How to Scrape Target Audiences from Competitor Chats in Telegram
Quick Summary: Telegram chat scraping is the fastest way to get a target audience database that is already interested in your niche. In this guide, we break down what data can be collected, which tools to use, and how to structure the process from preparing accounts to generating a ready-to-use database.
Table of Contents
- Why scraping is the foundation of Telegram marketing
- What data can be collected
- Scraping modules: what modern tools can do
- Step-by-step scraping process
- Tips for maximum efficiency
Why scraping is the foundation of Telegram marketing
Telegram has over 900 million active users. However, creating a group and waiting for organic audience growth is a failing strategy in an environment with high competition for user attention.
Scraping solves a key challenge: it allows you to compile a database of people who are already interested in your niche — participants of thematic groups, competitor chats, and industry-specific channels. This is an audience of fundamentally higher quality compared to cold traffic.
The resulting database can be used for:
- Inviting users to your own group or channel
- Personalized mass messaging with an offer
- Targeted nurturing before a sale
What data can be collected
Modern Telegram scraping tools collect the following types of data from open Telegram chats:
| Data Type | Description | Application |
|---|---|---|
| Username | Primary user identifier | Messaging, inviting |
| Telegram ID | Unique numerical ID | Precise targeting |
| Activity | Date of last message, number of messages | Filtering "live" users |
| Profile Photo | Presence or absence of an avatar | Excluding bots |
Note: Phone numbers are unavailable via scraping — Telegram hides them from third-party tools. Work is conducted using usernames and Telegram IDs.
Scraping modules: what modern tools can do
Quality Telegram scraping software provides several specialized modules for different tasks. Using Deskgram 2 as an example:
| Module | What it does | When to use |
|---|---|---|
| Member Scraping | Collects usernames from a chat or group | Primary database collection |
| Comment Scraping | Collects authors of comments in channels | Collecting active, engaged audience |
| Channel Search | Finds groups and channels by keywords | Searching for scraping sources |
| ID Targeting | Works directly with Telegram IDs | Precise, targeted campaigns |
Comment scraping is an especially valuable module: people who leave comments in niche channels demonstrate a high level of engagement and interest in the topic. Such an audience converts significantly better than passive group members.
Step-by-step scraping process
Step 1: Preparing accounts
It is recommended to use at least 3–5 accounts for scraping. Each account should be added to the source groups from which you plan to collect the database.
A mandatory requirement is a preliminary account warm-up: subscribing, reading messages, and leaving reactions. An account without an activity history arouses suspicion from Telegram’s algorithms and quickly receives restrictions.
Step 2: Setting up proxies
Connect an individual SOCKS5 proxy for each account. This eliminates the possibility of linking accounts by IP and significantly reduces the risk of being blocked. Good tools support automatic proxy rotation — this is convenient when working with a large pool of accounts.
Step 3: Configuring and launching the scrape
In the scraping module, specify:
- Source chats — competitor groups, thematic communities
- Activity filters — exclude users who have been inactive for the last 30–60 days
- Avatar filter — the presence of a profile photo reduces the percentage of bots in your database
After launching, the tool will process all specified chats and export the result to a file for further work.
Step 4: Deduplication and database filtering
After collection, be sure to:
- Remove duplicates — one user might be in several scraped groups.
- Exclude obvious bots (no photo, no username, no activity).
- Segment the database by source — this helps evaluate the quality of different chats.
A clean database after filtering provides significantly higher conversion rates for mass messaging and inviting campaigns.
Tips for maximum efficiency
Choose sources with high activity. A group with 50,000 members, but where the last message was a month ago, is a bad source. Look for chats with daily updates.
Use the last message date filter. Users who haven't posted in over 3 months are highly likely to be inactive — you can exclude them immediately.
Combine multiple sources. Scraping from 5–10 thematic groups provides a more diverse and voluminous database than working with a single source.
Regularly update your database. People leave groups, change usernames, and leave Telegram. A database collected six months ago loses its relevance — launch a re-scrape every 1–2 months.
Always use warmed-up accounts. This rule applies to scraping as well: an account with an activity history scrapes without limits, while a new one quickly gets a temporary ban.
Conclusion
Scraping competitor chats is not a "gray" tool, but standard practice in Telegram marketing. The keys to success are high-quality sources, warmed-up accounts, proper database filtering, and regular data updates. With a systematic approach, you receive a constant stream of a target audience that is already interested in your topic.
Guide updated in 2026, taking into account current Telegram API restrictions.
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