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Channel

深圳95-96水疗会所

@KB66699

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

1,865subscribers

-289 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003389708258
TypeChannel
Username@KB66699
CreatedBetween 1 November 2025 and 31 March 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live2 September 2026
Measurements held11
Confirmed unchanged1 time, most recently 2 September 2026
On Telegramt.me/KB66699

Growth

1,8652,1542,009.57 August 2026 — 2,154 subscribers7 August 2026 — 2,154 subscribers8 August 2026 — 2,153 subscribers11 August 2026 — 2,135 subscribers15 August 2026 — 2,080 subscribers17 August 2026 — 2,056 subscribers20 August 2026 — 1,976 subscribers24 August 2026 — 1,966 subscribers27 August 2026 — 1,928 subscribers30 August 2026 — 1,925 subscribers2 September 2026 — 1,865 subscribers7 August 20262 September 2026
11 measurements spanning 25 days, net -289. 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 1,822–2,197 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
2 Sept 2026, 04:551,865-60
30 Aug 2026, 06:441,925-3
27 Aug 2026, 11:141,928-38
24 Aug 2026, 09:431,966-10
20 Aug 2026, 20:441,976-80
17 Aug 2026, 19:242,056-24
15 Aug 2026, 01:352,080-55
11 Aug 2026, 19:292,135-18
8 Aug 2026, 09:532,153-1
7 Aug 2026, 20:312,154no change
7 Aug 2026, 18:362,154first reading

Engagement

13 posts held, back to 23 June 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.

ERR · 30 days
8.20%
avg views ÷ 1,865 subscribers
Avg views / post
153
1 post measured
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 13 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 6 August 2026
Posts held13 (23 June 20266 August 2026)
Views total153
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 20:31 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
1m 18s
Average length
10s

Measured directly from 8 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

6 reactions across 5 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
6100.0%

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 5 of the 13 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 6 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 23 June 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, 05:36 UTC153 viewsread 7 August 2026
Video

深圳全区⭐️⭐️⭐️⭐️⭐️服 务 全网最高端 安全可靠 兼职多多 提前预约不等位 只做高质量体验,主打放得开、高颜值,人员稳定、服务成熟,全程靠谱可控,环境私密,流程规范,安全始终放在第一位。没有套路、没有暗坑,无任何隐形消费,每一步都明明白白,体验实实在在,提前预约不排不等 预约客服:@zyl55

1 Aug 2026, 06:36 UTC416 viewsread 7 August 2026
Video

深圳全区94/95/96高端会所24小时营业,这里能制造快乐,妹子服务是专业的妹子都是穿黑丝的,各种类型都有的,宗旨是让客户满意的,做的就是回头客,有要求你尽管说,联系客服预约体验极致服务。 预约客服:@zyl55

28 Jul 2026, 05:15 UTC646 viewsread 7 August 2026
Video

深圳全区94/95/96⭐️⭐️⭐️⭐️⭐️服 务 安全可靠,提前预约不等位 只做高质量体验,主打放得开、高颜值,人员稳定、服务成熟,全程靠谱可控,环境私密,流程规范,安全始终放在第一位。没有套路、没有暗坑,无任何隐形消费,每一步都明明白白,体验实实在在,提前预约,安心安排

26 Jul 2026, 07:07 UTC702 viewsread 7 August 2026
Video

深圳全区94/95//96营业🀄️,风雨无阻每天都营业,现场佳丽20➕随便挑不满意可以换,欢迎各位咨询预约。 预约客服:@zyl55

24 Jul 2026, 03:31 UTC781 viewsread 7 August 2026
Video

深圳全区94/95/96营业🀄️!欢迎各位预约,春宵一刻值千金,初恋感满满,元气感满满,在岗佳丽20➕免费过夜。 金牌預約客服:@zyl55 双向私聊受限:@mao9594bot

17 Jul 2026, 23:08 UTC≈1,040 views2 reactionsread 7 August 2026
Photo

深圳全区南山、罗湖、宝安、龙岗,福田,光明,盐田94/95/56高端店面全天营业,嫩妹,少妇,御姐,任你挑选。妹妹颜值在线全程透明无坑,零定金零强制,验证通过放心预约,关注频道永不迷路。

2

15 Jul 2026, 08:51 UTC≈1,030 views1 reactionsread 7 August 2026
Video

深圳全区94/95/96/24小时营业欢迎各位预约,嫩妹,少妇,御姐,火辣夜场骚欲风、任你挑选。验证通过放心预约,关注频道永不迷路。

1

12 Jul 2026, 17:01 UTC≈1,090 views1 reactionsread 7 August 2026
Photo

长期伏案加班,肩颈硬得像块石板,睡眠也跟着亮起红灯。周末只想找个能彻底放空的地方,淡淡的芬香和迷人的暖色灯💡光,没有令人心烦的喧嚣声,房间比想象中更干净——纯白床品一客一换,整个人不自觉就松了下来。 #宝藏门店分享#放松解压#深圳SPA天花板#周末放松好去处

1

10 Jul 2026, 11:01 UTC≈1,160 viewsread 7 August 2026
Photo

深圳全区南山、罗湖、宝安、龙岗,福田,光明,盐田94/95/56高端店面全天营业,嫩妹,少妇,御姐,火辣夜场骚欲风、任你挑选。妹妹颜值在线全程透明无坑,零定金零强制,验证通过放心预约,关注频道永不迷路。

3 Jul 2026, 08:32 UTC≈1,520 viewsread 7 August 2026
Photo

深圳全区94/95/96营业🀄️!欢迎各位预约,春宵一刻值千金,初恋感满满,元气感满满,在岗佳丽20➕免费过夜。 金牌預約客服:@zyl55 双向私聊受限:@mao9594bot

28 Jun 2026, 11:41 UTC≈1,600 views1 reactionsread 7 August 2026
Video

想放松?想刺激?想极致享受?深圳会所 95 全部满足。现在私信或评论预约,优先安排优质资源。慢慢看,慢慢挑,慢慢的享受。

1

Showing the 12 most recent of 13 posts we hold for @KB66699. 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.

Mentions

Named by 7 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.

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

“深圳95-96水疗会所” (@KB66699), 1,865 subscribers as measured 2 September 2026. Telegram Register, tgregister.com/channel/KB66699.

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.