4 measurements spanning 6 days, net -35. 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 8,068–8,113 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 09:39
8,073
-14
10 Aug 2026, 09:01
8,087
-18
7 Aug 2026, 11:43
8,105
-3
6 Aug 2026, 22:01
8,108
first reading
Engagement
18 posts held, back to 29 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 11 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
13.7%
avg views ÷ 8,073 subscribers
Avg views / post
1,110
18 posts measured
Reaction rate
8.79%
reactions ÷ views · ER floor
Posts in window
18
of 18 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 10 August 2026
Posts held
18 (29 July 2026 – 10 August 2026)
Views total
19,976
Reactions total
1,755
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 16:47 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
Video runtime
1m 06s
Average length
1m 06s
Measured directly from 1 video 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
1,755 reactions across 18 posts, in 16 distinct kinds. The most used accounts for 59.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,051
59.9%
🔥
164
9.34%
❤🔥
129
7.35%
💔
116
6.61%
👀
90
5.13%
🦄
57
3.25%
💯
44
2.51%
🥰
19
1.08%
👏
17
0.969%
🙏
16
0.912%
👍
15
0.855%
😢
14
0.798%
🤗
12
0.684%
🤝
5
0.285%
🎉
3
0.171%
🤩
3
0.171%
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 18 of the 18 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 1,755reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 29 July 2026 to 10 August 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
1
across the posts below
Posts paid on
1
of 18 we hold a reading for · 6%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @ffrankel. 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 18 most recent posts we hold for this entry, published 29 July 2026 to 10 August 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.
Спустя много-много-много лет каталась на велосипеде — и сразу где-то посреди нигде в бурятской степи за местным легендарным мороженым.
Почему мы так часто забываем то, что любили в детстве и откладываем такие простые и доступные радости ради важных взрослых дел и срочных планов, кто мне объяснит?
Быть на своем месте
Сегодня попала в руки волшебного остеопата. Аня из Москвы — нас свел Байкал. Я была у многих остеопатов и телесников — но тут с самого начала сеанса стало понятно, что Аня — та, про которую сказано «Ведь у Бога нет других рук, кроме наших». По каким признакам ясно — не так важно, как важно встречать людей, которые настоящие «большие» мастера своего дела. Как теперь регулярно попадать к Ане, живя …
Ну а с интернетом у нас тут так все плохо (что даже хорошо), что выкладывается все рандомно и удалить не получается. Поэтому чайки задублились, ну и пусть летят)
Бурятская сторона Байкала нереальный кайф, расскажу.
Вынырнула из отпуска, чтобы вы узнали, что на Байкале нерпы бьют друг друга по круглым бочкам, чайки летят за катером, а я напоминаю, что сегодня до 00:00 можно успеть попасть на тестовую неделю моего нового проекта «Ивент-азбука». У нас там уже так много классных людей и планов✨
Я хочу успеть!
Сегодня день рождения моей мамы.
Впервые в этот день я ей не позвоню, впервые в этот день не приду к ней с цветами или не закажу букет, который ей доставят всегда, в какой точке мира я бы в этот день ни была.
Уже месяц понемногу разбираю мамину квартиру. Это небыстрый и осознанный процесс воспоминаний, отпускания и горевания. Квартира большая, вещей много, много документов. Много фотографий, осколков значимых собы…
О это многозначительное «Знаете, у нас тут ситуация…»
Когда так говорит клиент со своим фестивалем или владелец ивент-агентства на консультации, я невольно готовлюсь к «Завтра на конференцию моего заказчика пожалует Первое лицо», или «Со счета украли 95 миллионов, которые мы должны заплатить завтра подрядчикам и команде», ну или что-то не менее суровое и весомое.
Но нет. Но нет.
Обычно «ситуация» на поверку ока…
Вчера очень красиво вылетала из Москвы. Такой бескрайний простор и светящийся океан был под нами, и рядом взлетал еще самолет, и столько восторга и предвкушения в этом.
И думала о том, сколько у нас возможностей и свободы, если смотреть за рамками привычных паттернов и шаблонов. Если понимать, что реально влияем мы только на свой собственный мир.
И как сложно бывает быть за рамками. Выдерживать это расширение себя.…
Подруга моя Натали Туйгунова, пиарщик милостью божьей, вчера подарила новое дивное объяснение, что же такое «Ивент-азбука»!
«Ивент-азбука» — это то же самое, что CRM для маркетологов, 1С для бухгалтеров и «Консультант+» для юристов!
Ну роскошь! Так и будет, такой и план.
Заходите сюда, у нас до понедельника окно возможности попасть на тестовую неделю.
А для тех, кто верит в меня и мои проекты, меня поддерживает …
Я готова снять 30 видео, вычитать 50 сценариев, написать книгу, провести пять тренингов… лишь бы не собирать чемодан.
Всегда дотягиваю просто до последнего, особенно когда поездка не типовая (на 2 дня в Москву по работе), а более затейливая.
Перекличка!
❤️ люблю собирать чемодан!
👀 не люблю собирать чемодан и до последнего саботирую.
У моей подруги Натали Сеник (создателя ювелирного бренда Kintsugi) в запрещенке выходят рилсы с нашего подкаста. Принесла вам один из последних, там притча хорошая про многих людей.
Ниже – подпись к этому видео из аккаунта Наташи.
А сколько боли нужно вам, чтобы наконец разрешить себе что-то изменить?
Есть удивительная вещь: иногда мы прекрасно понимаем, что нам плохо. Но все равно остаемся.
Мы привыкаем к устало…
Спала рвано, проснулась очень рано. Огромный объем предвкушения, интереса, доверия и мандража.
Сегодня мы запускаем в мир мой новый проект – базу знаний для ивент-менеджеров. Уже много лет я не придумывала вот-прям-совсем-новых-продуктов. Пожалуй, с ветки скоростных онлайн-конференций в 2020. Потому что все живые конференции были сходны (хоть на 3 потока, хоть на 13), а в онлайн-курсах, которых были созданы десятки,…
❤48🔥33👏7🦄7❤🔥4🤩3
Showing the 12 most recent of 18 posts we hold for @ffrankel. 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 — 153,776 of 1,345,403entries 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
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 4 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Франкель про жизнь и бизнес” (@ffrankel), 8,073 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/ffrankel.
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.