Transforming IT Ticket Analysis with Sentiment Insights for Enhanced Service Quality
Client Overview
A leading global investor services group specializing in providing a comprehensive range of consulting solutions for alternative assets and corporate services. With a robust presence in the financial sector, the firm helps clients manage risk, optimize returns, and navigate complex regulatory landscapes. Their clientele spans across a diverse range of industries and sectors, and the firm prides itself on delivering high-quality, bespoke services designed to support their clients' financial strategies and long-term objectives.
Overcoming Fragmented Ticket Insights and Improving Customer Satisfaction
The organization is committed to providing exceptional service to clients across various sectors by leveraging innovative technologies to manage risk, optimize returns, and navigate regulatory complexities. The client sought to transform its IT ticket management system by integrating sentiment analysis and automation to maintain operational efficiency and stay competitive in a fast-evolving landscape.
Improve Customer Satisfaction and Service Quality
Implement sentiment analysis to classify IT service tickets based on emotional tones, identifying areas for improvement, and ensuring prompt resolution of customer issues.
Automate Ticket Classification and Assignment
Develop an automated system to categorize and assign IT tickets to the appropriate team based on sentiment and ticket content, reducing manual intervention and streamlining workflows.
Extract Relevant Data from Emails
Implement a solution to automatically extract and analyze key data from email communications for deeper insights into customer sentiment.
Enable Real-Time Insights
Provide a platform for real-time analysis and visualization of sentiment trends and service quality to help teams make quicker, more informed decisions.
Boost Operational Efficiency
Streamline ticket resolution processes, minimizing response times and maximizing team productivity by automating routine tasks and workflows.
Support Future Growth and Scalability
Build a scalable solution that can accommodate future increases in ticket volume, ensuring long-term adaptability and flexibility for the client’s evolving needs.
AI-Driven Sentiment Analysis and Automation Streamline Ticket Management and Response
Indium developed an AI-driven solution that utilized advanced natural language processing (NLP) and machine learning models to classify and analyze email sentiments automatically. Here's how the solution was implemented:
Sentiment Classification
Leveraged keyword-based and non-keyword-based methods using large language models (LLMs) for sentiment analysis. By employing machine learning and lexicon-based approaches, the system could determine the polarity of the text, whether positive, negative, or neutral, along with emotional insights like happiness, frustration, or dissatisfaction.
Data Extraction
Utilized Python libraries such as BeautifulSoup and lxml to parse HTML documents and extract the relevant content from specific tags in the customer emails. This allowed the system to process and categorize incoming emails for further analysis automatically.
Ticket Categorization
The emails were classified into internal and external categories, ensuring that the right team would receive the ticket. By automating the ticket assignment process, the solution minimized manual intervention and ensured faster response times to critical issues.
Power BI Dashboard
To enable trend analysis and reporting, Indium developed an interactive Power BI dashboard. This dashboard provided a user-friendly interface for visualizing sentiment trends, email volumes, and emotional tones, empowering stakeholders to identify service gaps and improve response strategies.
Automated Assignment
Based on sentiment analysis and ticket categorization, emails were automatically assigned to the appropriate team for further investigation or resolution. This automation helped reduce response times and ensured that critical issues were prioritized.
Indium Boosted Operational Efficiency and Identified Service Gaps
Volume Analyzed
Over 500,000 emails analyzed across 11,000 customers.
Negative Sentiment Identification
The system identified that 2% of the emails contained negative sentiment, highlighting areas that needed immediate attention.
Improved Efficiency
The automated system led to faster categorization, improving response times and reducing manual intervention by support teams.
Customer Satisfaction
The solution enabled the organization to proactively address dissatisfied customers, enhancing the quality of service and fostering greater client trust.
About Indium
Indium is an Al-driven digital engineering company that helps enterprises build, scale, and innovate with cutting-edge technology. We specialize in custom solutions, ensuring every engagement is tailored to business needs with a relentless customer-first approach. Our expertise spans Generative Al, Product Engineering, Intelligent Automation, Data & Al, Quality Engineering, and Gaming, delivering high-impact solutions that drive real business impact.
With 5,000+ associates globally, we partner with Fortune 500, Global 2000, and leading technology firms across Financial Services, Healthcare, Manufacturing, Retail, and Technology-driving impact in North America, India, the UK, Singapore, Australia, and Japan to keep businesses ahead in an Al-first world.
