Marketing & affiliate — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 61% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Growth
62 measurements spanning 92 days, net +2,040. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 12,867–15,519 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
7 Nov 2026, 16:16
15,213
+19
6 Nov 2026, 14:10
15,194
+45
5 Nov 2026, 15:56
15,149
+46
4 Nov 2026, 19:10
15,103
+5
3 Nov 2026, 15:50
15,098
+10
2 Nov 2026, 16:31
15,088
+16
1 Nov 2026, 15:09
15,072
+8
31 Oct 2026, 18:19
15,064
+20
30 Oct 2026, 18:47
15,044
+43
29 Oct 2026, 20:28
15,001
+84
28 Oct 2026, 17:36
14,917
+92
27 Oct 2026, 15:45
14,825
+10
26 Oct 2026, 11:46
14,815
+1
25 Oct 2026, 15:18
14,814
+11
24 Oct 2026, 16:50
14,803
+17
23 Oct 2026, 16:16
14,786
+90
22 Oct 2026, 12:57
14,696
+19
21 Oct 2026, 09:27
14,677
+55
20 Oct 2026, 10:47
14,622
-7
19 Oct 2026, 11:04
14,629
first reading
Engagement
61 posts held, back to 15 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 58 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
28.3%
avg views ÷ 15,213 subscribers
Avg views / post
4,310
23 posts measured
Reaction rate
3.34%
reactions ÷ views · ER floor
Posts in window
23
of 61 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 7 November 2026
Posts held
61 (15 July 2026 – 7 November 2026)
Views total
99,040
Reactions total
3,310
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Nov 2026, 05:41 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
338
Videos
5
Links
165
Lifetime counters from Telegram’s own channel header, read 8 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
4m 20s
Average length
2m 10s
Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
8,470 reactions across 61 posts, in 4 distinct kinds. The most used accounts for 52.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5238165358564613794
4,483
52.9%
❤
2,668
31.5%
🔥
1,144
13.5%
👍
175
2.07%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 61 of the 61 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 8,470 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 61 most recent posts we hold, published 15 July 2026 to 7 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
126
across the posts below
Posts paid on
35
of 61 we hold a reading for · 57%
Most on one post
14
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @big_bad_coach. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 61 most recent posts we hold for this entry, published 15 July 2026 to 7 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 8 of 23 posts held from the last 30 days (34.8%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Инструмент для сбора семантики в Яндекс Директе. 🎹
Мы там с Ольгой Ивановой сделали новый инструмент для Экосистемы, в этот раз для тех, кто работает с рекламой. Уже доступен всем участникам сообщества. 🥰
Пишете свою услугу или товар, а инструмент собирает семантическое ядро с частотностью, минусует мусор, кластеризирует. Что-то делает сам, а в чём сомневается — предлагает выбрать вам. ☺️
На выходе же отдаёт вам р…
SEO-чек-лист вашего сайта v1.0 — для самых маленьких. ☺️
Так как сейчас порог входа в создание сайтов крайне мал, а доверие к нейросетям крайне велико, я решил сделать серию чек-листов вам в помощь.
Выкатывать я их планирую итерациями в надежде на то, что вы не в тупую будете кормить ими нейронки, а реально узнавать что-то новое, НО! Есесно, всё остаётся на ваше усмотрение. ⌨️
Внутри чек-листа я сделал разбивку на…
Вы принимаете решения на основе цифр? Нет, просто показываю... Красивое! ☺️
Поняли, да? Это отсылка к тому мему с котами на рынке, где они подходят к прилавку рыбному и такие «Вы рыбов продаёте?» а продавец им «Нет, просто показываю…» кхэ-кхэ, КАРОЧЕ!
Есть такой data-driven подход — это когда решения принимаются на основе данных, а не эмоций, чувств и «похуй, погнали» от начальника в чате. 😝
И уже завтра в 11:00 в…
По поводу Beget — упал, не страшно, поднимется. 🥰
Гайс, не поддавайтесь на провокации СМИ с их заголовками "РУНЕТУ ПИЗДА, ПОЛМИЛЛИОНА САЙТОВ ПОД УГРОЗОЙ" — это их работа.
