Telegram RegisterThe public register of Telegram
Telegram profile photo for Подруга маркетолог (Маргарита Захарова)

Channel

Подруга маркетолог (Маргарита Захарова)

@marketing_dir

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Cite this entry

33,023subscribers

+1,334 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001762922547
TypeChannel
Username@marketing_dir
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live20 August 2026
Measurements held13
Confirmed unchanged1 time, most recently 20 August 2026
On Telegramt.me/marketing_dir

Growth

31,68933,02332,3567 August 2026 — 31,689 subscribers7 August 2026 — 31,768 subscribers9 August 2026 — 31,936 subscribers9 August 2026 — 32,072 subscribers11 August 2026 — 32,190 subscribers12 August 2026 — 32,316 subscribers13 August 2026 — 32,425 subscribers14 August 2026 — 32,558 subscribers15 August 2026 — 32,614 subscribers17 August 2026 — 32,696 subscribers18 August 2026 — 32,756 subscribers19 August 2026 — 32,838 subscribers20 August 2026 — 33,023 subscribers7 August 202620 August 2026
13 measurements spanning 14 days, net +1,334. 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 31,489–33,223 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
20 Aug 2026, 16:2633,023+185
19 Aug 2026, 14:4232,838+82
18 Aug 2026, 14:2432,756+60
17 Aug 2026, 11:1832,696+82
15 Aug 2026, 19:3932,614+56
14 Aug 2026, 12:4832,558+133
13 Aug 2026, 03:5332,425+109
12 Aug 2026, 03:5332,316+126
11 Aug 2026, 02:5832,190+118
9 Aug 2026, 23:3732,072+136
9 Aug 2026, 00:5131,936+168
7 Aug 2026, 23:0431,768+79
7 Aug 2026, 02:1631,689first reading

Engagement

31 posts held, back to 23 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 31 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
17.1%
avg views ÷ 33,023 subscribers
Avg views / post
5,640
30 posts measured
Reaction rate
5.56%
reactions ÷ views · ER floor
Posts in window
31
of 31 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 20 August 2026
Posts held31 (23 July 202620 August 2026)
Views total169,270
Reactions total9,412
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken20 Aug 2026, 14:12 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
3m 38s
Average length
55s

Measured directly from 4 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

9,412 reactions across 30 posts, in 18 distinct kinds. The most used accounts for 25.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2,35525.0%
🔥1,51016.0%
💯1,08011.5%
👍8549.07%
😍7588.05%
🤩7467.93%
❤‍🔥7167.61%
🎉6897.32%
🥰6637.04%
👏200.212%
🤯60.064%
40.042%
🙏40.042%
👌30.032%
👀10.011%
🗿10.011%
😁10.011%
😱10.011%

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 30 of the 31 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 9,412reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 31 most recent posts we hold, published 23 July 2026 to 20 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
28
across the posts below
Posts paid on
14
of 30 we hold a reading for · 47%
Most on one post
5
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @marketing_dir. 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 31 most recent posts we hold for this entry, published 23 July 2026 to 20 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.

Recent posts

20 Aug 2026, 13:54 UTC≈1,000 views129 reactionsread 20 August 2026
Photo

Пока ужинала агент по лид-магнитам сделал вот такую книжку 🙂 в этой же сфере [ссылка на книгу-тест] Сделал полностью сам. Я только тему задала. Получилась уже мини-воронка reels + книга Как вам? Завтра покажу, как работают агенты, если вам это интересно 👀

💯105❤‍🔥75🤩5🔥4👌1🗿1😍1

20 Aug 2026, 12:05 UTC≈1,170 views62 reactions3 Starsread 20 August 2026
Video

До и после использования агента по рилсам (один из видов B-roll) Посмотрите, как меняется восприятие информации 🙂 + давайте сделаем лид-магнит для этой ниши, чтобы вы посмотрели пример + сделаем презу Показать процесс - Как работают агенты? (чтобы вы увидели, что это не требует никаких сложных технических навыков) Например, видео выше агент сделал пока я ездила с сыном в школу и покупала ему форму 😁 Этого агента

43🔥9❤‍🔥7👍2😱1

20 Aug 2026, 05:08 UTC≈4,860 views143 reactions2 Starsread 20 August 2026
Photo

Как начать зарабатывать на нейросетях уже в этом месяце 💸 Записала видео про новую профессию — менеджер AI-агентов. И про то, почему куча людей уже делает агентов, но ни денег, ни клиентов у них с этого нет. Небольшой спойлер 👇 У агента есть два этапа. 💡 Первый — агент технически создан. Он включается, что-то выдаёт, формально работает. 💯 Второй — агент оттестирован и приносит результат, на который смотришь и ду

🔥12311🥰7👏2

19 Aug 2026, 06:11 UTC≈5,590 views210 reactionsread 20 August 2026

🤖 Меня бомбит на эту тему... Купила англоязычное обучение, где обещали готовую команду агентов под весь контент. Пошла из любопытства — интересно же, из чего человек такое собирает. Агенты там есть. Реально включаются, реально что-то выдают. 🫠 Только то, что они выдают — не работает Их собрали за месяц и ни разу не проверили на живых задачах. Технически рабочие агенты. Но результатов не будет…. Пример 👇 Агент д

