How to identify a channel with fake subscribers

Identifying a channel with fake subscribers requires analyzing several key metrics simultaneously — no single indicator is conclusive on its own, but a combination of red flags paints a clear picture. The most reliable signals include an abnormally low engagement rate, suspicious subscriber growth patterns, and bot-like activity in comments.

Understanding Fake Subscribers in Telegram

Fake subscribers (also called "bots" or "dead souls") are inactive accounts added to a channel artificially to inflate its subscriber count. This practice is widespread — some estimates suggest that 30-50% of channels with over 10,000 subscribers have at least some portion of fake followers.

Channels inflate their numbers for several reasons:

Attracting advertisers who pay based on subscriber count
Building social proof to appear more popular than they are
Meeting partnership thresholds that require minimum audience size
Competing in niche rankings where subscriber count matters

The good news is that fake subscribers leave distinct traces that become obvious once you know what to look for.

Key Metrics to Analyze

Engagement Rate (ERR and ERR24)

The engagement rate is your most powerful diagnostic tool. It measures how many subscribers actually interact with content.

How to calculate:

ERR = (average views per post / total subscribers) × 100%

Healthy benchmarks by channel size:

Subscribers Normal ERR Suspicious ERR 1,000–5,000 30–60% Below 15% 5,000–20,000 20–40% Below 10% 20,000–100,000 15–30% Below 5% 100,000+ 10–20% Below 3%

A channel with 50,000 subscribers but only 800 views per post (1.6% ERR) is almost certainly inflated. Compare this to a healthy channel of similar size that would typically get 7,500–15,000 views.

Important: ERR alone is not proof. Some legitimate channels in narrow professional niches may have lower engagement. Always combine ERR with other indicators.

Views-to-Subscribers Ratio Over Time

Examine how views accumulate in the first 24 hours after posting (ERR24). Organic channels show a characteristic curve:

First hour: 15–25% of total views
First 6 hours: 50–65% of total views
First 24 hours: 75–90% of total views

Channels with fake subscribers often show flat view growth — the views plateau quickly because only real subscribers are actually reading the content.

Subscriber Growth Pattern

This is where fake subscribers become most visible. Open a channel's statistics (available for channels with 50+ subscribers) and examine the growth chart.

Red flags in growth patterns:

Sudden spikes — jumping from 5,000 to 15,000 subscribers in a single day without any viral content or cross-promotion
Staircase pattern — flat periods followed by sharp jumps at regular intervals (suggesting periodic bot purchases)
Growth without content — subscriber count increasing during periods when no posts were published
Immediate drops after spikes — Telegram periodically purges bot accounts, causing sharp declines

A legitimate channel growing from 10,000 to 20,000 subscribers will typically show a gradual upward slope over weeks or months, possibly with small bumps corresponding to viral posts or mentions.

Comment and Reaction Analysis

If the channel has comments enabled, they provide valuable intelligence.

Signs of fake engagement:

Generic comments like "Great post!" "Very interesting!" "Thanks for sharing!" repeated by different accounts
Comments in languages that don't match the channel's content language
Accounts with no profile photos, randomly generated names, or names that follow a pattern (e.g., "User_28374", "User_83921")
All comments posted within the same 2–3 minute window
Reactions that spike artificially — for example, a post with 500 views but 400 reactions

Signs of genuine engagement:

Specific, contextual responses that reference post content
Questions and discussions between subscribers
Varied reaction types (not just one emoji dominating)
Comments spread naturally over several hours

Step-by-Step Verification Process

Step 1: Check Basic Statistics

Open the channel and tap the subscriber count to access Channel Statistics (if available). Note the total subscribers, average post reach, and growth graph.

Step 2: Calculate the Engagement Rate

Take the last 10–15 posts (excluding any that went viral) and calculate the average views. Divide by total subscribers. If the result falls significantly below the benchmarks listed above, proceed to deeper analysis.

Step 3: Analyze Growth History

Look at the subscriber growth chart for the past 3–6 months. Mark any unusual spikes and check whether corresponding content or external events explain them. If spikes have no explanation, this is a strong red flag.

Step 4: Use Third-Party Analytics Tools

Several services provide deeper analysis:

TGStat — shows detailed engagement metrics, growth history, and audience overlap
Telemetr — provides ERR calculations and historical data
tgchannel.space — allows you to view channel content on the web, making it easier to cross-reference posting frequency with growth patterns

These tools can reveal patterns that are difficult to spot manually, such as audience overlap with known bot networks.

