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Channel

AI да маркетинг

@marketing_da_ai

On this record: Topic · Observations · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

95,491subscribers

-13,634 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1003804048639
TypeChannel
Username@marketing_da_ai
DescriptionРассказываем, как работать с AI и новыми технологиями вместо того, чтобы бороться с ними.
CreatedBetween 1 February 2026 and 30 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live4 October 2026
Measurements held36
Confirmed unchanged1 time, most recently 4 October 2026
On Telegramt.me/marketing_da_ai

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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 why it has no browse page of its own yet.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Views per post sit far below this size band

185 average views per post against 95,491 subscribers — an engagement rate of 0.194%. Across the 8,320 registered channels in the same cohort — 31,625–99,978 subscribers, posting mainly in Russian — the middle half sit between 5.05% and 20.9%, with a median of 10.4%.

What this was computed from
Window30 days (4 September 2026 – 4 October 2026)
Posts measured22 of 22 published in the window (22 exact, 0 rounded by Telegram)
Views totalled4,065
Mature posts only0.194% over 22 posts read at least 24h after publication
Subscribers95,491 measured 4 October 2026
Cohortb31623:rus · 8,320 channels · p10 2.54% · p25 5.05% · p50 10.4% · p75 20.9% · p90 35.5%
Position in cohort0.625th percentile · 1/53 the cohort median
Uncertainty±0% of the figure, from Telegram’s rounding
Post languageRussian · 100.0% of the window’s posts

When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.

This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.

Recorded under the key err_low, last confirmed 4 October 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Growth

95,491132,516114,003.56 August 2026 — 109,125 subscribers6 August 2026 — 109,125 subscribers7 August 2026 — 109,114 subscribers8 August 2026 — 109,131 subscribers9 August 2026 — 109,175 subscribers10 August 2026 — 108,928 subscribers11 August 2026 — 108,973 subscribers12 August 2026 — 110,366 subscribers13 August 2026 — 111,461 subscribers14 August 2026 — 111,474 subscribers16 August 2026 — 132,516 subscribers17 August 2026 — 131,026 subscribers18 August 2026 — 130,203 subscribers19 August 2026 — 128,262 subscribers20 August 2026 — 127,250 subscribers22 August 2026 — 126,541 subscribers23 August 2026 — 125,732 subscribers25 August 2026 — 124,579 subscribers26 August 2026 — 123,507 subscribers27 August 2026 — 121,971 subscribers27 August 2026 — 121,107 subscribers28 August 2026 — 120,473 subscribers30 August 2026 — 120,289 subscribers31 August 2026 — 119,691 subscribers1 September 2026 — 118,931 subscribers2 September 2026 — 118,273 subscribers3 September 2026 — 118,040 subscribers5 September 2026 — 117,661 subscribers8 September 2026 — 115,495 subscribers11 September 2026 — 114,710 subscribers13 September 2026 — 114,305 subscribers14 September 2026 — 110,629 subscribers16 September 2026 — 109,917 subscribers19 September 2026 — 108,681 subscribers25 September 2026 — 100,015 subscribers4 October 2026 — 95,491 subscribers6 August 20264 October 2026
36 measurements spanning 59 days, net -13,634. 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 89,937–138,070 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)SubscribersChange
4 Oct 2026, 09:3795,491-4,524
25 Sept 2026, 22:39100,015-8,666
19 Sept 2026, 04:16108,681-1,236
16 Sept 2026, 17:39109,917-712
14 Sept 2026, 19:59110,629-3,676
13 Sept 2026, 09:15114,305-405
11 Sept 2026, 12:35114,710-785
8 Sept 2026, 20:18115,495-2,166
5 Sept 2026, 09:56117,661-379
3 Sept 2026, 09:46118,040-233
2 Sept 2026, 04:18118,273-658
1 Sept 2026, 01:18118,931-760
31 Aug 2026, 03:54119,691-598
30 Aug 2026, 01:03120,289-184
28 Aug 2026, 22:07120,473-634
27 Aug 2026, 23:04121,107-864
27 Aug 2026, 02:28121,971-1,536
26 Aug 2026, 05:25123,507-1,072
25 Aug 2026, 03:43124,579-1,153
23 Aug 2026, 23:17125,732first reading

