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 123–125 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
9 Aug 2026, 03:01
124
no change
7 Aug 2026, 23:37
124
first reading
Engagement
11 posts held, back to 11 June 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
56.0%
avg views ÷ 124 subscribers
Avg views / post
69.5
4 posts measured
Reaction rate
14.4%
reactions ÷ views · ER floor
Posts in window
4
of 11 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 6 August 2026
Posts held
11 (11 June 2026 – 6 August 2026)
Views total
278
Reactions total
40
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Aug 2026, 03:01 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
219
Videos
41
Links
51
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
4m 10s
Average length
36s
Measured directly from 7 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
111 reactions across 11 posts, in 7 distinct kinds. The most used accounts for 41.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
46
41.4%
🔥
35
31.5%
👍
11
9.91%
❤🔥
8
7.21%
custom 5341398939088223014
7
6.31%
🤯
2
1.80%
🥰
2
1.80%
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 isTelegram’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 11 of the 11 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 111reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 11 June 2026 to 6 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.
🧿🧿🧿 Собственнику не нужен экран из сорока показателей
Чем выше уровень руководителя, тем меньше случайных цифр должно попадать в его поле зрения
Собственнику нужны показатели, которые действительно влияют на решения:
✅ выполнение плана по выручке
✅ маржинальность
✅ ФОТ
🔖 При этом универсального набора KPI не существует. Для одной концепции критичны скорость обслуживания и оборачиваемость, для другой важнее средни…
🧿🧿🧿 Бесполезность дашборда просто проверить: после его просмотра непонятно, что именно нужно изменить
Если данные не приводят к конкретному действию, это пока просто красивый экран. Аналитика начинается там, где появляется управленческое решение⚡
🧿🧿🧿 Управляющий может провести всё утро в чатах и так и не понять, что на самом деле происходит с точкой
➡️ ПОЭТОМУ СНАЧАЛА ЦИФРЫ, потом сообщения:
🧿 Выручка покажет результат
🧿 Списания покажут потери
🧿 ФОТ в % покажет, насколько эффективны затраты на команду
А уже после этого можно разбираться, где появилась просадка и что нужно изменить сегодня, чтобы сохранить рентабельность
🧿🧿🧿🧿 Проверьте, насколько ваша система аналитики справляется сейчас
🔖 Чек-лист:
☐ Если сотрудник, который собирает отчёты, не выйдет на работу, никто не сможет быстро понять, что происходит с бизнесом.
☐ Отчёт собирают несколько дней, а анализируют за десять минут. К моменту принятия решения данные уже успевают устареть.
☐ Выручка, расходы и реклама находятся в разных системах, а итоговый отчёт хранится в отдельн…
🧿🧿🧿 Как работать с отзывами, чтобы они реально помогали бизнесу?
🧿 Разложите негатив по категориям
Кухня, бар, сервис, чистота, скорость, атмосфера
Так отзывы перестают быть просто потоком «что-то пошло не так» и превращаются в понятную картину
Например, вы видите, что большая часть негатива связана не с кухней, а с сервисом. И это уже не паника, а конкретная управленческая задача
➖➖➖➖➖
🧿Смотрите глубже рейтинг…
Запускать аналитику страшно, потому что цифры могут показать не то, что хочется увидеть 🙊
Вернулись с главных мероприятий IT и HoReCa и "по горячим следам" делимся полезными карточками - как преодолеть страхи внедрения аналитики и data-driven в любом бизнесе ⚡️
Делаем глубокий вдох, изучаем и применяем маленькие шаги уже сегодня 🔛
Команда СОВА на связи 🦉
Скачать презентацию с выступления Валентины можно по ссылке ⬇️
Цифры вместо интуиции: как выстроить управление бизнесом в реальном времени с помощью данных и AI 🦉
Валентина Головко выступила на GASTREET 2026 🔥
Важность операционной эффективности и управление ею через данные в очередной раз подтвердились полным залом в 10:00 в последний день форума ⚡️
Уже некуда откладывать внедрение data-driven, за этим будущее и развитие бизнеса.
Валентина в своем выступлении рассказала:
🟡 как она с командой управляет пекарнями КЕКС (36 объектов) через данные уже 3 года
🟡важности переход…
Валентина Головко рассказывает о цифрах вместо интуиции: как выстроить управление бизнесом в реальном времени о помощью данных и Al.
Прямо сейчас — Риксос (Баллрум)
Showing the 11 most recent of 11 posts we hold for @sovabusiness. 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.
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.
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.
“СОВА - Data-driven, HoReCa, IT” (@sovabusiness), 124 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/sovabusiness.
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.
