Clients we Helped
Case Studies
Case Study 1: Pharmaceutical Industry - Enhancing Patient Feedback Analysis
Client: Global Pharmaceutical Company
Challenge: A pharmaceutical company was struggling to analyze patient feedback from various clinical trials. They needed a way to quickly assess patient sentiment, identify trends in drug efficacy, and detect any emerging issues from unstructured survey data.
Solution: Mindtron implemented its AI-powered survey analytics tool to process and analyze thousands of qualitative responses. Using sentiment analysis, topic modeling, and anomaly detection, the tool identified key concerns related to drug side effects and patient adherence.
Results:
- 30% faster analysis time for feedback processing.
- Identified a 12% uptick in patient-reported side effects, enabling the company to make targeted adjustments to clinical practices.
- Improved patient satisfaction by addressing concerns more rapidly.
Client: Leading Home Appliance Retailer in the Balkans
Challenge: The client wanted to understand customer satisfaction trends across different regions and product categories but lacked the tools to analyze large volumes of text responses in real-time.
Solution: Mindtron’s text analysis and comparative analytics tools were deployed to examine customer feedback from product surveys. The AI identified sentiment shifts and pinpointed areas where specific product categories underperformed. Comparative analysis enabled the retailer to track improvements across various time periods and regions.
Results:
- Customer satisfaction scores improved by 15% after making data-driven product adjustments.
- Increased regional sales by 10% through better targeting of consumer preferences.
- Real-time sentiment tracking led to quicker responses to negative feedback.
Case Study 2: Retail Sector – Optimizing Customer Satisfaction with Sentiment Analysis
Case Study 3: SaaS ERP Company – Employee Engagement and Profiling
Client: International SaaS ERP Provider
Challenge: The client wanted to better understand employee engagement and detect early signs of dissatisfaction that could lead to higher turnover. They needed a solution capable of analyzing employee survey responses at scale while providing clear, actionable insights.
Solution: Mindtron’s employee profiling and causal analysis features were used to create detailed respondent profiles. By applying explainable AI (Shapley values) and clustering algorithms, Mindtron helped the company identify the primary factors affecting employee satisfaction and engagement.
Results:
- Reduced employee turnover by 18% after addressing key factors of dissatisfaction.
- Enhanced employee engagement scores by 22%, resulting in higher productivity.
- Generated actionable insights that helped the HR team develop targeted employee wellness programs.