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Channel

Менеджеры маркетплейсов | Вакансии

@MPmanagers

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

22,571subscribers

+527 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001718248552
TypeChannel
Username@MPmanagers
Description🔥 Ежедневная публикация свежих вакансий, а так же резюме от опытных специалистов. • Купить рекламу: https://t.me/+iVfQ8Iyk8Kg0ZTE6 • Бот с вакансиями - @LeadMagnet_MP_bot • Разместить резюме - @MPdesigns_bot • Админ - @Art_666999
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 live10 November 2026
Measurements held60
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/MPmanagers

Topic

Job listings — 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 97% 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.

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.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 6 other registered channels. This entry also sits inside a group of 4 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@MPmanagers/15404 · this entry4 Aug 2026, 13:35 UTC@Jobs_MP/45164 Aug 2026, 13:35 UTC1.00under a minute
@Jobs_MP/45205 Aug 2026, 17:19 UTC@MPmanagers/15417 · this entry7 Aug 2026, 09:03 UTC1.0040 hours
@Jobs_MP/45288 Aug 2026, 16:47 UTC@MPmanagers/15519 · this entry2 Sept 2026, 10:19 UTC1.0025 days
@MPmanagers/15459 · this entry15 Aug 2026, 16:07 UTC@Jobs_MP/454316 Aug 2026, 06:03 UTC1.0014 hours
@Jobs_MP/454516 Aug 2026, 15:15 UTC@MPmanagers/15466 · this entry17 Aug 2026, 09:59 UTC1.0019 hours
@MPmanagers/15496 · this entry24 Aug 2026, 09:32 UTC@Jobs_MP/456224 Aug 2026, 09:34 UTC1.002 minutes
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@Jobs_MP31 (8/8 hand-verifiable sample passed)1.002 minutesthis entry (17–14)
@MPdesigns23 (8/8 hand-verifiable sample passed)0.992 minutes@MPdesigns (14–9)
@sellersellerwb12 (8/8 hand-verifiable sample passed)0.9820 hoursthis entry (12–0)
@Designs_job9 (8/8 hand-verifiable sample passed)1.003.6 hoursthis entry (6–3)
@Designs_squad7 (7/7 hand-verifiable sample passed)1.003.0 hoursthis entry (6–1)
@sellerman6 (6/6 hand-verifiable sample passed)0.9610 hours@sellerman (5–1)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 33 of the 37 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 253 comparable posts for this entry, running 3 August 2026 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 4 channels, the one whose matching posts we hold earliest is @MPdesigns. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 11 November 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.

Channels linked by matching posts

This channel is in a group of 4 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

22,01322,59322,3037 August 2026 — 22,044 subscribers7 August 2026 — 22,043 subscribers8 August 2026 — 22,050 subscribers9 August 2026 — 22,037 subscribers10 August 2026 — 22,035 subscribers11 August 2026 — 22,034 subscribers12 August 2026 — 22,030 subscribers14 August 2026 — 22,023 subscribers15 August 2026 — 22,019 subscribers17 August 2026 — 22,013 subscribers18 August 2026 — 22,023 subscribers20 August 2026 — 22,220 subscribers21 August 2026 — 22,234 subscribers23 August 2026 — 22,235 subscribers24 August 2026 — 22,231 subscribers25 August 2026 — 22,222 subscribers26 August 2026 — 22,198 subscribers27 August 2026 — 22,194 subscribers28 August 2026 — 22,190 subscribers29 August 2026 — 22,186 subscribers30 August 2026 — 22,178 subscribers31 August 2026 — 22,174 subscribers1 September 2026 — 22,153 subscribers2 September 2026 — 22,137 subscribers3 September 2026 — 22,135 subscribers5 September 2026 — 22,127 subscribers9 September 2026 — 22,136 subscribers11 September 2026 — 22,300 subscribers13 September 2026 — 22,298 subscribers15 September 2026 — 22,280 subscribers17 September 2026 — 22,273 subscribers25 September 2026 — 22,290 subscribers4 October 2026 — 22,396 subscribers8 October 2026 — 22,455 subscribers13 October 2026 — 22,457 subscribers14 October 2026 — 22,440 subscribers15 October 2026 — 22,504 subscribers16 October 2026 — 22,521 subscribers17 October 2026 — 22,519 subscribers18 October 2026 — 22,521 subscribers19 October 2026 — 22,544 subscribers20 October 2026 — 22,539 subscribers21 October 2026 — 22,525 subscribers22 October 2026 — 22,578 subscribers23 October 2026 — 22,559 subscribers25 October 2026 — 22,546 subscribers26 October 2026 — 22,541 subscribers27 October 2026 — 22,536 subscribers28 October 2026 — 22,530 subscribers29 October 2026 — 22,524 subscribers30 October 2026 — 22,564 subscribers31 October 2026 — 22,590 subscribers2 November 2026 — 22,583 subscribers3 November 2026 — 22,591 subscribers4 November 2026 — 22,592 subscribers5 November 2026 — 22,593 subscribers6 November 2026 — 22,581 subscribers7 November 2026 — 22,573 subscribers8 November 2026 — 22,576 subscribers10 November 2026 — 22,571 subscribers22,5717 August 202610 November 2026
60 measurements spanning 95 days, net +527. 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 21,926–22,680 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)SubscribersChange
10 Nov 2026, 02:1922,571-5
8 Nov 2026, 14:5922,576+3
7 Nov 2026, 07:4722,573-8
6 Nov 2026, 07:2822,581-12
5 Nov 2026, 06:1122,593+1
4 Nov 2026, 06:5722,592+1
3 Nov 2026, 09:5622,591+8
2 Nov 2026, 12:4822,583-7
31 Oct 2026, 17:0622,590+26
30 Oct 2026, 14:3922,564+40
29 Oct 2026, 15:2022,524-6
28 Oct 2026, 14:4922,530-6
27 Oct 2026, 14:0522,536-5
26 Oct 2026, 16:1022,541-5
25 Oct 2026, 19:2722,546-13
23 Oct 2026, 21:1522,559-19
22 Oct 2026, 22:4522,578+53
21 Oct 2026, 22:4422,525-14
20 Oct 2026, 16:0622,539-5
19 Oct 2026, 17:3922,544first reading

