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Channel

آكادمی فروش دیدار

@salesdemy

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

3,069subscribers

-33 since we began measuring on 5 August 2026

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

Register entry

Telegram ID-1001003619987
TypeChannel
Username@salesdemy
Created30 September 2015 — measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live12 October 2026
Measurements held15
Confirmed unchanged1 time, most recently 12 October 2026
On Telegramt.me/salesdemy

Topic

Education — 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 11 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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 why it has no browse page of its own yet.

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 word for word on 1 other registered channel. 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 (2 of the pairs behind the counts below)
Posted firstThenOverlapGap
@salesdemy/4810 · this entry5 Nov 2025, 17:30 UTC@didarsalesacademyy/2135 Nov 2025, 18:06 UTC1.0036 minutes
@salesdemy/4811 · this entry14 Nov 2025, 18:27 UTC@didarsalesacademyy/21515 Nov 2025, 06:40 UTC1.0012 hours
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@didarsalesacademyy10 (8/8 hand-verifiable sample passed)1.0055 minutesthis entry (9–1)

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. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 19 comparable posts for this entry, running 14 July 2025 to 1 August 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).

Across the whole group of 2, the earliest publisher we hold is @salesdemy — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 7 August 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.

Also posting the same content

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.

Growth

3,0693,1023,085.55 August 2026 — 3,102 subscribers6 August 2026 — 3,102 subscribers12 August 2026 — 3,101 subscribers15 August 2026 — 3,100 subscribers19 August 2026 — 3,094 subscribers22 August 2026 — 3,084 subscribers26 August 2026 — 3,083 subscribers29 August 2026 — 3,081 subscribers4 September 2026 — 3,082 subscribers9 September 2026 — 3,081 subscribers13 September 2026 — 3,080 subscribers18 September 2026 — 3,078 subscribers27 September 2026 — 3,076 subscribers5 October 2026 — 3,073 subscribers12 October 2026 — 3,069 subscribers5 August 202612 October 2026
15 measurements spanning 68 days, net -33. 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 3,064–3,107 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Oct 2026, 10:593,069-4
5 Oct 2026, 17:583,073-3
27 Sept 2026, 23:193,076-2
18 Sept 2026, 04:553,078-2
13 Sept 2026, 19:003,080-1
9 Sept 2026, 15:363,081-1
4 Sept 2026, 02:203,082+1
29 Aug 2026, 07:173,081-2
26 Aug 2026, 05:253,083-1
22 Aug 2026, 20:273,084-10
19 Aug 2026, 04:123,094-6
15 Aug 2026, 18:543,100-1
12 Aug 2026, 05:383,101-1
6 Aug 2026, 04:513,102no change
5 Aug 2026, 22:293,102first reading

Engagement

20 posts held, back to 14 July 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pages 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 20 posts for this entry, the most recent from 1 August 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

84 reactions across 18 posts, in 8 distinct kinds. The most used accounts for 79.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤6779.8%
👍55.95%
🔥44.76%
🙏33.57%
🤩22.38%
👌11.19%
👎11.19%
👏11.19%

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 18 of the 20 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 84 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 14 July 2025 to 1 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

1 Aug 2026, 07:37 UTC188 viewsread 7 August 2026
Forwarded from @didarsalesacademyyPhoto

🚨 چرا تیم فروش به هدفش نمی‌رسه؟ هر ماه برای تیم فروش هدف تعیین می‌کنید، اما آخر ماه نتیجه با انتظارتان فاصله دارد؟ خیلی وقت‌ها مشکل از تیم فروش نیست؛ بلکه از KPI و OKR‌هایی است که درست تعریف نشده‌اند. در این وبینار یاد می‌گیرید: 🔹 تفاوت KPI و OKR و کاربرد هرکدام 🔹 چطور هدف‌های قابل اندازه‌گیری برای تیم فروش تعریف کنید. 🔹 روی چه شاخص‌هایی تمرکز کنید که واقعاً فروش را رشد می‌دهند. 🔹 اشتباهات رایج هدف‌گذاری را بشناسی…

20 Feb 2026, 05:44 UTC934 views5 reactionsread 7 August 2026
Photo

💥رفتار مشتری در عصر تصمیم‌گیری لحظه‌ای💥 مشتری امروز منتظر نمی‌ماند؛ یا در لحظه تصمیم می‌گیرد، یا شما را رد می‌کند! 👤 مدرس: دکتر محسن محمودی مدیرعامل پلتفرم آیدا (دستیار هوشمند مدیریت کسب‌و‌کار) مشاور فنی ارشد دیدار مدرس دانشگاه تهران 📅 زمان برگزاری: سه‌شنبه ۵ اسفند 📍 برگزارکننده: آکادمی دیدار + آیدا در این وبینار یاد می‌گیرید چگونه فروش را به یک سیستم هوشمند، پایدار و نتیجه‌ساز تبدیل کنید. 🚀 🔗 لینک ثبت‌نام رای…

