Channel
@hrpeach
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
146subscribers
+2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002946298814 |
|---|---|
| Type | Channel |
| Username | @hrpeach |
| Created | Between 1 August 2025 and 31 October 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 15 September 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 2 times, most recently 15 September 2026 |
| On Telegram | t.me/hrpeach |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Sept 2026, 00:00 | 146 | +1 |
| 30 Aug 2026, 12:47 | 145 | +1 |
| 23 Aug 2026, 16:48 | 144 | +1 |
| 16 Aug 2026, 18:44 | 143 | -1 |
| 8 Aug 2026, 21:30 | 144 | no change |
| 7 Aug 2026, 21:22 | 144 | first reading |
6 posts held, back to 3 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 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 6 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
67 reactions across 6 posts, in 9 distinct kinds. The most used accounts for 37.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 25 | 37.3% | |
| ❤ | 10 | 14.9% | |
| 😁 | 10 | 14.9% | |
| 😍 | 8 | 11.9% | |
| ❤🔥 | 5 | 7.46% | |
| 👍 | 3 | 4.48% | |
| 🥰 | 3 | 4.48% | |
| 🌚 | 2 | 2.99% | |
| 🤝 | 1 | 1.49% |
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 6 of the 6 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 67 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 3 July 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.
Используете ИИ? Понятно Не используете ИИ? Понятно На каждом шагу мы слышим про нейросети: кандидатов бесит, что их отсеивает искусственный интеллект, а эксперты твердят, что без него сейчас не обойтись. На чьей стороне правда и как применяют нейросети специалисты по управлению персоналом — читайте в карточках. Спасибо за комментарии Анастасии Юрловой, Яне Плясовских, Анжелике Чередниченко и Полине Подкорытовой. …
🔥6❤5
Летний дайджест: качаемся на волнах качаем бренд работодателя 🌊 Собрали посты, которые вызвали наибольший ажиотаж в наших соцсетях. Смотрим: ✔️ Как развивать бренд работодателя в 2026 году ✔️ Что добавляют на карьерные страницы лучшие компании ✔️ Как стать классным работодателем для поколения Х ✔️ Что мы поменяли в визуале для соцсетей HR IMPACT ✔️ Почему фото улыбающихся людей в касках не привлекают заводчан …
🔥7❤🔥5🥰3
Почему мы это смотрим? Разбираем феномен Лутчака и других офисных блогеров 💼 Заметили, насколько популярны стали блоги о работе в офисе? Ролики «бухгалтера» Евгении Аверьяновой набирают больше 100 000 лайков, а самый известный офисный зумер Максим Лутчак победил в рейтинге Forbes «30 до 30». Объясняем, в чем секрет их популярности: 📌 Людям нравится видеть не красивую недосягаемую жизнь, а такую же рутину, как у н…
🔥6❤3👍3
А что, если бы рекрутеры и кандидаты общались как… на сайтах знакомств? Визуализировали страшный сон рекрутера и собрали забавные ситуации, с которыми многие из нас сталкиваются каждый день 🫣 Какой тип соискателя ваш самый «любимый»? Делитесь в комментариях⬇️
😁10🌚2
Пу-пу-пу… Сотрудник оставил негативный отзыв 📨 Без паники! Такая ситуация знакома большинству компаний. Вместе с нашими экспертами по рекрутингу и бренду работодателя собрали несколько простых советов, которые помогут снизить эмоциональный накал и показать компанию с лучшей стороны. И по традиции ждем вас в комментариях! А если заинтересовала эта тема, посмотрите пост о том, как управлять репутацией с помощью конте…
😍8❤2🔥1
Топ-3 ошибки в брендинге работодателя 🍑 На самом деле их гораздо больше, но остановимся на тех, с которыми сталкиваемся чуть ли не каждый день. 1️⃣ Разрабатывать ценностное предложение, фирменный стиль или карьерную страницу без исследования Кажется, все это понимают: сначала исследование, потом решение. Но на практике часто получается по-другому: «Мы и так хорошо знаем своих сотрудников» или «И без аудита понятны…
🔥5🤝1
Showing the 6 most recent of 6 posts we hold for @hrpeach. 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
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.
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 8 September 2026 — this entry's latest reading, not the date you are reading this.
“Peach | Брендинг работодателя” (@hrpeach), 146 subscribers as measured 8 September 2026. Telegram Register, tgregister.com/channel/hrpeach.
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.