Enhancing automotive industry insights through advanced monitoring by XDAS

The business need

Our client, a prominent B2B market research firm specializing in the automotive industry, faced the challenge of efficiently monitoring and analyzing vast amounts of news articles related to the sector. With multiple divisions dedicated to different sectors, they aimed to enhance their insights specifically within the automotive supply chain.

The key objectives included classifying news articles, extracting relevant entities, and establishing a structured repository for data storage and lineage to facilitate deeper analysis and strategic decision-making.


The challenges our client encountered revolved around:

Classification of News Articles

The need to categorize articles under various topics relevant to the automotive industry to enable focused analysis.

Entity Extraction

Identifying and extracting entities such as companies, organizations, individuals, and events mentioned within the articles to gauge their impact on the industry.

Data Storage and Lineage

Establishing a structured repository to store classified news articles along with their lineage of events against mentioned entities for further research and analysis.

Tackling these challenges will allow the client to remain updated on advancements within the automotive sector, pinpoint emerging trends, and execute informed strategies to propel business expansion and attain market dominance.

How we solved the problem

Our XDAS data team embarked on a comprehensive solution to address the client's challenges:

Aggregation of Sources

We identified and incorporated over 8000 RSS sources and developed assets to convert search query results into XML feeds, laying a robust foundation for content aggregation.

Source Monitoring Workflow

A dedicated workflow was configured to continuously fetch articles from around 50,000 news sources using a feed extractor, ensuring a steady stream of relevant content.

Machine Learning Classification

An ML model asset was constructed to classify articles based on predefined categories, enhancing analysis capabilities and enabling targeted tracking of industry trends.

Entity Extraction

We employed Spacy NER (Named Entity Recognition) model assets to extract entities mentioned within the articles, including companies, organizations, individuals, and events, thereby providing a comprehensive understanding of industry influencers.

Event Chronology

Meticulous recording of event chronology using published dates and event categories enabled the client to trace the lineage of events over time, facilitating deeper analysis and trend identification.


Through our XDAS solution implementation, our client achieved significant outcomes:

Systematic News Monitoring

  • The client gained the ability to systematically monitor news articles, ensuring they remained abreast of developments within the automotive industry.

Enhanced Analysis Capabilities

  • Classification of articles under relevant topics, extraction of key entities, and meticulous event chronology storage empowered the client to conduct in-depth analysis and derive actionable insights.

Informed Decision-making

  • Armed with comprehensive insights, our client could make informed decisions and strategic plans to drive business growth and maintain market leadership within the automotive sector.

  • By leveraging advanced media monitoring techniques and cutting-edge technologies within the XDAS platform, we enabled our client to stay ahead in the dynamic automotive industry landscape, transforming data into actionable intelligence for sustained success.

Looking out for a similar solution?

© 2024 Xtract.io Technology Solutions Pvt Ltd | All Rights Reserved | A Mobius Venture.

© 2024 Xtract.io Technology Solutions Pvt Ltd | All Rights Reserved | A Mobius Venture.