This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word 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.
5 measurements spanning 11 days, net -11. 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 2,612–2,627 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Aug 2026, 17:34
2,614
-7
13 Aug 2026, 06:57
2,621
-3
6 Aug 2026, 19:10
2,624
-1
6 Aug 2026, 05:20
2,625
no change
5 Aug 2026, 21:02
2,625
first reading
Engagement
7 posts held, back to 29 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 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
3.40%
avg views ÷ 2,614 subscribers
Avg views / post
88.9
7 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
7
of 7 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
Window
Rolling 30 days · latest post in window 5 August 2026
Posts held
7 (29 July 2026 – 5 August 2026)
Views total
622
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 16:20 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
2m 18s
Average length
1m 09s
Measured directly from 2 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.
تجربه من بهم میگه همیشه مشکل کمبود پول نیست؛ گاهی فقط به یه همراه با تجربه نیاز داری تا گرهها وا بشن و رشد اتفاق بیفته.🍃✨
تو صنعت زیبایی، خیلی از سالنها منابع مالی کافی دارن، اما هنوز تو جذب مشتری و مدیریت تیم گیر کردن. راز موفقیت، یه بیزینس کوچ صنعت زیبایی هست که مسیر رو بهت نشون بده.💡💇♀️
اگر مالک یا مدیر یه سالن زیبایی هستی و حس میکنی با وجود هزینههایی که کردی، هنوز به درآمد واقعی نرسیدی، بیا یه مسیر جدید رو …
آموزش آرایشگری زنانه حرفهای
✅ دورههای حضوری – اقساط ۱۲ ماهه، بدون پیشپرداخت
✅ دورههای مجازی – اقساط با اسنپ پی
از مقدماتی تا پیشرفته با مدرک معتبر.
ظرفیت محدود! برای ثبتنام و مشاوره تماس بگیرید:
📞 09120289041
Tehranenaz.com
🎨 فرمولهای حرفهای رنگ مو
(بر اساس جدیدترین متدهای روز دنیا)
🔸 بلوند نسکافهای روشن با تناژ دودی
🔸 نسکافهای دودی با هایالیت صدفی یا طلایی
🔸 ترکیبهای اختصاصی با پایه ۸ دکلره و اکسیدانهای ۶٪ و ۹٪
✅ همه فرمولها شامل:
· پایه، رنگ کلی، هایالیت، تناژ دودی، اکسیدان، نسبت ترکیب و زمان مکث
—————————————————————
💡 آموزش اقساطی ۱۲ ماهه
✔ بدون پیشپرداخت
✔ همراه با پشتیبانی و جزوههای تخصصی
✔ مناسب برای آرایشگران و علاق…
قرار نیست بیشتر کار کنی؛ قراره هوشمندانهتر کار کنی.
اگر سالن زیبایی داری، من بهت کمک میکنم تا مشتریهای بیشتری جذب کنی، فروشت رو افزایش بدی، تیم قویتری بسازی و کسبوکارت رو از یک سالن معمولی به یک برند شناختهشده تبدیل کنی
@zahraaghelnezhadd
#کوچ_سالن_زیبایی #کوچینگ_بانوان #کوچ_بانوان #سالنزیبایی_تهران #سالن_زیبایی
همیشه برام سوال بود چطوری پیازو سرخ میکنن که طعمش شیرین و لذید میشه.
امروز یادگرفتم و بسیار خر ذوقم.
پیازو عمود بر جهت خطوطش برش میزنی، میذاری ۴-۳ دقیقه با شعله نسبتن زیاد و بدون روغن تفت بخوره. وسطش نمکم اضافه میکنی تا قشنگ عصارهی پیازو بکشه بیرون.
بعد روغن و تفت و تمام 🤌
@makeup_nokte
آموزش آرایشگری زنانه حرفهای
✅ دورههای حضوری – اقساط ۱۲ ماهه، بدون پیشپرداخت
✅ دورههای مجازی – اقساط با اسنپ پی
از مقدماتی تا پیشرفته با مدرک معتبر.
ظرفیت محدود! برای ثبتنام و مشاوره تماس بگیرید:
📞 09120289041
Tehranenaz.com
✨ جهان مال کسیه که بدون نتیجه دیدن، ادامه بده.
🚀 بیوقفه باش. نتیجه خودش میآید.
━━━━━━━━━━━━━━━━━━
👩🏫 مربی: ZahraAghelnezhad Coach
📞 تماس / مشاوره:
☎️ 09120289041
http://Aghelnezhad.com
@zahraaghelnezhadd
#کوچینگ_برای_زنان #کوچینگ_سالن_زیبایی #کوچینگ_صنعت_زیبایی
Showing the 7 most recent of 7 posts we hold for @makeup_nokte. 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 16 August 2026 — this
entry's latest reading, not the date you are reading this.
“نکات آرایشی” (@makeup_nokte), 2,614 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/makeup_nokte.
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.
