Customer Sentiment Analytics
A centralized AI-powered intelligence platform that transforms multi-channel customer feedback into actionable product and business insights.
Partnership Goal
→ Build a unified system that aggregates feedback from all customer touchpoints and uses AI to surface sentiment trends, root causes, competitive gaps, and improvement opportunities in near real time.
Service
Custom AI Web Application
Overview
Product name is a placeholder as it is covered under NDA.
Feedback Intel is an AI-enabled analytics platform built for a large manufacturing organization receiving customer feedback across multiple channels. Previously, feedback data was fragmented, reactive, and difficult to interpret at scale.
The platform consolidates reviews, support interactions, and social signals into a single intelligence layer, enabling leadership and product teams to understand sentiment, identify pain points, track improvement impact, and benchmark against competitors.
Scope:
Challenge
Customer feedback existed across reviews, support channels, and social platforms, but there was no unified, structured way to analyze it at scale. Teams struggled to move from raw feedback to consistent, actionable insights.
Feedback scattered across multiple channels
No unified sentiment or performance view
Manual analysis of large feedback volumes
Difficulty identifying recurring issues
Limited understanding of emotional drivers
No visibility into competitor sentiment
Reporting required manual consolidation
Solution
We designed an AI-assisted customer intelligence platform that continuously ingests feedback, analyzes it across multiple dimensions, and delivers role-specific, decision-ready insights.
• Centralized feedback ingestion from: - Google reviews - App stores - Live chat transcripts - Support tickets - Social media - Email feedback • Role-based dashboards for leadership and product owners • Overview dashboard with 7, 14, 30, and 90-day analysis windows • Sentiment scoring with confidence trends over time • AI-driven insights and alerts • Channel health classification into healthy, warning, and critical • Topic Explorer analyzing themes such as: - Delivery and returns - Pricing - App performance - Product quality, color, and fit - Packaging and payment options • Emotion analysis categorizing feedback into: - Joy, Trust, Satisfaction - Confusion, Frustration, Anger, Sadness • AI-assisted root cause analysis across topics and emotions • Competitor benchmarking using publicly available review data • Executive reports with AI-generated summaries and recommendations • Conversational AI assistant for natural language exploration of insights
Process
Team
- 1 Product Manager
- 2 Full-Stack Developers
- 1 AI/NLP Engineer
- 1 Data Analyst
- 1 UX Designer
Technology Stack
Frontend
Backend
Database
AI & Intelligence
Authentication & Security
Data Processing
Infrastructure
Multi-channel feedback source mapping
Identified and integrated all customer feedback sources across the organization.
Custom NLP pipeline design for domain-specific analysis
Built specialized NLP models tuned for manufacturing and product feedback context.
Topic and emotion taxonomy definition
Created a structured taxonomy for categorizing feedback themes and emotional responses.
AI model tuning for sentiment and root cause detection
Fine-tuned models to accurately detect sentiment polarity and identify root causes.
Dashboard and reporting design for fast decision-making
Designed intuitive dashboards that surface actionable insights for different stakeholders.
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Outcome
The platform established a single, trusted source of customer intelligence and enabled faster, data-driven decisions across product, quality, and leadership teams.
Unified Customer Voice: All customer feedback is now centralized, searchable, and analyzed through a consistent sentiment, topic, and emotion framework.
Faster Insight to Action: AI-assisted alerts and root cause analysis enable early detection of emerging issues and quicker corrective action.
Stronger Product Decision-Making: Product owners gain clarity on priority improvement areas, feature performance, and customer expectations.
Competitive Intelligence: Leadership has continuous visibility into how customer sentiment and experience compare against key competitors.
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