This project focused on building an internal marketing intelligence platform designed to collect, analyze, and structure large volumes of online data for competitive and brand monitoring purposes.
The platform supports marketing teams by transforming unstructured web content into actionable insights through automated data collection and analysis.
The solution is used in the context of global fashion and consumer brands, supporting data-driven decision-making at scale.
Marketing and analytics teams required a scalable system capable of continuously scanning large sets of websites and identifying predefined keywords, topics, and brand-related signals.
The platform needed to process high data volumes reliably while presenting insights through clear visualizations and reports.
We designed and implemented a distributed scraping and analytics platform built on a microservices architecture.
The system continuously collects data from multiple sources, processes it through message queues, and indexes results for fast querying and analysis.
Collected data is transformed into visual dashboards and statistical reports, enabling marketing teams to identify trends, monitor brand presence, and support competitive analysis workflows.
Automated brand and market monitoring, replacing manual research
Faster insight generation through real-time dashboards and analytics
Scalable data pipeline supporting continuous data collection
Improved decision-making for marketing teams analyzing global brands