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Channel

Я пользуюсь Мозгом!

@ilovemozg

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

1,708subscribers

+64 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002355658343
TypeChannel
Username@ilovemozg
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live14 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/ilovemozg

Growth

1,6431,7291,6867 August 2026 — 1,644 subscribers7 August 2026 — 1,643 subscribers10 August 2026 — 1,729 subscribers14 August 2026 — 1,708 subscribers1,7087 August 202614 August 2026
4 measurements spanning 7 days, net +64. 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 1,630–1,742 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 07:061,708-21
10 Aug 2026, 21:451,729+86
7 Aug 2026, 17:051,643-1
7 Aug 2026, 11:471,644first reading

Engagement

18 posts held, back to 13 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
35.4%
avg views ÷ 1,708 subscribers
Avg views / post
605
15 posts measured
Reaction rate
1.96%
reactions ÷ views · ER floor
Posts in window
15
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
WindowRolling 30 days · latest post in window 7 August 2026
Posts held18 (13 July 20267 August 2026)
Views total9,075
Reactions total178
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 17:53 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.

Reaction mix

209 reactions across 18 posts, in 9 distinct kinds. The most used accounts for 33.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
6933.0%
🔥5827.8%
👍4220.1%
custom 5271912827869737544146.70%
👏125.74%
🥰52.39%
🤩41.91%
31.44%
❤‍🔥20.957%

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 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 209reactions 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 13 July 2026 to 7 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.

Recent posts

7 Aug 2026, 14:09 UTC128 views9 reactionsread 7 August 2026
Video message

Video message, posted without a caption

3👍3🔥3

7 Aug 2026, 14:09 UTC131 views9 reactionsread 7 August 2026

⚡️ Вы уверены, что закупки в вашем ресторане действительно под контролем? Закупочные цены растут, на складе копятся лишние остатки, увеличиваются списания – и все это незаметно съедает прибыль ресторана. Александр Копылков и команда экспертов MOZG собрали гайд по 10 ключевым отчетам, доступным в системе «Мозга». Они помогут контролировать закупочные цены, себестоимость, списания, результаты инвентаризации и товарны

4👍3🔥2

6 Aug 2026, 12:16 UTC533 views9 reactionsread 7 August 2026
Photo

Обновленные данные по «Индексу Цезаря» за июль 2026 года! «Индекс Цезаря» – это ежемесячный показатель, который отражает динамику средней цены самого продаваемого салата в России. Это наш взгляд на инфляцию в ресторанной индустрии. 🧠 Индекс рассчитан аналитической платформой MOZG на основе данных из 1200+ ресторанных компаний разных форматов и ценовых сегментов по всей России. В июле 2026 года «Индекс Цезаря» сост

3👍3🔥3

3 Aug 2026, 12:05 UTC324 views8 reactionsread 7 August 2026
Photo

3 подхода, которые изменят отношение к ФОТ Шеф-повар говорит, что сотрудников не хватает и команда перегружена. Собственник видит превышение бюджета по ФОТ и требует сокращать расходы. Знакомая ситуация? Обычно каждая сторона оценивает её со своей позиции, поэтому разговор быстро заходит в тупик. Но ФОТ – это не просто процент от выручки или количество сотрудников в штате. Итоговая цифра зависит от графиков, загру

👍42🔥2

31 Jul 2026, 14:46 UTC352 views13 reactionsread 7 August 2026
Photo

Как МОЗГ помогает франшизе «Контакт Бар»? Алексей Гамов, CEO франшизы «Контакт Бар», рассказал, почему команда работает с системой МОЗГ уже несколько лет: «Ресторатору жизненно необходим инструмент для повседневной аналитики в режиме online или почти online» Полную версию отзыва читайте по ссылке 👈🏻 В ресторанном бизнесе решения нужно принимать быстро. Ждать конца месяца, чтобы увидеть отклонения и только потом н

