How to check Telegram subscribers after ads and reduce churn

Launched a Telegram ad campaign and saw new subscribers flow in? It is time to understand who came and whether they were worth the spend. Subscriber analysis after ads is more than counting numbers in stats. It shows if your promotion strategy works, whether content matches new audience expectations, and whether you are overpaying for empty subscriptions. The right analysis helps you adjust ads, improve traffic quality, and get more target subscribers for the same money.

Why analyze subscribers after ads

Many people call a campaign successful if the subscriber count grows. In reality that is only half the picture. Real effectiveness is measured not by inflow but by retention. If out of 1000 new subscribers only 200 stay after a month, you overpaid by five times. Analysis helps you calculate the real subscriber cost after churn and see which ad sources bring quality audiences. By tracking new subscriber behavior, you can adapt content to their interests or change targeting to attract more relevant people. Without this analysis you risk spending budget on empty numbers instead of real customers.

Signs of live users and bots after a subscriber spike

How to spot bots and fake growth

Modern bots are smarter and try to look real. Here are common signs of fake audiences:

• Same style usernames with similar names, numbers at the end, or meaningless letter combinations.
• No profile photos when more than 30 percent of new subscribers have no avatar.
• Suspicious Telegram Premium patterns when either all new subscribers have Premium or none do at scale.
• Empty profiles with no bio, no message history, and recently created accounts.
• Abnormal timing where many accounts subscribe at the same time.
• Geographic mismatch for example a Russian target audience but incoming accounts have unrelated names and locations.

With small inflow, five to ten people, coincidences happen. But if out of fifty new subscribers everyone has Premium or nobody does, that is a warning signal.

Behavior of suspicious audiences

Bots and fake accounts behave in predictable ways:

• Synchronized reactions where everyone leaves the same emoji at the same time.
• Mass unsubscribes with large groups leaving on one day.
• Total passivity with no comments, shares, or interactions.
• Ignoring direct messages because bots do not reply.

Real audiences are always diverse. Even passive users show some activity, such as viewing older posts or occasionally reacting. It is suspicious when the entire new audience behaves identically or shows zero engagement for weeks.

What end to end analytics means in Telegram and how to set it up

Telegram does not provide full end to end analytics like a website, but basic user path tracking can be organized manually. In Telegram, end to end analytics means understanding where the audience came from, how long they stay, and what happens next.

The idea is simple: create unique links for each placement and track not only subscribers but also their later behavior. For example, you place ads in five channels and create five links. A month later you see that 100 people came from channel one and 20 left, while 80 came from channel two and 60 left. The first source is higher quality even if it costs more.

This approach is especially important for clickbait posts. Ads may look great with fast growth, but if half the people leave within a week, the real cost doubles. For that money it is better to buy less active but more focused traffic from the start.

How to evaluate ad effectiveness step by step

Preparation: tracking parameters and unique links

Before any campaign, create unique links for each placement. This is the foundation of quality analysis.

How to build links correctly:

• Use a clear naming system such as t.me/your_channel?start=channel1_post1.
• Use a separate tag for each channel, for example channel1, channel2, business_channel.
• Add placement dates, for example t.me/your_channel?start=channel1_15dec.
• Maintain a table with every link, the channel name, the date, and the budget.

Tag examples:

• Ad in a business channel: ?start=business_channel_dec2024
• Post in an information technology community: ?start=it_community_week50
• Placement with a blogger: ?start=blogger_ivanov_nov

This system helps you understand which channels work even months later. The key is to use tags consistently and keep records of what each tag means.

Churn analysis and real subscriber cost

The real subscriber cost becomes clear only after two to four weeks, when the first churn wave passes. Here is the correct calculation:

Real cost formula: Budget divided by (New subscribers minus Unsubscribes) equals real subscription cost.

Example calculation:

Channel	Budget	Joined	Unsubscribed after a month	Stayed	Final cost
Channel A	50,000 rubles	500	100	400	125 rubles
Channel B	30,000 rubles	200	20	180	167 rubles
Channel C	40,000 rubles	400	300	100	400 rubles

At first glance channel C looked cheapest, 100 rubles per subscriber. But after churn the cost rose four times. Channel B looked expensive at 150 rubles, but turned out average. Track unsubscribes weekly in the first month, then monthly. This shows when losses happen and how to adjust retention.

