Analysis of Pharmaceutical Call Center Records

The analysis of call center log data presents opportunities for pharmaceutical companies to improve operations along several fronts, including administrative services, adverse event monitoring and reporting, and product quality control. Recently, Melax Tech worked with a major pharmaceutical company to demonstrate the value that an AI-assisted analysis of their call center records could provide. Traditional call center systems are focused on note-taking and performance of call center staff. To glean deeper insights into the data, systems supporting logical inference, such as those that can be constructed with Artificial Intelligence and Natural Language Processing (NLP), are required.


To conduct the call center analysis, we analyzed tens of thousands of notes collected from the customer call center support system. Our experienced team of NLP and machine learning scientists reviewed the data and created an AI-assisted classification system for the data. We were consequently able to capture a rich set of variables including topic category, geolocation, timestamps, occupation of the reporter (the person seeking help from the call center), and so forth. The resulting data demonstrated major opportunities to improve:

  • Product quality control

  • Call center operations

  • Fraud detection

  • Improved data collection and reporting

  • Medication shipment improvement

Consequently, we developed interactive dashboards, such as the one shown below, to support management in improving these areas.

Interactive dashboard with data filtering options to visualize the call center distributions using a geo heat map, number of records using a line graph, and requester types using bar graphs.

The Melax Tech team was able to conduct this analysis because of our strong background in clinical NLP and AI, as well as our senior-level analysts who are familiar with all facets of the life sciences and pharmaceutical industry.


If you need to analyze text-based data, Melax Tech can help. Our team is comprised of senior-level software engineers, senior-level NLP and AI scientists, and analysts with years of industry experience.