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Channel

Omnidata Retail Hub

@omnidata_retail_hub

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

157subscribers

+4 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001738862827
TypeChannel
Username@omnidata_retail_hub
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live17 September 2026
Measurements held4
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/omnidata_retail_hub

Growth

1531571557 August 2026 — 153 subscribers8 August 2026 — 153 subscribers9 September 2026 — 155 subscribers17 September 2026 — 157 subscribers7 August 202617 September 2026
4 measurements spanning 41 days, net +4. 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 152–158 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Sept 2026, 00:58157+2
9 Sept 2026, 05:36155+2
8 Aug 2026, 19:16153no change
7 Aug 2026, 12:50153first reading

Engagement

9 posts held, back to 26 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 9 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Video runtime
9m 42s
Average length
9m 42s

Measured directly from 1 video 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

56 reactions across 9 posts, in 6 distinct kinds. The most used accounts for 50.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥2850.0%
👍2137.5%
47.14%
11.79%
👏11.79%
💯11.79%

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 9 of the 9 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 56 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 9 most recent posts we hold, published 26 May 2026 to 6 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

6 Aug 2026, 12:42 UTC46 views4 reactionsread 8 August 2026
Video

Управление жизненным циклом бьюти-продукта в PLM: от концепта до аналитики Разработка косметики требует тщательного контроля: от соответствия рецептур и валютных расчетов с поставщиками до прохождения сертификации. Показываем на практике, как Omnidata.PLM структурирует разработку бьюти-ассортимента на всех этапах: 📍 00:00 — Стратегическое планирование и запуск пайплайна идей 📍 01:56 — Проработка продукта: рецептур

🔥3👍1

4 Aug 2026, 09:37 UTC81 views2 reactionsread 8 August 2026
Photo

Полезный подкаст от PROfashion 🎬 В их проекте «PROFIT.ROLE» вышел выпуск с Николаем Константиновым (CEO универмагов «Телеграф» и Trend Island) – о том, как превращать продукт в деньги и почему бренды закрываются в 2026 году. 📍 Почему маркетплейсы не ликвидировали офлайн ритейл, а просто отсекли слабых игроков? 📍 Как человеческий фактор до сих пор сливает ваши бюджеты? 📍 Где искать точки роста и новые ниши Мы с удо

👍2

30 Jul 2026, 11:16 UTC83 views6 reactionsread 8 August 2026
Photo

Полезные кейсы, сильные спикеры и атмосфера для открытого общения – именно таким мы задумывали Omnidata Фэшн Клуб! Делимся отзывом Екатерины Сальниковой, руководителя отдела женской верхней одежды Zolla🧡 Вдохновляемся вашими словами и уже активно собираем программу для следующего OFC. Дату и тему раскроем совсем скоро💬

👍6

28 Jul 2026, 08:55 UTC79 views3 reactionsread 8 August 2026
Photo

Разобрали 3 симптома того, что ручной контроль ассортиментного и календарного планирования в Excel начинает перегружать команду. При масштабировании fashion-бренда таких скрытых проблем становится еще больше. В новой статье – чек-лист триггеров и опыт Bungly и Lassie: как перестроить управление ассортиментом на этапе активного роста. 👉 Читать статью

🔥2👍1

23 Jul 2026, 06:37 UTC119 views12 reactionsread 8 August 2026
Photo

У нас крутые новости: обновили модуль BOM в Omnidata.PLM — смотрите в карточках, как теперь легко управлять себестоимостью и планировать закупки! 🔥

🔥10👍1👏1

22 Jul 2026, 06:21 UTC137 views8 reactionsread 8 August 2026

Как выстроить международный fashion-бизнес с 19-летней историей: заглянули за кулисы Choupette 🎬 Детский fashion — один из сложных и требовательных сегментов в ритейле. Но бренд Choupette уже 19 лет доказывает: это системный, высокотехнологичный и отлично масштабируемый бизнес. В новом выпуске мы встретились с совладелицами бренда: записали интервью с Анастасией Васильковой (директор по развитию, ведет Telegram | I

👍4🔥31

26 Jun 2026, 08:18 UTC112 views7 reactionsread 8 August 2026
Forwarded from @retailfashionPhoto

Правила расчета реальной себестоимости и скрытые точки потери маржи в фэшн-индустрии Поговорили с Екатериной Башниной, главным аналитиком Omnidata.PML (ex-руководитель продукта PML в Спортмастере) о том, где можно потерять маржу еще до контракта с фабрикой, и как действовать в разных ситуациях. #словоэксперта ▶️Как рассчитывать реальную себестоимость до подписания контракта с фабрикой и не терять маржу? Cебестоимо

🔥51💯1

22 Jun 2026, 13:22 UTC131 views8 reactionsread 8 August 2026
Photo

Делимся отзывом от Ирины Герасимовой, старшего конструктора O'STIN, о последних встречах Omnidata Фэшн Клуб! Невероятно ценно создавать атмосферу закрытого клуба, где каждый чувствует себя частью чего-то большего. Рады, что вы с нами, и ждем на новых мероприятиях! 🧡

👍53

26 May 2026, 09:51 UTC188 views6 reactionsread 8 August 2026
Photo

21 мая прошла весенняя встреча нашего клуба Omnidata Фэшн Клуб🔥 Обсуждали, как формировать узнаваемость бренда через ассортимент, усиливать ценность продукта и находить свое место на перегретом рынке. Сильный состав спикеров сделал разговор по-настоящему практическим: в этот раз было много профессиональных дискуссий и реальных кейсов от ведущих компаний. 🙂 Спикеры встречи: - Игорь Карпов: «Изменение стратегии прод

🔥5👍1

Showing the 9 most recent of 9 posts we hold for @omnidata_retail_hub. 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.

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

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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“Omnidata Retail Hub” (@omnidata_retail_hub), 157 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/omnidata_retail_hub.

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.