Все лучшее в теме Social Media Marketing от Дамира Халилова: инструменты, сервисы, книги, статьи.
Регистрация в РКН:
https://knd.gov.ru/license?id=6787a7b41e4e233a711c058b®istryType=bloggersPermission
Created
17 June 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Education — 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 58% 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
56 measurements spanning 88 days, net -296. 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 23,071–23,464 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 56
Measured (UTC)
Subscribers
Change
2 Nov 2026, 01:19
23,123
+3
1 Nov 2026, 03:16
23,120
-2
31 Oct 2026, 03:52
23,122
+6
30 Oct 2026, 04:08
23,116
-8
29 Oct 2026, 06:09
23,124
-3
28 Oct 2026, 04:09
23,127
-10
25 Oct 2026, 22:55
23,137
+8
24 Oct 2026, 23:27
23,129
-12
23 Oct 2026, 22:37
23,141
-2
22 Oct 2026, 23:07
23,143
-7
21 Oct 2026, 18:50
23,150
-19
20 Oct 2026, 13:56
23,169
-12
18 Oct 2026, 11:19
23,181
-13
17 Oct 2026, 14:05
23,194
-15
16 Oct 2026, 11:21
23,209
-5
15 Oct 2026, 09:59
23,214
+1
14 Oct 2026, 10:09
23,213
-14
12 Oct 2026, 23:17
23,227
-30
8 Oct 2026, 14:58
23,257
-23
4 Oct 2026, 05:41
23,280
first reading
Engagement
16 posts held, back to 14 October 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 99 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.03%
avg views ÷ 23,123 subscribers
Avg views / post
1,630
3 posts measured
Reaction rate
1.68%
reactions ÷ views · ER floor
Posts in window
3
of 16 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 20 October 2026
Posts held
16 (14 October 2025 – 20 October 2026)
Views total
4,880
Reactions total
82
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Nov 2026, 14:17 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
139
Videos
19
Links
569
Lifetime counters from Telegram’s own channel header, read 3 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.
Reaction mix
1,208 reactions across 16 posts, in 12 distinct kinds. The most used accounts for 38.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
469
38.8%
❤
457
37.8%
👍
79
6.54%
👏
79
6.54%
🎉
74
6.13%
💯
22
1.82%
🥰
8
0.662%
🤔
7
0.579%
😁
6
0.497%
🍓
3
0.248%
😢
2
0.166%
😱
2
0.166%
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 16 of the 16 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 1,208 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 14 October 2025 to 20 October 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
4
across the posts below
Posts paid on
4
of 16 we hold a reading for · 25%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @damirkhalilov. 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 16 most recent posts we hold for this entry, published 14 October 2025 to 20 October 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.
Завтра в 15:00, в рамках проекта «Встречаемся в Читай Городе», мы повидаемся с Дамиром Халиловым.
Предпринимателем, пионером Smm в России и создателем одного из самых известных агентств GreenPR.
Сегодня он во всю известен как специалист по работе с искусственным интеллектом и создатель целой школы.
А еще он писатель. В том смысле, что он пишет книги не только образовательные, но и художественные.
Нам будет о чем …
AI-ПРАКТИК, СУРОВЫЙ ПИТЕРСКИЙ И 22 ПЛАГИНА
Всего несколько дней назад мы презентовали наш новый флагманский курс «AI-практик».
В 2023 году я начал заниматься нейросетями для маркетинга, и тогда работа с AI была равна написанию промптов. Позже поочерёдно появились агенты, интеграции (n8n, Zapier и ко), изменивший игру вайбкодинг.
Но 26-й перевернул вообще всё! Десятки новых инструментов, тонны новых функций у лидер…
AI-2027: ПОГРУЖЕНИЕ В СОЗДАНИЕ ПЛАГИНОВ, НАВЫКОВ И В ВАЙБКОДИНГ
А ведь давненько у нас с Вами не было интенсивов! Таких, чтобы искрились от практики, воркшопов, новейших техник, авторских фишек. Чтобы после них — море идей и их воплощений, новые проекты, новые горизонты, инструментарий на все случаи жизни. При этом с бесплатным участием. Почитай, полгода прошло с последнего интенсива. А для AI полгода — это целая эп…
Дети и искусственный интеллект: ЗА и ПРОТИВ
Кто-то принципиально не покупает ребенку смартфон, а у кого-то уже в 8 лет дети ведут блоги, генерят с легкостью ИИ-изображения, да и родители берут советы у ИИ по обучению и воспитанию детей.
Вы сами в каком лагере?
Как взять пользу от ИИ и превратить его потенциальные опасности в возможности?
Мы с давним другом Дамиром Халиловым (у которого в этом году вышла книга «Не…
ТРИ МОИ НОВЫЕ КНИГИ: ЛАБОРАТОРИЯ ДАМИРА ХАЛИЛОВА
Необычное чувство. Увидеть опубликованными сразу три свои книги. И вдруг понять, что за 13 лет у тебя вышло уже девять книг.
В общем, в прошлом году «Альпина Паблишер», вдохновлённая успехом предыдущих книг, предложила запуск моей авторской серии под общим названием «Дай списать промт. Лаборатория Дамира Халилова». Авторская серия — явление уникальное для российской …
44.
