Brand Perception Analytics at Scale
Aspect-Level Sentiment from Millions of Reviews for Investment Decisions
The Challenge
Investment teams at a private investment company needed to understand brand perception as part of their due diligence process. Manually reading and synthesizing millions of online reviews across multiple brands and markets was impossible. They needed an automated way to extract structured brand intelligence — strengths, weaknesses, and sentiment trends — to support investment thesis formation.
Our Approach
We built a large-scale NLP pipeline to ingest and process millions of online reviews across brands and markets. The pipeline handled deduplication, language detection, and noise filtering to ensure high-quality input for the analysis stage.
Aspect-based sentiment analysis was implemented to go beyond overall sentiment scores. The system identified specific product and service aspects mentioned in reviews (e.g., quality, customer service, pricing, reliability) and extracted sentiment for each aspect separately.
Results were aggregated into brand intelligence dashboards showing sentiment trends over time, competitive comparisons, and drill-down capabilities to individual review clusters. This gave investment teams a clear, data-backed view of brand positioning.
The product was integrated into the same platform as the investment knowledge assistant, making it accessible within the teams' existing daily workflow. Dozens of investment teams used the analytics to complement traditional due diligence with consumer-sentiment data.
The Results
Consumer sentiment became a quantified input to the investment thesis rather than a gut feel. Teams could compare brand perception across competitors, track sentiment shifts over time, and back their convictions with data — all without adding any research headcount.
Millions Reviews Analyzed
Multi-aspect Aspect Extraction
Dozens of teams Daily Users
Technologies Used
Ready to build something similar?
Let's discuss how we can apply these approaches to your specific challenges.
Get in Touch