Third-Party Analytics Platforms
Posted: Sun May 18, 2025 10:36 am
Platforms such as TGStat, Combot, and Telemetr.io specialize in aggregating Telegram channel and group statistics. They provide:
Subscriber growth tracking
Post engagement analytics
Influencer discovery tools
Competitive benchmarking
Using these services saves time and offers a qatar telegram mobile phone number list user-friendly way to extract marketing insights without heavy technical skills.
How to Analyze Telegram Data: Methodologies and Tools
Sentiment Analysis
Sentiment analysis helps marketers gauge public opinion. By analyzing messages and comments in channels or groups, you can identify how users feel about a product, brand, or topic.
Tools and Techniques:
Open-source NLP libraries such as NLTK, TextBlob, or spaCy
Sentiment-specific APIs like Google Cloud Natural Language or IBM Watson
Custom machine learning models trained on Telegram-specific language nuances
Engagement Metrics Analysis
Telegram offers metrics like views on posts, forward counts, and comments (if enabled). Analyzing these helps understand:
Which content types resonate most (videos, images, text)
Optimal posting times for maximum reach
Influencer effectiveness in collaborations
Visualization tools like Tableau, Power BI, or Google Data Studio help turn raw data into actionable insights.
User Segmentation and Profiling
By grouping users based on behavior and interests (inferred from channel subscriptions, interaction frequency, and bot activity), marketers can create tailored messaging strategies.
Subscriber growth tracking
Post engagement analytics
Influencer discovery tools
Competitive benchmarking
Using these services saves time and offers a qatar telegram mobile phone number list user-friendly way to extract marketing insights without heavy technical skills.
How to Analyze Telegram Data: Methodologies and Tools
Sentiment Analysis
Sentiment analysis helps marketers gauge public opinion. By analyzing messages and comments in channels or groups, you can identify how users feel about a product, brand, or topic.
Tools and Techniques:
Open-source NLP libraries such as NLTK, TextBlob, or spaCy
Sentiment-specific APIs like Google Cloud Natural Language or IBM Watson
Custom machine learning models trained on Telegram-specific language nuances
Engagement Metrics Analysis
Telegram offers metrics like views on posts, forward counts, and comments (if enabled). Analyzing these helps understand:
Which content types resonate most (videos, images, text)
Optimal posting times for maximum reach
Influencer effectiveness in collaborations
Visualization tools like Tableau, Power BI, or Google Data Studio help turn raw data into actionable insights.
User Segmentation and Profiling
By grouping users based on behavior and interests (inferred from channel subscriptions, interaction frequency, and bot activity), marketers can create tailored messaging strategies.