Comments Analytics Suite is an AI-powered toolset designed to extract, analyze, and interpret consumer feedback from video comments, social posts, product reviews, and more. It helps you understand customer thoughts, emotions, motivations, and needs by delivering clear insights through sentiment analysis, keyword extraction, and category classification. The platform emphasizes no-code usability, scalable analytics, and customizable inference models for diverse websites and languages.
How it works
- Collect comments from various platforms (YouTube, social media, product pages, etc.).
- Apply NLP models to extract sentiment, keywords, entities, and topics.
- Generate structured insights, visualizations (e.g., word clouds), and actionable reports.
- Export insights as text or reports and integrate with business workflows.
Core Capabilities
- Sentiment Analysis: Contextual mining to determine emotional tone of comments and track brand/product sentiment over time.
- Keywords Extraction: Identify and surface the most important words and phrases driving discussion; supports word clouds and topic detection.
- Named Entity Recognition (NER): Locate and classify entities mentioned in unstructured text (people, organizations, products, etc.).
- Predict Customers' Needs: Anticipate future customer needs based on feedback patterns and trends.
- Category Extraction: Automatically categorize comments into predefined topics for streamlined analysis.
Key Features and Tools
- No-Code Analytics: Pre-built models with easy import/export, enabling rapid insights without coding.
- Multi-Source Ingestion: Analyze comments across video platforms, social posts, product pages, and more.
- On-Demand SaaS Delivery: Scalable cloud-based service with flexible usage.
- Localized NLP: Supports multiple languages via NLP models for broad audience coverage.
- Real-Time Handling: Designed to scale to many requests with fast processing.
- Custom Inference Models: Tailor models to specific websites and data sources.
- Visual Insights: Word clouds, topic clusters, and summarized reports for quick decision-making.
- 24/7 Support and Guidance: Access to dedicated managers, engineers, and tailored analyses.
Use Cases
- Understand customer sentiment toward products and campaigns.
- Identify recurring issues and areas for product improvement.
- Track trends in customer needs and expectations over time.
- Benchmark brand reputation across platforms.
Data & Delivery Details
- Input: Comments from videos, posts, reviews, and other text sources.
- Output: Clean insights, categorized topics, sentiment trends, and customizable reports.
- Privacy & Security: (Not specified in provided content; consult vendor for details.)
Language and Analytics Coverage
- 23 languages supported in NLP model suite (multi-language capability highlighted).
- Overview explains 36.5 trillion paragraphs trained and 500 million keyword phrases extracted as part of the analytics depth (runtime figures from the content).
Pricing, Tutorials & Support
- Pricing and tutorials available via the platform’s pricing blog and tutorials sections.
- Contact options include a general inquiries channel and terms/privacy policy references.
Accessibility and Integration
- Chrome extension availability mentioned for easier data extraction from web pages.
- No-code export/import options to integrate insights into existing workflows.
Safety and Compliance
- The description emphasizes valuable and actionable insights for business improvements but does not specify data storage or privacy guarantees; verify with provider.
What Makes It Stand Out
- End-to-end comments analytics with sentiment, keywords, entities, and category extraction.
- Scalable SaaS model with no-code usability and customizable inference models.
- Rich visualization and reporting to inform product, marketing, and customer experience strategies.
Core Features
- Sentiment Analysis
- Keywords Extraction
- Named-Entity Recognition (NER)
- Predict Customers' Needs
- Category Extraction