Engagement

267 posts held, back to 3 August 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 106 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.48%
avg views ÷ 22,571 subscribers
Avg views / post
561
69 posts measured
Reaction rate
0.424%
reactions ÷ views · ER floor
Posts in window
74
of 267 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. It is computed over the 23 of 69 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 November 2026
Posts held267 (3 August 2026 – 10 November 2026)
Views total38,675
Reactions total58
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 05:59 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
≈3,900
Videos
≈4
Links
≈3,920

Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

158 reactions across 75 posts, in 5 distinct kinds. The most used accounts for 35.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤5635.4%
👎5635.4%
👍2918.4%
🔥138.23%
❤‍🔥42.53%

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 90 of the 267 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 158 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 267 most recent posts we hold, published 3 August 2026 to 10 November 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

Telegram’s own ‘edited’ marker: 2 of 74 posts held from the last 30 days (2.70%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

10 Nov 2026, 16:05 UTC235 viewsread 11 November 2026
Photo

Аудит и аналитика Ozon / Яндекс Маркет | Опыт с 2020 года Менеджер-аналитик Ozon и Яндекс Маркет | Аудит и консультации Работаю с маркетплейсами с 2020 года. По образованию инженер-математик, специализация — математическая статистика. Опыт работы в различных товарных нишах. Мой принцип — цифры вместо догадок. Решения принимаю на основе данных, расчётов и анализа, а не интуиции. Активно применяю ИИ для повышения эффек…

10 Nov 2026, 14:48 UTC258 viewsread 11 November 2026

#ищу_работу #менеджер_ВБ #помощникменеджера #менеджер #Wildberries #WB #удаленно Привет! Меня зовут Анна. Я сертифицированный менеджер маркетплейса “Wildberries”. Опыт работы более 1,5 года Моя основная компетенция: 🔸 Полное или частичное ведение личного кабинета 🔸 Создание, заполнение и SEO оптимизация карточки товара 🔸 Ежедневная работа с отзывами и вопросами покупателей 🔸 Формирование и контроль поставок, созд…

10 Nov 2026, 12:18 UTC347 viewsread 11 November 2026

Ищу работу ассистентом / помощником менеджера маркетплейсов Более 3 лет работаю с Wildberries и Ozon. Ищу удалённую работу с занятостью 3–6 часов в день. Могу взять на себя: - Аналитику продаж, конкурентов и цен. - Работу с карточками, SEO и контентом. - Excel / Google Таблицы, отчёты и расчёты. - Контроль остатков, поставок и цен. - Рекламу и акции. - Работу с отзывами и текущими задачами менеджера. - Поиск информа…

