagement: to optimize communication between Rep or MSL and doctors, we studied the most useful datasets of information able to identify and suggest relevant, personalized, and therefore most effective interaction opportunities;
– Go-to-Market: by using approaches based on market share and competitive analysis, we have developed a model that can identify products with high market potential. This model provides in-field insights that help identify opportunities to increase market share and support content recommendations and up-sell strategies;
– Actionable Insight: by developing specific AI & Machine Learning algorithms we were able to implement a system of relevant and personalized recommendations both at an interaction level with customers and suggested content.
AI and Chat GPT – the synergy we couldn’t wait to see
The integration between ChatGPT and AiDEA Suite has significant potential for the pharmaceutical industry for a variety of reasons. Here are some of them.
Firstly, the chance to optimize one's activities through simplified search of relevant information from medical/scientific documentation. Secondly, the generation of contextualized summaries on specific topics, e.g. Clinical Trial. Finally, the automated creation of communications targeted and pertaining to previous research. All of this makes it possible to address complex challenges such as processing large amounts of data, identifying significant patterns and trends, and generating innovative solutions to improve communication with health professionals, patients, and caregivers.