2 measurements spanning 1 day. 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 118–120 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
9 Aug 2026, 04:30
119
no change
7 Aug 2026, 16:47
119
first reading
Engagement
20 posts held, back to 12 August 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
55.5%
avg views ÷ 119 subscribers
Avg views / post
66.0
1 post measured
Reaction rate
10.6%
reactions ÷ views · ER floor
Posts in window
1
of 20 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 17 July 2026
Posts held
20 (12 August 2025 – 17 July 2026)
Views total
66
Reactions total
7
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Aug 2026, 04:30 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
13
Videos
2
Links
9
Lifetime counters from Telegram’s own channel header, read 9 August 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
1h 25m
Average length
42m 40s
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
178 reactions across 20 posts, in 12 distinct kinds. The most used accounts for 51.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
91
51.1%
❤
41
23.0%
👍
15
8.43%
👏
9
5.06%
😎
9
5.06%
❤🔥
3
1.69%
🤝
3
1.69%
🤩
3
1.69%
🆒
1
0.562%
👌
1
0.562%
💯
1
0.562%
🤡
1
0.562%
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 20 of the 20 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 178reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 12 August 2025 to 17 July 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
15
across the posts below
Posts paid on
9
of 20 we hold a reading for · 45%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @convergate. 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 20 most recent posts we hold for this entry, published 12 August 2025 to 17 July 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.
Мы просто сделаем классный продукт и он сам себя будет продавать!
Одна из самых влажных фантазий, которую только можно придумать в B2B-коммерции. История человеческой деятельности насчитывает десятки (а может сотни) случаев, когда даже самые прорывные идеи и продукты прозябали в забвении без должного продвижения. Вот вам один из таких.
В конце 19 века американский ученый Джозайя Гиббс разработал математическую теор…
Мы обновили сайт
В какой-то момент продукт, который мы создаем, убежал далеко вперед в сравнении с сайтом, где мы о нем рассказываем. Пока мы добавляли новые возможности, общались с пользователями и запускали пилоты, сайт постепенно превратился в эдакий снимок из прошлого – как те старые фотографии, которые достает дед, и показывает, как все было раньше. Поэтому мы его обновили.
Самое главное – мы заново ответили с…
Как мы используем Convergate в своих продажах
Рассказываю.
Есть у меня знакомая, Маша. Работает в компании, которая делает кассовое оборудование и ПО для ритейла. А еще у нее есть tg-канал, где мы рекламу покупаем. Собственно, в один из таких разов пришел за рекламой, принес креатив, рассказал два слова про продукт – что делаем рисерч целевых клиентов, ищем ЛПР, собираем гипотезы ценности и все такое.
Маша говорит…
Проблема современного аутрича
Когда-то давно продажи выглядели так:
- взять справочник желтого цвета
- обвести кружочками там нужные компании
- звонить по общим номерам, всякими хитростями обходить секретаря и пытаться выйти на ЛПРа
И если удавалось добыть email/телефон — считай полдела сделано. На дворе 2026 год. И уже давно найти контакт нужного человека не проблема (LinkedInn, Apollo, TG-боты всякие). А вот проб…
Знай своего клиента
Был такой период, когда я работал в консалтинге. Мы работали с крупным производственным энтерпрайзом - нефтяники, металлурги, химики. Серьезные ребята крч. Продавали проекты по безопасности и непрерывности производства. Делали так, чтобы работяги на местях не косячили, оборудование не ломали и сами себя на вентилятор не наматывали. Если что-то случится на производстве, 1 день простоя цеха - милли…
Сколько времени у вас уходит на подготовку ко встрече с клиентом?
Как обычно бывает:
- 2-3 часа рисерча (x3, если клиент из enterprise)
• куча вкладок и документов
- и всё равно есть ощущение, что ты что-то упускаешь
А после звонка выясняется, что ты говорил не с теми людьми и вообще не о том 😒
Мы делаем Convergate, который делает рисерч по клиенту за тебя:
- собирает инфу о компании из 50+ источников
- находит ЛПР…
Получили комментарий, что наш подход к АВМ кажется ближе к PR, чем к маркетингу, ведь в нем нет агрессивных и прямых продаж. Хочется прокомментировать)
АВМ - это такая хитрая стратегия построения отношений с крупными брендами. Именно с теми ребятами, до кого вы вряд ли дотянетесь прямым агрессивным аутричем, там таких как вы еще целая очередь.
Именно поэтому мы создаем такую стратегию, где касаниями маркетинга, пиа…
Друзья, спасибо всем, кто был на воркшопе! Кажется, получилось хорошо) Нам самим понравилось, а вам?
Запись скоро будет, а пока, как обещали, отдаем пароли-явки.
Если хотите на консультацию, поработать индивидуально или обсудить групповой формат - пишите @SEkaterin или @antonindeed
Мы планируем продолжать делать подобные разборы, так что если вы готовы стать нашим гостем и собрать АВМ план для вашего продукта/бизн…
Воркшоп: продаем цифровой В2В-продукт в Энтерпрайз (Account-based marketing подход).
Если вы работаете в В2В, то у вас точно есть свой wish-list идеальных клиентов: крупные компании, которым нужен ваш продукт, но они про него пока ничего не знают.
Или знают, но почему-то не покупают.
Как их заполучить?
Маркетинг пишет статьи и кейсы, продажи - атакуют холодными рассылками, все работают сами по себе, выхлоп - окол…
❤10🔥10👍4
Showing the 12 most recent of 20 posts we hold for @convergate. 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.
Citation-graph rank
Citation-graph rank — 749,572 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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 2 registered channels — 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 9 August 2026 — this
entry's latest reading, not the date you are reading this.
“Convergate” (@convergate), 119 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/convergate.
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.