10 Nov 2026, 06:25 UTC410 views2 reactionsread 11 November 2026

Выспался. Создал чат-бота. Заработал +17.000 рублей. Пока ты едешь на «любимую работу» к 8ч утра, другие запускают этого бота, следуют пошаговой инструкции и получают +17.000 рублей за несколько часов работы. Эти люди не программисты и у них даже нет высшего образования. Они просто научились создавать чат-ботов, где нет ничего сложного. И за это им готовы платить 200-250.000 рублей в месяц. На старте новички зараб…

👍2

10 Nov 2026, 06:09 UTC429 viewsread 11 November 2026

Здравствуйте! Меня зовут Герман. Развиваюсь в e-commerce. Ищу позицию "помощник селлера \ менеджера маркетплейсов". Предлагаю простую вещь - я беру на себя рутину, которая обычно съедает время: • Создание и оптимизацию карточек. • Сбор отчётов. • Контроль остатков. • Мониторинг цен у конкурентов. • Участие в акциях. • Ответы на отзывы. • Работу с таблицами. Далее хочу осваивать продвижение, рекламу и работу с бюдж…

9 Nov 2026, 13:13 UTC510 viewsread 11 November 2026

Кристина Контактные данные: Телеграм: @Kristi_SKO 🕹Маркетплейс: WILDBERRIES Одежда, товарка, электроника, аксессуары 💰Успехи: Прошла обучение с практикой в реальном личном кабинете поставщика. ☝🏻Готова помочь вашему бизнесу расти и развиваться на маркетплейсе Wildberries. ▪️О менеджере ☑ Новичок ☑ Удаленная работа ☑ Регистрация и настройка лк. ☑ SEО-оптимизация ☑ Анализ карточек ☑ Оформление поставок ☑ Рассчет…

9 Nov 2026, 09:00 UTC524 views1 reactionsread 11 November 2026
Photo

Написали пошаговую инструкцию: как находить клиентов в 2026 году Для менеджеров маркетплейсов и дизайнеров инфографики ДАЖЕ БЕЗ ОПЫТА В гайде разобрали: где искать поставщиков, как предлагать им свои услуги и как закрывать их на оплату за 15-20 минут переписки Без изнурительных откликов на вакансии и неработающих методов. Отдаю инструкцию бесплатно 👇 → Для менеджеров маркетплейсов → Для дизайнеров карточек

❤1

9 Nov 2026, 06:31 UTC533 viewsread 11 November 2026

📊 Увеличила оборот магазина на OZON х3 за месяц! Меня зовут Юлия, менеджер озон с опытом работы более 2х лет. 📦 Работала с ассортиментом 3000 SKU (ozon) 📉 Снизила ДРР с 17% до 6% без потерь продаж 🔥 Увеличила оборот магазина с 1.5 млн руб до 7 млн руб за 2 месяца работы 📈За 1,5 месяца работы вышли на стабильный оборот х3 🔝Вывод карточки в топ с нуля при минимальном ДРР ❗️Вывод проблемного магазина из минуса ч…

8 Nov 2026, 15:53 UTC593 viewsread 11 November 2026

Веду 3 проекта из дома по 40к — на карте +120.000 в месяц, пока ты сидишь на окладе 60к Кто-то едет на «любимую работу» к 8 утра, а кто-то запускает этого бота, следуют пошаговой инструкции и получают +3.000 - 4.000 рублей за пару часов работы. Эти люди не программисты и у них даже нет высшего образования. Они всего лишь освоили профессию технического специалиста, где нет ничего сложного. И за это им готовы платить…

8 Nov 2026, 12:41 UTC610 viewsread 11 November 2026

Менеджер / РОП на WB Более 5 лет опыта на WB, более 3 лет РОП. Создание отдела с нуля. Комплексное развитие продаж: вывод товаров в ТОП, системне увеличение заказов и прибыли, регулярное отслеживание и улучшение метрик. Ключевые компетенции: • создание, развитие и управление командой; • анализ ниши, конкурентов и ЦА; • создание и SEO-оптимизация карточек; • подготовка фотоконтента; • настройка и ведение внутренней…

7 Nov 2026, 17:32 UTC686 views7 reactionsread 11 November 2026

📌 ИЩУ ОПЫТНОГО МЕНЕДЖЕРА OZON + WILDBERRIES Ищем сильного специалиста для комплексного ведения и развития двух действующих магазинов на маркетплейсах. 🚗 Наша ниша: автомобильные запчасти 📦 О бизнесе: • Действующие магазины с продажами и ассортиментом. • Налаженные поставки и товарные остатки. • Цель — увеличение чистой прибыли, а не просто оборота. 🎯 Задачи: • Управление внутренней рекламой Ozon и WB, оптимизация ДРР…

