At a Glance
- The South Korean automotive OEM struggled to process vast online data to identify vehicle issues and understand customer sentiment in real time.
- Tata Elxsi’s AI-powered tool provided real-time social media and web data analysis, featuring NLP, customizable dashboards, and competitor benchmarking.
- Achieved a 40% reduction in issue resolution time, a 20% increase in customer satisfaction, and enabled proactive issue detection, significantly enhancing product quality and strategic decision-making.
Background
For a top South Korean Automotive OEM, Tata Elxsi’s snazzy Web Data Mining Tool uses NLP magic to dive into social media buzz, visualising sentiment, competitor snapshots, and customer tips.
It provides deep insights into vehicle part performance and customer satisfaction.
The AI Solution
Data Ingestion
The AI-powered Web Data Mining Tool supports both online and offline data extraction, ensuring comprehensive coverage of relevant data sources. It seamlessly collects data from various platforms, including social media, forums, blogs, and internal databases. This robust data ingestion capability ensures that the tool captures a wide array of customer feedback and industry insights.
NLP for Sentiment Analysis
Natural Language Processing (NLP) is at the heart of the tool’s sentiment analysis feature. The NLP engine meticulously processes customer feedback, extracting valuable information and identifying key issues and observations. The tool highlights areas requiring immediate attention and action by analyzing sentiments expressed in social media posts, reviews, and comments. This sentiment analysis provides a nuanced understanding of customer perceptions and experiences, enabling proactive measures to enhance satisfaction.
Dashboard Delight
The tool organizes the analyzed data into user-friendly dashboards and detailed reports. These dashboards present a clear and concise visualization of the results, making it easy for users to interpret and act upon the insights. Key metrics, trends, and comparisons are displayed in an intuitive format, facilitating informed decision-making. The customizable dashboards can be tailored to meet the specific needs of different user roles within the organization.
Full-Spectrum Analysis
The Web Data Mining Tool offers full-spectrum analysis, covering essential vehicle parts such as electronics, horn, infotainment system, sound system, clutch pedal, and manual transmission (MT) lever. This comprehensive analysis ensures that all critical components are monitored for performance and customer satisfaction. By identifying trends and potential issues across a wide range of parts, the tool helps the OEM maintain high standards of quality and reliability.
Role-Based Access
Security and access control are paramount in the design of the tool. It features role-based access, ensuring that users have appropriate permissions based on their responsibilities and requirements. This secure access framework protects sensitive data while enabling efficient collaboration among team members. Different user roles, such as engineers, analysts, and managers, can access the specific data and insights they need to perform their tasks effectively.
Tech Stack
- Data Engineering: Spark, Python
- Data Lake: Elastic Search
- AI Model: NLP Engine
- Hosting: Hosted in machine using Ubuntu Docker (Windows 10 Host)
Impact and Results
- The AI powered Web Data Mining Tool has the OEM’s ability to track and resolve vehicle part issues by 50%, has reduced resolution time by 40%
- Deftly extracts data from up to 42 websites
- Visualised customer sentiment and trends enabled 35% swift issue identification, 25% increase in part improvement efficiency, and boosted customer satisfaction
- The tool’s slick export feature transformed insights into management-friendly reports, ensuring data-driven decisions