Telegram RegisterThe public register of Telegram

Channel

Koloskov: growth, product, analytics

@sergeyproduct

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

4,604subscribers

-3 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001192730444
TypeChannel
Username@sergeyproduct
DescriptionКейсы роста и эфиры от Product advisor с 70 кейсами роста и спикера, консультирую по продуктам, процессам, командам.Contact - @SKoloskov Сайт - https://koloskoveducation.tilda.ws/. Про предпринимательство @freshfoundergo
Created30 March 2021measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded7 August 2026
Last confirmed live10 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/sergeyproduct

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 100% 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 4 other registered channels. 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 (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@sergeyproduct/698 · this entry30 May 2026, 10:50 UTC@eduproduct/58131 May 2026, 10:53 UTC1.0024 hours
@eduproduct/5837 Jun 2026, 07:24 UTC@sergeyproduct/700 · this entry7 Jun 2026, 08:25 UTC1.0062 minutes
@eduproduct/5848 Jun 2026, 08:47 UTC@sergeyproduct/701 · this entry8 Jun 2026, 08:47 UTC1.00under a minute
@sergeyproduct/702 · this entry11 Jun 2026, 07:01 UTC@eduproduct/58511 Jun 2026, 07:35 UTC1.0034 minutes
@sergeyproduct/703 · this entry13 Jun 2026, 09:56 UTC@eduproduct/58613 Jun 2026, 13:51 UTC1.003.9 hours
@eduproduct/59228 Jun 2026, 07:31 UTC@sergeyproduct/714 · this entry5 Jul 2026, 09:32 UTC1.007 days
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@eduproduct12 (8/8 hand-verifiable sample passed)1.002.5 hourseven
@productcasebar8 (8/8 hand-verifiable sample passed)1.004.5 hoursthis entry (53)
@productconsult5 (5/5 hand-verifiable sample passed)1.005.2 hoursthis entry (32)
@FreshProductGo5 (5/5 hand-verifiable sample passed)1.0026 hours@FreshProductGo (50)

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 14 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 20 comparable posts for this entry, running 30 May 2026 to 5 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 5, the earliest publisher we hold is @eduproduct. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual, 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 4 other registered channels, 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

4,6044,6084,6067 August 2026 — 4,607 subscribers7 August 2026 — 4,607 subscribers7 August 2026 — 4,608 subscribers10 August 2026 — 4,604 subscribers7 August 202610 August 2026
4 measurements spanning 3 days, net -3. 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 4,603–4,609 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 01:054,604-4
7 Aug 2026, 06:004,608+1
7 Aug 2026, 01:004,607no change
7 Aug 2026, 00:554,607first reading

Engagement

21 posts held, back to 30 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 7 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
4.49%
avg views ÷ 4,604 subscribers
Avg views / post
207
5 posts measured
Reaction rate
1.09%
reactions ÷ views · ER floor
Posts in window
5
of 21 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. It is computed over the 4 of 5 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 8 August 2026
Posts held21 (30 May 20268 August 2026)
Views total1,034
Reactions total10
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 05:45 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

Photos
50
Videos
5
Links
445

Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

35 reactions across 15 posts, in 2 distinct kinds. The most used accounts for 77.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍2777.1%
🔥822.9%

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 15 of the 21 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 35reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 30 May 2026 to 8 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.

Advertising

Ad load
4.76%
1 of 21 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
241
over 1 measured post
Median views · rest
228
over 20 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor.A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2W5zFGxo89w123 June 202623 June 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 21 most recent posts we hold, published 30 May 2026 to 8 August 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

8 Aug 2026, 10:32 UTC116 viewsread 12 August 2026

Все для роста от редакции канала 1. Образовательные возможности редакции (можно с счета юрлица, можно придумать персональную рассрочку): Для тех, кто хочет системно расти в продакт-менеджменте: - Курс по Продуктовой стратегии и защите инициативы • Курс по развитию продаж и услуг в консалтинге 2. Разборы кейсов, 76 разборов прошли, всего свыше 190 тестовых и реальных задач продактов. Плейлист доступен по ссылке 3.

Signed Sergey Koloskov

5 Aug 2026, 13:05 UTC157 views2 reactionsread 12 August 2026

Как траблшутинг помогает решать проблемы продакт-менеджера? В большинстве компаний проблемы диагностируют очень поверхностно. Упала конверсия - значит проблема в UX. Упали продажи - значит проблема в маркетинге. Пользователи жалуются - значит проблема в продукте. Но если посмотреть разборы крупных инцидентов в банках, маркетплейсах, финтехе и SaaS-компаниях, оказывается, что реальная причина почти всегда находится н

👍2

Signed Sergey Koloskov

29 Jul 2026, 07:02 UTC239 views3 reactionsread 12 August 2026

Как понять, что встреча – не собеседование, а выжимание информации? Самые опасные случаи сбора экспертизы под видом найма выглядят максимально профессионально Настолько профессионально, что многие сильные консультанты и продакты понимают это только спустя несколько месяцев, когда видят свои идеи в продукте компании. В нормальном найме объем информации примерно симметричен. 1. Один из самых сильных сигналов - вас пр

