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NLP Solution For Pharmaceutical Marketing

Azati developed a unique AI and Computer Vision-based solution to help pharmaceutical companies generate assessment reports based on insights from medical practitioners. The solution automates the process of analyzing questionnaires and provides valuable data for enhancing pharmaceutical marketing strategies.

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All Technologies Used

Python
Python
MongoDB
MongoDB
Metabase
Metabase
Google Cloud
Google Cloud

Motivation

The goal of the project was to create an MVP that uses AI and Machine Learning technologies to build assessment reports for pharmaceutical companies. The reports would be based on questionnaires and insights from doctors, helping the companies enhance trust in their products and improve marketing strategies. The challenge was to make the process of comparing pharmaceutical products easier and more informative for both professionals and consumers.

Main Challenges

Challenge 1
Tool Efficiency

The project was complex and the available tools were insufficient during the initial stages of development. This led to the involvement of an expert consultant (a Doctor of Science) to guide effective approaches, which helped Azati overcome the initial challenges.

Challenge 2
Report Structuring

The reports had to be clear, structured, and easy to read for all users, regardless of their familiarity with the content. Azati developed a custom system to classify and sort the results based on calculated ratings, ensuring that the final reports were easily digestible.

Key Features

  • AI-Driven Data Analysis: The solution uses AI and NLP to process medical questionnaires, automatically identifying insights and generating reports. This allows pharmaceutical companies to better understand what doctors think about their products and how to improve marketing strategies.
  • Report Generation and Sentiment Analysis: The system can analyze responses from medical professionals, correlate their insights with the pharmaceutical company’s marketing strategies, and generate detailed reports that highlight the most important feedback.
  • Customizable Categorization: Azati’s solution allows for the automatic classification and grouping of data based on thematic relevance, making it easier to understand trends in doctor feedback on different aspects of pharmaceutical products.
  • Data Visualization Tools: The reports are presented using advanced data visualization techniques, ensuring that stakeholders can easily interpret the results and apply the insights to improve marketing strategies.

Our Approach

Initial Analysis and Solution Design
Before starting the project, Azati successfully passed a test task and proposal process. The project used an Agile methodology, allowing close collaboration with the client to develop a solution that met their expectations.
Data Standardization
The first challenge was to bring input data into a standardized format that could be processed by AI algorithms. Azati solved speech-to-text recognition issues and prepared the data for NLP processing by handling punctuation, capitalization, and domain-specific terms.
NLP Data Analysis
Azati applied NLP techniques to analyze input text, identify common phrases, and segment the responses by topic. Sentiment analysis was performed, and scores were calculated to assess the relevance of each phrase.
Data Grouping and Reporting
The next step involved grouping the analyzed data into thematic reports. These reports highlighted key aspects of the responses from doctors, such as opinions on product effectiveness, safety, and usage.
Visualization and Sharing
Finally, Azati focused on finding a simple and intuitive way to visualize and present the reports. The solution was designed to be easily shared with stakeholders and customers, providing actionable insights into the effectiveness of pharmaceutical marketing strategies.

Project Impact

Azati successfully delivered a solution that automates the process of analyzing medical questionnaires and provides pharmaceutical companies with actionable insights to improve their marketing strategies.

By using AI and NLP to evaluate feedback from medical practitioners, pharmaceutical companies can better tailor their products and campaigns, increasing trust among consumers and improving sales outcomes.

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