5👏4🔥4

30 Jul 2026, 14:24 UTC366 views9 reactionsread 7 August 2026
Photo

💙 Коллеги, делимся записью третьего вебинара «Мозг.Скан» В прямом эфире ведущий эксперт экономики Александр Копылков разобрал отчеты и экономику действующего ресторана. Анализ показал потенциал роста прибыли почти на 1 млн рублей и возможность высвободить еще около 1,5 млн рублей, замороженных в товарных остатках. Вместе с представителем ресторана: 🔹 нашли потенциал роста продаж и определили, с какими показателям

3🔥3custom 52719128278697375443

29 Jul 2026, 12:03 UTC748 views18 reactionsread 7 August 2026
Photo

🎁 Мы разыгрываем участие в онлайн-курсе «Управление экономикой и прибылью ресторана»! Это ваша возможность бесплатно присоединиться к новому потоку, который стартует уже 15 августа, и разобраться, как управлять экономикой ресторана системно. Чтобы принять участие в розыгрыше: 1 – Подпишитесь на telegram-канал Welcomepro; 2 – Подпишитесь на telegram-канал MOZG; 3 – Нажмите кнопку «Участвую». 2-ух победителей выб

6👍6custom 52719128278697375446

29 Jul 2026, 08:16 UTC391 views12 reactionsread 7 August 2026
Photo

Коллеги, начинаем в 12.00 по мск ⚡️ Сканируем и разбираем экономические отчеты действующего ресторана с экспертом и операционным директором консалтинга Welcomepro. На примере реального ресторана эксперт Александр Копылков: 🔹 познакомит с методиками экономического анализа ресторанов 🔹 разберет потенциалы по росту прибыли через работу с данными 🔹 соберет ППР по основной задаче бизнеса 🔹 сформирует набор аналитик

4👍4🔥4

27 Jul 2026, 12:57 UTC411 views14 reactionsread 7 August 2026

💬 Что, если Мозг сам покажет, где ваш ресторан недополучает прибыль? В видео рассказываем, как раздел «Потенциалы» рассчитывает в рублях скрытые возможности ресторана и помогает определить, на каких задачах команде стоит сосредоточиться в первую очередь. 👉 Записывайтесь на демо платформы "Мозг": 📱 Telegram ➡️ Max 💻 Заявка на сайте ___ ▶️ Читайте "Я пользуюсь Мозгом!" также в Max

5🔥5👏4

27 Jul 2026, 12:57 UTC400 views12 reactionsread 7 August 2026
Video message

Video message, posted without a caption

5🤩4🔥3

24 Jul 2026, 12:27 UTC929 views9 reactionsread 7 August 2026
Photo

💙 МОЗГ.СКАН. Третий выпуск 29 июля в 12:00 (мск) ждем вас в прямом эфире уникального проекта "Мозг.Скан". Сканируем и разбираем экономические отчеты действующего ресторана с экспертом и операционным директором консалтинга Welcomepro. На примере реального ресторана эксперт Александр Копылков: 🔹 познакомит с методиками экономического анализа ресторанов 🔹 разберет потенциалы по росту прибыли через работу с данными

33🔥3

22 Jul 2026, 12:34 UTC≈2,810 views18 reactionsread 7 August 2026
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Коллеги, у нас хорошие новости! ⚡️ Мы добавили новые функции – теперь работать с «Мозгом» стало еще удобнее! Рассказываем, что нового появилось в платформе 👇🏻 🔹 В отчете «Основные показатели» у наполняемости и средней цены появилась кнопка «Анализ по мотивам». Теперь из отчета можно сразу перейти к подробной диагностике и разобраться в причинах роста или снижения показателей. 🔹 В «Диагностику MotiveMarketing» доб

🔥85👍5

Showing the 12 most recent of 18 posts we hold for @ilovemozg. 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.

Citation-graph rank

Citation-graph rank — 30,040 of 1,481,217entries 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

Names

Channels on the register whose handles appear in this channel's posts.

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 14 August 2026 — this entry's latest reading, not the date you are reading this.

“Я пользуюсь Мозгом!” (@ilovemozg), 1,708 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/ilovemozg.

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.