The Challenge
Businesses often struggle to manually track competitor pricing, feature updates, and customer sentiment across multiple platforms. This fragmented data leads to delayed strategic decisions and missed opportunities in the market. The goal was to build an automated pipeline that ingests messy web data and outputs clean, structured strategic insights.
The Solution
I developed a Python-based scraping engine combined with OpenAI's GPT-4 API to categorize sentiment and extract feature requests from thousands of user reviews. The data is visualized in a real-time Streamlit dashboard, allowing stakeholders to instantly see where they stand against the competition.
Project Details
Reduced analysis time by 85% and identified 3 key product gaps.
Visuals
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Real-time Sentiment Dashboard
Data Processing Pipeline
Network Graph of Competitor Relationships
Development Process
Data Collection
Implemented Scrapy spiders to gather 50k+ reviews from G2, Capterra, and TrustRadius.
NLP Analysis
Utilized BERT models for initial topic modeling, refined by GPT-4 for nuance detection.
Visualization
Built an interactive dashboard enabling filters by competitor, date range, and feature set.