Engagement

49 posts held, back to 30 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 122 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.194%
avg views ÷ 95,491 subscribers
Avg views / post
185
22 posts measured
Reaction rate
7.68%
reactions ÷ views · ER floor
Posts in window
22
of 49 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 2 October 2026
Posts held49 (30 July 2026 – 2 October 2026)
Views total4,075
Reactions total313
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken4 Oct 2026, 23:38 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
901
Videos
122
Links
146

Lifetime counters from Telegram’s own channel header, read 4 October 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
13m 44s
Average length
52s

Measured directly from 16 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

725 reactions across 49 posts, in 13 distinct kinds. The most used accounts for 32.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤23532.4%
👍16522.8%
🔥15521.4%
🤔496.76%
😁314.28%
👏263.59%
💯253.45%
🤯223.03%
❤‍🔥50.69%
🤩50.69%
🥰40.552%
🎉20.276%
😢10.138%

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 49 of the 49 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 725 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 49 most recent posts we hold, published 30 July 2026 to 2 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
9
across the posts below
Posts paid on
9
of 49 we hold a reading for · 18%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @marketing_da_ai. 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 49 most recent posts we hold for this entry, published 30 July 2026 to 2 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.

Recent posts

2 Oct 2026, 14:10 UTC145 views14 reactionsread 4 October 2026
Photo

🙂 Муха, которая играет в Doom, паркуется и торгует криптовалютой 3 сентября Google Research и HHMI Janelia представили полную карту центральной нервной системы самца дрозофилы: более 166 тысяч нейронов и около 125 миллионов связей. Её создавали несколько лет: при помощи AI собрали 3D-реконструкцию нервной системы по снимкам электронного микроскопа, а специалисты вручную проверили результат. Уже на следующий день ци…

❤5👍3🔥2🥰2😁2

1 Oct 2026, 11:19 UTC154 views13 reactions1 Starread 4 October 2026
Photo

🙂 Как AI-компании превращают кофейни в маркетинговые площадки Anthropic открыла поп-ап с кофе и книгами, Perplexity запустила постоянную кофейню в Сеуле, Microsoft угощала кофе покупателей в магазинах электроники, а AI-стартап Corgi сделал круглосуточное кафе для айтишников. За последние два года собственные кофейни стали для AI-компаний почти таким же привычным инструментом, как мерч. В карточках разбираем эти кей…

❤6👍4🔥2😁1

30 Sept 2026, 08:53 UTC99 views13 reactionsread 4 October 2026
Forwarded from @sbermarketingPhoto

💡 СберМаркетинг на ResearchExpo 2026: исследования, которые помогают принимать решения сегодня и проектировать будущее 2 октября на ежегодной выставке-конференции ResearchExpo 2026 СберМаркетинг представит специальную программу в зале «Пятый элемент». В течение дня представители направлений исследований, маркетинга, продукта и клиентского опыта обсудят, как меняется роль исследователя: от изучения пользовательского…

❤4🔥4👍3❤‍🔥1👏1

30 Sept 2026, 07:05 UTC157 views16 reactionsread 2 October 2026
Photo

⚡️ AI-агенты начали придумывать собственные слова Исследователи лаборатории Emergence объединили автономных AI-агентов в группы и поставили перед ними задачи, требующие сотрудничества. Через несколько дней модели начали самостоятельно создавать новые слова, сокращения и общие значения, а их переписка становилась всё менее понятной людям. В карточках разбираем, какие выражения появились у AI-агентов, почему они форм…

🔥7❤4👍4👏1

29 Sept 2026, 09:47 UTC185 views18 reactions1 Starread 2 October 2026
Photo

🔗 AI-токены становятся новой валютой лояльности в Китае Китайский бизнес начал экспериментировать с необычной механикой: вместо привычных бонусных баллов, скидок и кэшбека компании предлагают клиентам доступ к вычислительным ресурсам AI-моделей — токены, лимиты запросов, минуты работы агентов или премиальные модели. В карточках разбираем, как AI-трафик встраивается в клиентский сервис и становится новой маркетингов…

