Similar channels in Telegram and how to use them for ads

For a long time, channel selection for Telegram ads relied on keywords. It felt simple and logical. But Telegram works differently. Today the Similar Channels feature based on user behavior is much more precise. Instead of guesses, you get real audience overlaps. This article explains how Telepars works with that data and why keywords are no longer enough.

What Similar Channels mean in Telegram

Similar Channels is not a manual list, not tags, and not categories. It is a system mechanism in Telegram that analyzes user subscriptions and shows which other channels those users join. In other words, Telegram determines where your audience is by behavior, not descriptions.

The list is built for each channel separately. It usually includes 50 to 100 links ordered by similarity. This does not mean the channels have the same description. The common factor is subscriber behavior: they move between these channels and engage with content.

The algorithm is not public, but practice shows Telegram filters random overlaps and focuses on stable behavior patterns. The result is a living ecosystem of channels with a close audience.

Similar Channels is an automatically generated map of user interests, and you can rely on it as an objective data source for ad placements or seeding.

How Telepars helps use this feature

Telegram does not allow exporting the Similar Channels list. It only shows it in the interface. To use the logic systematically, you need a tool. Telepars provides a Similar Channels module that automates this work.

How it works: you paste several channel usernames into the service, usually five to ten. Telepars collects similar lists for each and analyzes overlaps. The output is a table where each found channel has an overlap count, for example it appears in six of ten base channels. That means its audience overlaps tightly with your core.

The higher the overlap count, the closer the channel is to your target audience. You can sort the list and keep only those that appear in several groups. This gives you not just a list of similar channels but a priority ranking by audience density. It is faster and more precise than browsing profiles manually.

You can also export the channels, run analysis, and check activity, posting frequency, and administrator contact, all in one system.

Why this is more precise than keyword search

Keyword search is an old tool that seems reliable. You type marketing and find marketing channels. But in practice it produces noise. A keyword may appear in a name but not reflect the content, and it does not guarantee audience overlap.

Example: a channel titled "Business from scratch" may post memes about success, not cases or practice. Or a channel named "Human resources tools" may be read by freelancers for humor, not recruiters.

Similar Channels is a behavioral metric. It does not depend on descriptions or titles. Telegram checks which channels real people subscribe to. If your target audience is beginner marketers, there is a strong chance they overlap across different channel styles with similar meaning.

That is why Similar Channels works better. You do not guess interest match, you get a list of channels where the same audience already exists. This removes manual verification because Telegram already points to where the segment lives. Telepars turns it into a usable list.

How this affects ads and channel seeding

Working with similar channels directly improves results. Reach may stay the same, but audience quality increases. That means more subscribers for the same money, less churn, and higher engagement.

When you place ads based on keywords, you often get a mixed audience. Some people came for memes, some for discounts. This spreads the budget. The seeding worked, reach was there, but only two percent converted to subscribers. The topic looked right, but the people were not.

With Telepars and similar channels, you run a "similar funnel". You start with a small core of proven channels, for example those that already brought good subscribers. Then you expand from them using overlap lists. Telepars shows channels where the audience intersects.

Then you repeat: expand the core, launch new placements, expand again. After two to three iterations you reach 100 to 300 channels with a high share of the right audience. Without analysts, without manual checks, and without wasting budget on unrelated placements.

The result is better ad performance, lower subscriber cost, and fewer irrelevant impressions.

Similar channel search is not guesswork and not subjective. It is based on real actions of Telegram users. Instead of manually filtering channels by titles, you get a list where the audience already proved interest. Combined with Telepars, it becomes a fast and accurate tool for mass placement selection. Ad budgets work more efficiently and seeding becomes purposeful.