Useful tools for Telegram channel analytics

Telepars and its features

Telepars is one of the few services that solves detailed subscriber analysis in Telegram. The Channel Pulse feature shows the full picture for each unique link.

Main capabilities:

• Detailed link statistics showing how many people joined and left from each source.
• Subscriber lists so you can see who joined from a specific link.
• Automatic reports with daily stats delivered to a bot.
• Bulk bot removal to select suspicious accounts and remove them in batches.
• Traffic quality analysis by comparing sources based on churn rate.

The service is especially useful at budgets from 20,000 rubles per month. With smaller spend, detailed analytics may be excessive, but for serious campaigns Telepars provides data that standard Telegram stats cannot.

Built in Telegram analytics: what it shows and what is missing

Telegram provides basic analytics but with limitations. You cannot see specific subscribers, there is no demographic data, and there is no detailed source breakdown.

Key sections:

Chart	What it shows	How to use it
Growth	Subscriptions and unsubscribes by day	Track the effect of campaigns
Subscribers	Overall audience trend	See long term growth
Subscriber sources	Where new people come from	Understand which channels work
Hourly views	Audience activity by hour	Choose the best posting time
View sources	Where content is seen from	Find unexpected traffic sources
Activity	Shares and forwards	Measure virality
Notifications	Notification disable rate	See if posting frequency annoys users

Main drawbacks of built in analytics:

• No link to specific ad links.
• No access to subscriber profiles.
• No audience quality analysis.
• No unsubscribe timing details.

Built in stats are enough for overall trends, but serious ad analysis needs additional tools.

How to interpret churn and engagement

Normal and alarming churn levels

Unsubscribes are normal. The key is understanding which numbers are acceptable.

Normal churn levels:

• Up to 20 percent within a week after a campaign is normal.
• About 1 percent of the total audience per week is a natural decline.
• Five to ten percent right after subscribing is expected as people evaluate content.

Example for a 100,000 subscriber channel:

• Normal weekly churn: up to 1,000 people, one percent.
• Per day: about 140 to 150 people.
• After a campaign with 1,000 new subscribers: up to 200 unsubscribes is normal.

Alarming signals:

• More than 30 percent churn after ads.
• Weekly loss above 2 to 3 percent of the total audience.
• Mass synchronized unsubscribes, which can signal bots or irrelevant traffic.

Remember: better 1,000 active subscribers than 10,000 dead ones. High churn usually points to targeting problems or a mismatch between ad message and channel content.

Why subscribers leave: main reasons

Understanding churn reasons helps you fix issues in future campaigns.

Main reasons:

• Clickbait ads that promise one thing and deliver another.
• Irrelevant content where ad topic does not match channel focus.
• Weak first touch with no welcome message or a vague one.
• Wrong posting frequency with too many or too few posts.
• No value where content does not solve subscriber problems.
• Incorrect targeting so ads reach the wrong people.
• Poor channel packaging with no description, avatar, or pinned posts.
• Aggressive sales right after subscribing.

Most unsubscribes happen in the first 48 hours when people evaluate the channel. That is why first impression and a welcome sequence are critical.

What to do if traffic is not relevant

Do new subscribers leave fast or show no activity? Use a structured plan:

Action algorithm:

• Analyze sources and identify channels that bring low quality traffic.
• Review ad posts because they may be too clickbait and promise what the channel does not deliver.
• Adjust targeting if you use Telegram Ads and refine audience settings.
• Update the channel description so it clearly explains who the channel is for.
• Create a welcome sequence with posts that explain the channel value.
• Adjust the content plan if topics do not match expectations.
• Refine your unique selling proposition so it matches the actual content.
• Pause weak sources and stop placements with high churn.

Do not try to retain irrelevant audiences at any cost. It is better to bring fewer but higher quality subscribers than to inflate a passive base.

Conclusion: key points for subscriber analysis

Subscriber analysis is not a one time task. It is a continuous optimization process. Track not only inflow but also quality through engagement and retention. Remember: 1,000 active subscribers are always better than 10,000 passive. Do not fear unsubscribes, they are natural and clean the audience. Focus on long term metrics: paying more for a subscriber who stays for years is better than saving on cheap traffic that leaves in a week. Use data to improve - every campaign should give insights for the next one.