🙏3❤2

30 Dec 2025, 09:03 UTC≈1,100 views9 reactionsread 7 August 2026
Photo

همراهان گرامی آکادمی فروش دیدار، ما در آکادمی معتقدیم بهترین سفیران رشد فروش، دانشجویانی هستند که مسیر یادگیری را با ما تجربه کرده‌اند. 💙 با معرفی دوره‌های حضوری به دوستان و همکاران، در توسعه آموزش حرفه‌ای فروش نقش داشته باشید و به ازای هر ثبت نام، ۳ میلیون تومان پاداش نقدی دریافت کنید. همچنین این امکان وجود دارد که بخشی از پاداش خود را به عنوان کمک هزینه ثبت‌نام دوره با شخصی که معرفی می‌کنید اهدا کنید. 🎁 در این مس…

❤7👍2

19 Dec 2025, 09:44 UTC≈1,090 views4 reactionsread 7 August 2026
Photo

یلدا، شبِ نبردِ روشنایی و تاریکیه … امسال، افسانه‌های شاهنامه دوباره زنده شدن و حالا نوبت توئه که وارد میدان بشی. 👇🏼 وارد مسابقه هفت‌خوان شو، کاراکترت رو انتخاب کن و جوایز جذاب آکادمی دیدار رو ببر! 🤩 https://linki.ir/HoAbwpD

🤩2👎1👏1

15 Dec 2025, 05:37 UTC≈1,170 views4 reactionsread 7 August 2026
Photo

📊 در این جلسه یاد می‌گیریم چگونه پورسانت‌دهی را از یک عدد ساده، به یک سیستم هوشمند انگیزه‌ساز تبدیل کنیم؛ سیستمی که هم فروشنده را به حرکت وادارد و هم سازمان را به رشد پایدار برساند. ✅ لینک ثبت نام رایگان در وبینار: 👇🏼 https://eseminar.tv/wb169664

❤4

3 Dec 2025, 17:51 UTC≈1,490 views4 reactionsread 7 August 2026
Photo

اگر می‌خواهید CRM از یک مخزن داده، به یک موتور رشد فروش، وفاداری و ارزش برند تبدیل شود، این وبینار برای شماست! 🚀 ✅ لینک ثبت‌نام رایگان: https://eseminar.tv/wb168775

❤3👍1

14 Nov 2025, 18:27 UTC≈1,070 views5 reactionsread 7 August 2026
Photo

🎯 در این وبینار یاد می‌گیرید چگونه: ✅ ساختار فروش خود را فرآیندمحور کنید ✅ مشتری و بازار هدف را علمی بشناسید ✅ برای هر نوع مشتری ارزش خلق کنید ✅ از اولین تماس تا امضای قرارداد، مسیر مشخص و قابل تکرار داشته باشید ✅ و در نهایت، فروش را از یک عملکرد فردی به سیستمی سازمانی تبدیل کنید. ✔️ همین حالا رایگان ثبت‌نام کنید: 👇🏼 https://eseminar.tv/wb167803

❤5

5 Nov 2025, 17:30 UTC≈1,040 views5 reactionsread 7 August 2026
Photo

✅️ در این وبینار یاد می‌گیریم چطور از نقش «مدیر فروش» به نقش «کوچ رشد دهنده تیم فروش» عبور کنیم. چطور به جای پیگیری مداوم اعداد، افراد رو طوری توانمند کنیم که خودشون مسیر موفقیت رو بسازن. 📥 لینک ثبت‌نام رایگان: https://eseminar.tv/wb166872

❤5

20 Oct 2025, 17:29 UTC982 views5 reactionsread 7 August 2026
Photo

کارگاه آنلاین «مدیریت عملکرد فروش» مدرس: حسین راد مشاور و مدرس بین المللی توسعه بازار و سیستم سازی فروش ✅️ لینک ثبت‌نام: https://linki.ir/XAFwf74 آکادمی دیدار

❤3🔥2

18 Oct 2025, 06:29 UTC≈2,100 views5 reactionsread 7 August 2026
Photo

💥وبینار مهندسی فروش💥 بازاریابیِ مؤثر یعنی تصمیم‌گیری هوشمندانه؛ از شناخت دقیق بازار تا ارزیابی عملکرد تیم فروش. در این وبینار یاد می‌گیرید چطور فروش و بازاریابی را به زبان داده، استراتژی و تحلیل ترجمه کنید. 🎯 ✅️ لینک ثبت‌نام رایگان: https://eseminar.tv/wb165802

❤5

15 Oct 2025, 08:34 UTC783 views4 reactionsread 7 August 2026
Photo

کارگاه حضوری «اصول و فنون مذاکره» مدرس: دکتر سروش حریرفروش مدیرعامل سابق آسیاتک، مدرس دوره DBA دانشگاه تهران، معاون توسعه شاتل، قائم‌مقام شرکت آوا، مدیربازرگانی هلدینگ تفتا و فن‌آوا 📍 ظرفیت محدود | شهرک غرب ✅️ لینک ثبت‌نام: https://linki.ir/xwXXcEO آکادمی دیدار

❤2🔥2

Showing the 12 most recent of 20 posts we hold for @salesdemy. 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

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.

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 12 October 2026 — this entry's latest reading, not the date you are reading this.

“آكادمی فروش دیدار” (@salesdemy), 3,069 subscribers as measured 12 October 2026. Telegram Register, tgregister.com/channel/salesdemy.

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.