Step 5: Examine the Audience Profile

If you have access to advertising statistics or can request a media kit from the channel, examine:

Geographic distribution — a Russian-language tech channel with 40% of subscribers from Bangladesh or Vietnam is suspicious
Activity hours — real audiences show peaks during waking hours in their timezone; bot audiences show uniform activity
Device breakdown — an unusually high percentage of "unknown" devices may indicate bot accounts

Step 6: Monitor Over Time

The most reliable method is tracking changes over 2–4 weeks. Real channels maintain relatively stable view counts. Channels that recently bought subscribers will show views that stay constant while subscriber counts jump.

Tips & Best Practices

Compare with competitors: Find 3–5 channels in the same niche and similar size. A channel with dramatically different ERR from its peers deserves scrutiny.
Look at forwarded posts: Genuine channels are forwarded by real users. Check if the channel's posts appear in other legitimate channels or groups.
Check post frequency consistency: Real channels typically maintain a posting schedule. Gaps in posting followed by subscriber surges are suspicious.
Verify advertising claims: If a channel claims specific CPM rates or conversion rates, compare them against industry averages for that niche and audience size.
Use the "fresh post" test: If you're evaluating a channel for advertising, ask the admin to publish a test post and monitor its view growth in real time over 24 hours. The growth curve reveals a lot about audience quality.
Examine the oldest posts: Scroll to the very beginning of the channel. If early posts have view counts proportional to the channel's current size (rather than the size it was when those posts were published), it may indicate bulk bot additions that retroactively viewed old content.

Common Mistakes

Mistake 1: Relying solely on subscriber count
Why it's wrong: Subscriber count is the easiest metric to fake and the least informative about actual audience quality. A channel with 5,000 real subscribers is far more valuable than one with 50,000 fake ones.
How to avoid: Always calculate ERR and analyze growth patterns before drawing conclusions.

Mistake 2: Assuming low ERR always means fake subscribers
Why it's wrong: Some legitimate scenarios produce low engagement — channels that have been inactive for months, channels in highly specialized niches, or channels where subscribers keep notifications off and check content infrequently.
How to avoid: Compare ERR with similar channels in the same niche and look for multiple red flags, not just one.

Mistake 3: Ignoring seasonal variations
Why it's wrong: Engagement naturally fluctuates — it drops during holidays, weekends, and summer months. Judging a channel based on a single week's data during a holiday period can lead to false conclusions.
How to avoid: Analyze at least 30 days of data and account for seasonal trends.

Mistake 4: Trusting screenshots of statistics
Why it's wrong: Channel admins can easily manipulate screenshots using image editing software or by timing their screenshots during brief engagement spikes.
How to avoid: Always verify statistics independently using third-party tools or by accessing the channel's built-in statistics directly.

Frequently Asked Questions

Can a channel have both real and fake subscribers?
Yes, this is actually the most common scenario. Many channels start with a genuine audience and then "top up" with purchased subscribers to hit psychological milestones (10K, 50K, 100K). The real audience still engages, but the overall ERR drops proportionally.

Does Telegram delete fake subscribers automatically?
Telegram periodically conducts purges of bot and spam accounts. When this happens, channels with fake subscribers can lose thousands of followers overnight. These purge events are visible as sharp drops in the growth chart and serve as strong evidence of prior subscriber inflation.

Is buying subscribers illegal or against Telegram's rules?
Buying subscribers violates Telegram's Terms of Service. While Telegram rarely bans channels solely for having fake subscribers, it does remove the fake accounts themselves. Additionally, advertisers who discover inflated metrics may pursue legal action for fraud.

How accurate are bot-detection tools?
Third-party tools can detect obvious cases of subscriber inflation with roughly 70–85% accuracy. However, sophisticated bot services that use aged accounts with profile photos and activity history are harder to detect. No tool provides 100% certainty — manual analysis combined with automated tools gives the best results.

What is a "good" engagement rate for advertising purposes?
For most advertisers, an ERR above 20% for channels under 50K subscribers and above 10% for larger channels indicates a healthy, engaged audience. Channels with ERR consistently below 5% are generally poor advertising investments regardless of their subscriber count.