❤7👍5🔥4❤‍🔥1💯1

28 Sept 2026, 07:05 UTC217 views13 reactionsread 1 October 2026
Photo

💡 Что нового у AI-продуктов Разбираем последние новинки и их возможности. ➡️ Claude Opus 5.5 Anthropic представила Opus 5.5 — новую флагманскую модель. По большинству задач она сопоставима с Fable 5.1, но в среднем на 40% дешевле и на 30% быстрее Opus 5. В Anthropic отмечают, что Opus 5.5 лучше справляется с миграцией и аудитом кода, реже делает что-то без прямого указания пользователя и лучше распознаёт попытки п…

❤5👍4🔥3😁1

25 Sept 2026, 07:10 UTC276 views18 reactionsread 29 September 2026
Photo

💻 AI-агенты в играх: планы, ошибки и неожиданные решения Компания Vals AI отправила модель OpenAI GPT-6 Astra в Minecraft на 141 час. Она продвинулась дальше любой другой модели в тестах лаборатории — но затем крипер взорвал сундук со всеми ценными ресурсами. После этого Astra несколько часов почти без остановки сажала картошку. Игры позволяют увидеть, как AI справляется со сложными задачами: планирует действия, уч…

❤6😁6🔥5🎉1

24 Sept 2026, 09:59 UTC228 views14 reactionsread 28 September 2026
Photo

🙂 AI в рекламе, кино и видеопродакшене: 6 кейсов лета 2026 года Coca-Cola превратила Жозе Моуринью в цифрового героя, Google реконструировала гол Пеле без единой видеозаписи, Netflix использовала AI примерно в 300 проектах, а Private Island собрала бойзбенд из техномиллиардеров. В карточках разбираем эти и другие кейсы лета 2026 года. Бренды и студии использовали AI для доработки отдельных сцен, создания новых форм…

❤6👍4🔥3😁1

23 Sept 2026, 09:49 UTC207 views15 reactions1 Starread 27 September 2026
Video

🎥 От «сломанных» рук до реалистичных роликов: как развивается AI-видео от года к году В 2023 году завирусился ролик, в котором нейросеть генерирует Уилла Смита, поедающего спагетти: у него меняются черты лица, появляются лишние руки, а еда ведёт себя вопреки законам физики. Со временем этот сюжет стал неформальным тестом для моделей генерации видео. Сегодня нейросети справляются с ним гораздо лучше: ролики выглядят …

❤5👍5🔥4🤯1

22 Sept 2026, 13:07 UTC145 views15 reactionsread 24 September 2026
Photo

🚀 Explainable AI: почему важно понимать решения алгоритмов Чем выше уверенность человека в том, что нейросеть справится с задачей, тем реже он критически оценивает её ответы. К такому выводу пришли исследователи Microsoft и Университета Карнеги — Меллона, проанализировав опыт 319 специалистов и 936 примеров использования GenAI в работе. В карточках разбираем, что такое Explainable AI, почему убедительный ответ не в…

👍5❤4🤯2😁2❤‍🔥1👏1

21 Sept 2026, 10:14 UTC173 views10 reactionsread 24 September 2026
Photo

🙂 Что нового у AI-продуктов За последние пару недель вышло несколько крупных обновлений. Разбираем новинки и их возможности. ➡️ DeepSeek V4.1-Flash DeepSeek выпустила новую модель V4.1-Flash. В неё встроили понимание изображений, поэтому отдельная «визуальная» версия больше не нужна. По бенчмаркам новинка обходит прежний флагман DeepSeek-V4-Pro, а также почти во всех тестах — китайских конкурентов Kimi K3 и GLM-5.…

❤4👍2👏2🔥2

18 Sept 2026, 13:09 UTC195 views15 reactions1 Starread 24 September 2026
Photo

🐱 Как AI-агенты нарушают правила и разоблачают друг друга AI-агентам можно поручить подготовку маркетинговых кампаний, распределение бюджета и сбор отчётности. Но если не выстроить эффективную систему контроля, цифровые сотрудники могут вести себя недобросовестно. В математическом эксперименте Google DeepMind один агент обнаружил лазейку, а другие начали её копировать. Нашлись и несогласные, которые пытались остано…

🔥6❤4👍4🤩1

Showing the 12 most recent of 49 posts we hold for @marketing_da_ai. 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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.

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 4 October 2026 — this entry's latest reading, not the date you are reading this.

“AI да маркетинг” (@marketing_da_ai), 95,491 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/marketing_da_ai.

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.