💯12837🔥26👍10🥰7🎉1😍1

19 Aug 2026, 02:49 UTC≈7,100 views192 reactionsread 20 August 2026
Photo

🔍 Нашла исследование, которое объясняет, почему ИИшные тексты палятся даже там, где нет ни одного длинного тире Называется StoryScope. [выше результат исследования: формы текста от человека и от разных ИИ моделей] Университет Мэриленда и Google DeepMind взяли 61 608 рассказов — человеческих и написанных пятью нейросетями по одинаковым заданиям. И смотрели на нарратив. На то, как вообще устроена история. Оказалось,

🔥14921👏11❤‍🔥5👍4🎉1😍1

18 Aug 2026, 03:15 UTC≈5,320 views107 reactionsread 20 August 2026
Video

Так вот... Он очень много разрабатывает для нейросетей. Например он упаковал свой дизайн-вкус в навык... 👉 https://emilkowal.ski/skill Один из его навыков — apple-design. Эмиль пересмотрел лучшие видео с Apple WWDC и вытащил оттуда 17 принципов дизайна и моушна. Этот навык можно применять, если хотите сделать сайт болеее премиальным. А еще можно установить навыки Эмиля и потом дать скриншоты того, что вы делаете

🔥3826🥰9👍8❤‍🔥7🎉5🤩4🙏4

18 Aug 2026, 03:14 UTC≈4,510 views29 reactionsread 20 August 2026
Photo

Я давно слежу за дизайнером Emil Kowalski. Он дизайн-инженер. Делает интерфейсы и анимации того уровня, когда открываешь сайт и залипаешь, хотя формально там ничего не происходит. Его библиотеки Sonner и Vaul стоят у половины нормальных веб-продуктов.

🔥13👍84🎉1👏1💯1🥰1

11 Aug 2026, 05:52 UTC≈6,250 views184 reactions4 Starsread 20 August 2026
Photo

самые важные аудио, которые могут дать опору, направление, инсайт или просто вдохновить вас Я отобрала наиболее важные: 👉 Теория игр и как с помощью нее я выросла в доходе https://t.me/marketing_dir/3226 👍 Самый дорогой навык 2026 ... https://t.me/marketing_dir/3269 👉 Метод "часы ясности" делает тревожников продуктивными и богатыми https://t.me/marketing_dir/3193 👉 Подкаст, который убирает ощущение кризиса https

🔥40👍27❤‍🔥25💯21🥰19😍1613🤩12

10 Aug 2026, 13:18 UTCviews —

Подруга маркетолог (Маргарита Захарова) pinned a photo

10 Aug 2026, 13:16 UTC≈6,220 views293 reactionsread 20 August 2026
Photo

ПОЛНАЯ БАЗА ИНСТРУМЕНТОВ ПРОДВИЖЕНИЯ ЧАСТЬ 1 - здесь https://t.me/marketing_dir/3044 ЧАСТЬ 2 - здесь https://t.me/marketing_dir/3146 ЧАСТЬ 3 - здесь https://t.me/marketing_dir/3304 ЧАСТЬ 4 - здесь https://t.me/marketing_dir/3405 Часть 5 ⚙️ Лайфхаки Claude от создателя OpenClaw (+ секретные команды) https://t.me/marketing_dir/3406 🔄 Метод петли — результат без бесконечных правок https://t.me/marketing_dir/3410

🔥7246🤩39👍37😍34❤‍🔥31🎉30👏2

10 Aug 2026, 06:10 UTC≈6,210 views837 reactions5 Starsread 20 August 2026
File

Не включайте это аудио, если вы здесь только ради готовых PDF-ок и инструментов по нейросетям. В новом подкасте рассказала про практики, которые лично мне очень помогли в жизни. Некоторые буквально меня вытащили. ❤️ 01:49 — прайминг от Тони Роббинса 04:28 — моя практика 08:03 — как просить подсказку 10:46 — почему я была жёстким скептиком 13:01 — инсайт от Маргулана Сейсенбая 17:12 — страх против веры 18:58 — чек Д

655🔥54❤‍🔥36👍18🤩18🎉14🥰14😍13

7 Aug 2026, 06:47 UTC≈6,840 views221 reactions1 Starread 20 August 2026
File

Как снять yapping-видео уже буквально завтра Первое — тезисы вместо сценария. ▪️Выберите какую-то острую, актуальную тему, по поводу которой сейчас много споров в сети. ▪️Наговорите любой нейросети все свои мысли на эту тему — просто как есть, потоком. ▪️А потом попросите выделить из этого ключевые тезисы. И когда будете записывать видео, просто двигайтесь от тезиса к тезису. Зачем это нужно: не все умеют классн

67🔥42👍27🎉19🤩17💯15🥰15😍12

Showing the 12 most recent of 31 posts we hold for @marketing_dir. 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 edited after publishing

@marketing_dir edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
9 August 2026
Most recent edit
20 August 2026

Citation-graph rank

Citation-graph rank — 317,440 of 1,568,528entries 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

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 1 registered channel — 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 20 August 2026 — this entry's latest reading, not the date you are reading this.

“Подруга маркетолог (Маргарита Захарова)” (@marketing_dir), 33,023 subscribers as measured 20 August 2026. Telegram Register, tgregister.com/channel/marketing_dir.

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.