👍2🔥1

Signed Sergey Koloskov

27 Jul 2026, 14:04 UTC205 views3 reactionsread 12 August 2026

Закономерности остаются удивительно стабильными уже десятилетиями Фокус продакта не только про Gartner Hype Cycle. Гораздо важнее понимать, какие силы реально двигают продукты, рынки и поведение пользователей. Есть несколько моделей, которые я бы поставил в обязательный набор любого сильного продакта. 1. S-Curve Innovation. Практически любая технология проходит одинаковый путь: медленный старт, взрывной рост, насыщ

👍3

Signed Sergey Koloskov

14 Jul 2026, 08:35 UTC317 views2 reactionsread 12 August 2026

Что останется незыблемым в профессии продакта с учетом AI Просматривая свое выступление про классику продакт-менеджмента, убеждаюсь: чем больше AI забирает механическую часть работы, тем ценнее становятся вещи, которые никогда не были про документы, SQL или презентации. 1. Выбор проблемы. Большинство компаний тонут не потому, что не умеют реализовывать идеи. Они тонут потому, что реализуют не те идеи. AI может пред

👍2

Signed Sergey Koloskov

12 Jul 2026, 09:47 UTC245 views3 reactionsread 12 August 2026
Forwarded from @FreshProductGo

Фичи, которые стали тиражируемыми Большинство тиражируемых продуктовых фич родились как решение очень локальной проблемы. А потом их начал копировать весь мир. Это 2-я часть в серии постов, вот первый https://t.me/FreshProductGo/1809 • Казахстан – счет на оплату по QR из любого контекста. Любой человек или бизнес может за секунды сгенерировать QR на конкретную сумму и получить оплату без терминала, эквайринга и сло

👍3

Signed Sergey Koloskov

5 Jul 2026, 09:32 UTC286 viewsread 12 August 2026

Все для роста от редакции канала 1. Обратите внимание на предложение в основном канале редакции https://t.me/FreshProductGo/1792 2. Образовательные возможности редакции (можно с счета юрлица, можно придумать персональную рассрочку): Для тех, кто хочет системно расти в продакт-менеджменте: - Курс по продакт-менеджменту, базовый - Карьерный интенсив с разборами тестовых - Курс по аналитике, базовый - Курс по Продукт

Signed Sergey Koloskov

1 Jul 2026, 12:24 UTC277 views1 reactionsread 12 August 2026

Вопросы для понимания, на чем лучше зарабатывать в продукте После прошлого поста многие задали хороший вопрос: а как вообще понять, на чем компании выгоднее всего зарабатывать? Есть ощущение, что это какая-то магия, доступная только CEO и финансистам. На самом деле у сильных продактов есть несколько очень практичных приемов. Если вам нужна помощь в росте продуктов и команды, пишите @SKoloskov (свыше 120 кейсов на 7

👍1

Signed Sergey Koloskov

27 Jun 2026, 06:15 UTC273 views3 reactionsread 12 August 2026

Какие кейсы у продактов по запускам на новых рынках? Многие пишут в резюме: запустил продукт в новой стране. Начинаешь задавать вопросы – и выясняется, что человек координировал перевод приложения, договорился с локальной платежкой и участвовал в запуске маркетинга. Это полезная работа, но она мало похожа на настоящий вывод продукта на новый рынок. Для меня первый признак сильного продакта — он начинает рассказ не

👍3

Signed Sergey Koloskov

24 Jun 2026, 13:34 UTC244 views2 reactionsread 12 August 2026

Мы недооцениваем масштаб изменений, которые происходят сейчас на стыке бизнеса и образования Традиционная модель выглядела так: университет дает знания, студент их получает, а компания уже на рабочем месте превращает выпускника в специалиста. Эта схема работала десятилетиями, пока скорость изменений внутри бизнеса была ниже скорости обновления образовательных программ. Но сегодня ситуация изменилась. Во многих профе

🔥2

Signed Sergey Koloskov

23 Jun 2026, 11:45 UTC241 viewsread 12 August 2026
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Signed Sergey Koloskov

21 Jun 2026, 08:16 UTC220 viewsread 12 August 2026

Все для роста от редакции канала 1. Образовательные возможности редакции (можно с счета юрлица, можно придумать персональную рассрочку): Для тех, кто хочет системно расти в продакт-менеджменте: - Курс по продакт-менеджменту, базовый - Карьерный интенсив с разборами тестовых - Курс по аналитике, базовый - Курс по Продуктовой стратегии и защите инициативы - Сайт команды 2. Разборы кейсов, 76 разборов пришли, всего

Signed Sergey Koloskov

Showing the 12 most recent of 21 posts we hold for @sergeyproduct. 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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Koloskov: growth, product, analytics” (@sergeyproduct), 4,604 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/sergeyproduct.

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.