👎3❤2👍1🔥1

7 Nov 2026, 15:52 UTC656 viewsread 11 November 2026

Я — менеджер маркетплейсов и готова высвободить вам до 25 часов в неделю, чтобы вы занимались бизнесом, а не рутиной маркетплейсов. Возьму на себя работу с контентом, поставками, рекламой на Wildberries, Ozon и Яндекс.Маркете и другие задачи, которые забирают ваше время. Вы сможете сосредоточиться на производстве, продукте и стратегических задачах. Имею более года практического опыта работы с маркетплейсами и прошл…

Showing the 12 most recent of 267 posts we hold for @MPmanagers. 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.

Posts edited after publishing

@MPmanagers 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
27 August 2026
Most recent edit
5 October 2026

Posts recorded as deleted after publishing

We recorded 16 posts on @MPmanagers 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
24 August 2026
Most recent seen missing
10 November 2026
Median time before seen missing
4 days
Seen missing in the last 30 days
3

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 4 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.

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.

Селлеры и Менеджеры, Инфографика, Вакансии и резюме WB OZON YM
@sellerman · 58,149
#1
Вакансии на маркетплейсах
@Jobs_MP · 12,368
#2
Наталья Малиновская про Wildberries 🔥
@tinder_kc · 4,739
#3
Работа на маркетплейсах. Вакансии менеджера маркетплейса
@workmarketplaces · 10,765
#4
Вакансии для менеджеров маркетплейса | Удаленная работа Wildberries Ozon
@jobs_marketplace · 8,611
#5
WB Партнёры
@wbsellerofficial · 178,446
#6
Вакансии менеджера WB|OZON🔥
@vacancyWB · 9,369
#7
Инфографика | Продвижение | Маркетплейсы
@MPdesigns · 31,395
#8
Работа на маркетплейсах
@marketplacejob · 14,393
#9
Вакансии и Резюме менеджеры маркетплейсов
@menedgermarketpleisov · 16,028
#10
☀️Семья на Маркетплейсах
@sellermp · 46,418
#11
Иван Куриленко (Акулы Wildberries и Ozon)
@wbsharks · 72,000
#12
Max EVIRMA / Продвижение на Wildberries / LET`S ROCK on WB
@maxprowb · 100,572
#13
Вячеслав Малых
@seotrener1 · 27,291
#14
Аналитик на миллиард | Wildberries
@wbbillion · 23,325
#15
О маркетплейсах для начинающих. Склад13.
@mpreklama · 5,078
#16
SEOREMICA 💎 Павел Михайлов
@seoremica_ru · 23,065
#17
Основатель mkeeper
@mkeeper · 21,708
#18
Андрей: Про маркетплейс Wildberries, OZON и не только
@andrey_pro_business · 26,674
#19
Новак Павел wb и ozon
@novak_WB · 24,875
#20
Elena Gyreeva | AI Креатив
@elena_gyreeva_ai · 871
#21
Василий MarketPapa
@marketpapa_channel · 27,444
#22
Владлен Строкань | Основатель Wildbox
@vladlen_strokan · 58,746
#23
Внешняя реклама | Контент завод с Олесей
@prodvizgenie_wb · 7,423
#24
Дарья Лаиш PRO маркетплейсы
@dashaprowildberries · 3,808
#25
MPGO
@mpgo_ru · 80,386
#26
Менеджер WILDBERRIES | ДАРЬЯ
@raskaz_managerWB · 362 (as read 21 September 2026)
#27
Найм по любви-Recruit Place❤️
@recruit_place · 2,060
#28
💰MarketGuru | Секреты Wildberries
@marketguruclub · 39,201
#29
Тимур Товарка | WB и OZON
@nadiradze_t · 9,225
#30
Николай | Отец 5-х | Селлер WB, Ozon | Оцифровка MPfact
@smenik_mp · 6,564
#31
Мария MarketPlaceStep WB OZON маркетинг
@marketplacestep · 6,901
#32
Wbradar.ru сервис управления рекламы на wildberries
@wbradarbidder · 4,901
#33
Ирина Агафонова / Деньги на Китае
@irina_agafonova_ved · 14,234