Как же нежно я люблю прошедший год: ароматный, бездонный, терпкий на вкус, неистово подмигивающий и прямо-таки истекающий любовью.
Векторы любви в этом году были крайне разносторонними, при этом абсолютно взаимными: с семьёй, друзьями, нашими учениками и подписчиками, с нейросетями (немаловажные отношения в 2026-м), с творчеством, бизнесом, сотрудниками, музыкой, литературой, Барселоной, Римом, Москвой, Буэнос-А…
Вот уже много лет каждый год я выкладываю список прочитанных за год книг. В этом году я публикую его в моём новом канале «Культурный капитал», причём сразу за 2 года: 2024–2025. Получилось 113 книг, прочесть и посмотреть оценки можно здесь.
НОВОГОДНИЙ ПОДАРОК ОТ ДАМИРА
Друзья!
Хочу пожелать Вам:
🎨 Творчества — без натуги!
❤️ Любви — без борьбы!
⚙️ Продуктивности — без надрыва!
🧠 Будней — без тревоги!
🌿 Выходных — без забот пустых!
🧭 Решений — без сожалений!
🤖 Нейросетей — без галлюцинаций!
💡 Идей — без ограничений!
🎯 Фокуса — без размытия!
🔀 Выбора — без рефлексии!
⚡ Энергии — без энергетиков!
✨ Счастья — без условий!
📡 Смыслов — без шума!
🛤️ Пути — …
Знаете этот распространённый литературный и киноштамп: сможет ли автор бестселлера написать вторую книгу, не уступающую первой? Я автор четырёх бестселлеров (три из которых лонгселлеры), но, несмотря на это, для меня тоже волнительна судьба двух моих новых книг.
Ты долго работаешь над книгой, делишься в ней сокровенным — и вот он, момент истины: найдут ли книги отклик у читателя. Прошёл месяц с момента выхода «Нейро…
ЧЁРНАЯ ПЯТНИЦА: ПОСЛЕДНИЙ ШАНС КУПИТЬ НАШИ ПРОДУКТЫ СО СКИДКОЙ ДО 80%
Итак, наша распродажа выходит на финишную прямую. Время не ждёт, и уже в понедельник скидки сгорят и станут историей. Но сейчас у Вас есть возможность приобрести наши продукты с выгодой до 80%.
Чёрная пятница здесь!
В распродаже участвуют:
AI-сотрудники. Я люблю каждого из них, но вот топ-5, которых я рекомендую приобрести в первую очередь:
⭐️…
СРАЗУ ДВЕ МОИ НОВЫЕ КНИГИ!
Ну что же, с трепетом, гордостью и бесконечной радостью сообщаю, что в издательствах «Альпина Паблишер» и «Альпина.Дети» вышли две мои новые книги (пятая и шестая в моей библиографии).
📖 «Нейросети могут всё: 254 универсальных промта для счастливой, здоровой и яркой жизни»
Ozon
Wildberries
«Альпина»
«Читай-город»
📖 «Нейросети для детей и родителей. 204 промта для учебы, здоровья, воспита…
❤50🔥49👍12👏6🎉3😁1
Showing the 12 most recent of 16 posts we hold for @damirkhalilov. 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 recorded as deleted after publishing
We recorded 4 posts on @damirkhalilov as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
18 October 2026
Most recent seen missing
24 October 2026
Median time before seen missing
6 days
Seen missing in the last 30 days
4
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 3 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Промт дня (Приручаем ChatGPT, Midjourney и другие нейросети) @ai2smm · 59,193#1
DNative — блог Ткачука про SMM @dnative · 80,123#2
Миджорниум - промпты и советы для нейросететей Midjourney, Dall-e, SD, и др. @midjornium · 6,848#90
Нейроиллюстратор | Владимир Троицкий @tve_proneuro · 2,232#91
Read from Telegram’s recommendation API, most recently 18 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Промт дня (Приручаем ChatGPT, Midjourney и другие нейросети) @ai2smm · 59,193 Telegram ranks this channel #2 of 95 here — alongside 94 others — read 22 August 2026
💎 Зерокодер | Нейросети и искусственный интеллект @oqode · 39,405 Telegram ranks this channel #57 of 92 here — alongside 91 others — read 30 August 2026
Мир нейросетей - новости, обучение и заработок @pro_ai_novosti · 50,072 Telegram ranks this channel #59 of 90 here — alongside 89 others — read 25 August 2026
Нейросетевые покои: нейросети, ChatGPT, Midjourney @neural_houses · 44,165 Telegram ranks this channel #77 of 92 here — alongside 91 others — read 28 August 2026
AI Университет @neural_university_webinar · 37,098 Telegram ranks this channel #88 of 96 here — alongside 95 others — read 31 August 2026
This channel appears in 5 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 2 November 2026 — this
entry's latest reading, not the date you are reading this.
“SMM с Дамиром Халиловым” (@damirkhalilov), 23,123 subscribers as measured 2 November 2026. Telegram Register, tgregister.com/channel/damirkhalilov.
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.