Comments Analytics: An Overview

Comments Analytics is an advanced platform designed to extract and analyze comments from diverse sources, including web pages, social media posts, and videos. By leveraging AI-powered technology, it provides insightful data on customer thoughts, emotions, motivations, and decision-making processes, making it an invaluable tool for businesses seeking to understand their audience better.

Comments Analytics: Main Features

1. Sentiment Analysis: Analyzes comments to extract subjective information and emotions, revealing the social sentiment surrounding a brand or product.
2. Named Entity Recognition: Identifies and classifies named entities within unstructured text.
3. Key Phrases Extraction: Extracts important words and expressions from comments, highlighting popular discussion topics.
4. Predict Customers' Needs: Utilizes machine learning models to forecast future customer needs and preferences.
5. No-Code Text Analytics: Offers a user-friendly interface that allows users to obtain comment insights without any coding experience.
6. Scalability: Supports a high volume of real-time requests and provides a scalable infrastructure to accommodate increased workloads.
7. Immediate Support: Delivers 24/7 ticket support, dedicated sales managers, and accessible engineers for user assistance.
8. Custom Analysis and Websites: Allows users to customize inference models for various texts and obtain tailored insights through machine learning.
9. Multiple Use Cases: Generates insights from videos, social media, product pages, and more to enhance marketing strategies, product offerings, and customer loyalty.

Comments Analytics: User Guide

1. Step 1: Choose your method of comment import, such as copy/paste, website crawling, or uploading an Excel CSV/XLSX file.
2. Step 2: Select the language for analysis, as the platform supports 23 languages.
3. Step 3: Utilize the advanced natural language processing (NLP) techniques to analyze the comments.
4. Step 4: Extract key phrases and sentiments to gain insights into customer opinions.
5. Step 5: Customize the models as needed to obtain clean and relevant insights.
6. Step 6: Review the insights generated to inform decision-making and strategy development.

Comments Analytics: User Reviews

• "Comments Analytics has transformed the way we approach customer feedback. The insights are incredibly detailed and actionable!" - User A
• "The sentiment analysis feature has helped us understand customer emotions better. It's a must-have for any marketing team." - User B
• "I appreciate the no-code interface. It makes it easy for our team to analyze comments without needing a data scientist." - User C
• "The support team is always responsive and helpful. They've assisted us in customizing our models effectively." - User D