#34
Рыжий М.
@redman · 100,845
#35
Хогвартс маркетплейсов
@marketplace_hogwarts · 57,774
#36
Found&Craft | эффективный найм для селлеров
@found_sm · 1,461
#37
За кейс | Фриланс вакансии
@For_case · 11,313
#38
ВАКАНСИИ ДЛЯ МЕНЕДЖЕРОВ ПО ПРОДАЖАМ
@freelance_joob · 14,228
#39
Мастерская копирайта | Вакансии
@Copywriters_Job · 10,884
#40
IT jobs | Вакансии в ИТ
@Jobs_for_IT · 6,754
#41
Wildbox.News
@wildbox_news · 85,864
#42
Designs squad | Дизайн вакансии
@Designs_squad · 11,180
#43
РАБОТА ИЗ ДОМА | ВАКАНСИИ
@rabota_is_doma_vakansii · 20,593
#44
Уголок дизайнера | Вакансии
@Designs_job · 35,399
#45
СЁРЧЕР | ВАКАНСИИ | УДАЛЕНКА
@searcher_freelance · 6,989
#46
Сергей WBway
@wbway2 · 10,933
#47
ВАКАНСИИ ДЛЯ ДИЗАЙНЕРОВ МОСКВА
@vakansii_dizaynerov · 18,705
#48
VibeVO | Видеоклиппинг и реклама в коротких видео
@vibevo_io_ru · 10,915
#49
Татьяна Ким
@kimtatyana2024 · 86,893
#50
СОВА на ФРИЛАНСЕ
@sova_freelance · 36,443
#51
⚡️Поставлено! Логистика на WB и OZON
@postavleno · 26,508
#52
Диана: ИИ для бизнеса на МП
@Diana_Pro_Wildberries · 7,656
#53
Your Career | Твоя карьера
@yourcareerchannel · 4,381
#54
АВИТО ПРОДВИГАТОР
@prodviggator · 7,700
#55
ВАКАНСИИ SMM РИЛСМЕЙКЕРЫ МОСКВА
@smm_vakansiii · 18,483
#56
REMOTER @ вакансии на удаленке
@TRemoters · 29,017
#57
Съёмки и модели | Москва | Питер
@MPphotographer · 5,442
#58
Работа в комфорте🧘‍♀
@frilancekomfort · 41,323
#59
Кейсы по внешней рекламе на WB
@vneshkastats · 2,534
#60
SMM / Contentmakers hunter freelancers
@smmfreelancer · 21,350
#61
Баландин Никита
@vsegdaprosto · 12,983
#62
Бабки на Юбках💲
@robo_wb · 10,180
#63
🏄🏼 Таверна СММ | РАБОТА | ВАКАНСИИ
@vakansii_smm · 11,013
#64
Финансы WB – Виноградов Алексей
@wbfinance · 7,842
#65
Вб на прокачку | Максим Емельянов
@silavomne · 11,360
#66
Анжела | про бренд и маркетинг
@anzhelawb · 4,352
#67
Бизнес в корзине
@business_in_cart · 3,873
#68
Таргет | Арбитраж | Вакансии
@Traffic_jobs · 10,370
#69
Удалёнка для всех
@worksvsem · 30,325
#70
Копирайтер на фрилансе? Заходи!
@freelanceeboom · 18,500
#71
GetClient | Фриланс вакансии
@GetClient · 45,653
#72
Python jobs | Вакансии в IT
@Python_Jbs · 7,537
#73
Vasilisa.ai — Ваша команда ИИ
@aiVasilisa · 1,202
#74
Дизайнер? Есть работа!
@workfordesigner · 25,838
#75

Read from Telegram’s recommendation API, most recently 21 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.

Селлеры и Менеджеры, Инфографика, Вакансии и резюме WB OZON YM
@sellerman · 58,149
Telegram ranks this channel #10 of 77 here — alongside 76 others — read 22 August 2026
Инфографика | Продвижение | Маркетплейсы
@MPdesigns · 31,395
Telegram ranks this channel #19 of 81 here — alongside 80 others — read 7 September 2026
Вакансии Workzilla — Удаленная работа | Фриланс
@workzilla_vacancies · 27,873
Telegram ranks this channel #54 of 81 here — alongside 80 others — read 11 September 2026
РАБОТА ИЗ ДОМА | ВАКАНСИИ
@rabota_is_doma_vakansii · 20,593
Telegram ranks this channel #85 of 85 here — alongside 84 others — read 4 October 2026

This channel appears in 4 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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Менеджеры маркетплейсов | Вакансии” (@MPmanagers), 22,571 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/MPmanagers.

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.