Я не сторонник нагнетать и танцевать на костях и моя позиция проста — если нечего сказать по делу, лучше завалить ебало. 😝
Чего и желаю всем недоСМИ и хайпожорам.
На деле же — упали, да, бывает, у меня также отъебнулась пачка и я также расстроен…
Вам нужно развивать личный бренд, и начать нужно сегодня.
Не завтра, не потом — сегодня… С каждым днём будет всё сложнее.
Я никого не пугаю и ничего не собираюсь вам продавать, я лишь хочу поделиться кейсом — эксперимента ради два месяца назад я сделал ИИ-блогера, весь его контент создан нейросетями… И вчера у него купили рекламу.
И я не буду вам рассказывать, как сделать такого блогера и зарабатывать на нейроконте…
Там это... нихуя себе. 🥰
Почему-то особенно приятно именно от этой цифры, спасибо большое всем причастным — всем вам. ☺️
Обнимаю каждого, дальше больше. 🥰
Вашему вниманию — база знаний по маркетингу более чем на 1000 тем. 😎
Нихуясебе? А иначе-то и не скажешь... 🤣
Давайте в этот раз коротенько — меня давно просили сделать курс, я решил пойти дальше и сделать ЕДИНУЮ БАЗУ ПРИКЛАДНОГО МАРКЕТИНГА — сокращённо ЕБПМ. Название ещё выберем... 😏
ЛАДНО, коротенько всё равно не получится, но я постараюсь. 🥰
У меня есть мечта — сделать место, куда каждый сможет зайти, не опасаяс…
Тиндер для B2B: как находить постоянных партнёров, а не разовые встречи с ЛПР. 🍌
Завтра, в 11:00, в Экосистеме разберём, как устроен B2B-аутрич: от поиска подходящих компаний до выхода на лиц, принимающих решения. 😎
И в этот раз я, пожалуй, не буду сильно распинаться, так как тема в представлении особо не нуждается и окажется крайне полезной компаниям, работающим с B2B, особенно тем, кто только начинает свой нелёгк…
На вашем сайте должны быть статьи, иначе вы теряете клиентов. 🤓
«Какие нахуй статьи, мне нужно, чтобы у меня покупали». (с)
Наверное, именно из-за подобного я неоднозначно отношусь к нейросетям, так как это очень простой инструмент с очень небольшим порогом входа, НО НИХУЁВО завышающий самооценку всем, кого он коснётся. Даже тем, кому это противопоказано…
Блядь, знали бы вы, сколько людей за последние полгода в раз…
«А схуяли я должен платить за Экосистему?» — вежливо спросили меня. 😑
А вот действительно, схуяли вы мне что-то должны… Вы не должны! 🥰
Знаете, есть такой большой культ — я называю его «потребляди». Это люди, которым все должны, они же нихуя не должны взамен. И сообщение, которое красуется в заголовке, я получил как раз от почетного члена такого культа…
Для контекста: в четверг я дропнул инструмент для сбора семант…
Мы сделали инструмент для сбора семантического ядра. 😎
Будет полезно для всех, кому не хочется сильно разбираться, но надо вот это вот всё непонятное: SEO/GEO, структура многостраничного сайта, контекстная реклама, контент-стратегия и всякое другое.
Короче, если без приколов, то можете просто зайти вот сюда — https://ekosistema.pro/tools/semantics — и посмотреть, как выглядит инструмент. Если захотите не только пос…
🔥38custom 523816535856461379428❤14
Showing the 12 most recent of 61 posts we hold for @big_bad_coach. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@big_bad_coach edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
19 August 2026
Most recent edit
19 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“Жаворонков Кирилл” (@big_bad_coach), 15,213 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/big_bad_coach.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.