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Channel

Потребительское поведение; факты и тренды

@c_behavior

On this record: Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

8,892subscribers

+28 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001125692324
TypeChannel
Username@c_behavior
Created7 August 2017measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live3 September 2026
Measurements held10
Confirmed unchanged1 time, most recently 3 September 2026
On Telegramt.me/c_behavior

Growth

8,8618,8928,876.56 August 2026 — 8,864 subscribers6 August 2026 — 8,864 subscribers8 August 2026 — 8,861 subscribers11 August 2026 — 8,871 subscribers15 August 2026 — 8,879 subscribers17 August 2026 — 8,882 subscribers20 August 2026 — 8,884 subscribers24 August 2026 — 8,891 subscribers27 August 2026 — 8,890 subscribers3 September 2026 — 8,892 subscribers6 August 20263 September 2026
10 measurements spanning 28 days, net +28. 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 8,856–8,897 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
3 Sept 2026, 11:408,892+2
27 Aug 2026, 23:268,890-1
24 Aug 2026, 18:458,891+7
20 Aug 2026, 21:368,884+2
17 Aug 2026, 21:558,882+3
15 Aug 2026, 02:578,879+8
11 Aug 2026, 19:258,871+10
8 Aug 2026, 23:108,861-3
6 Aug 2026, 03:008,864no change
6 Aug 2026, 02:288,864first reading

Engagement

25 posts held, back to 6 April 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 31 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.95%
avg views ÷ 8,892 subscribers
Avg views / post
618
5 posts measured
Reaction rate
0.252%
reactions ÷ views · ER floor
Posts in window
5
of 25 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 27 August 2026
Posts held25 (6 April 202627 August 2026)
Views total3,092
Reactions total7
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 16:07 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
55s
Average length
28s

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.

Reaction mix

87 reactions across 24 posts, in 6 distinct kinds. The most used accounts for 47.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4147.1%
👍3236.8%
🔥55.75%
👎44.60%
33.45%
👌22.30%

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 24 of the 25 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 87 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 25 most recent posts we hold, published 6 April 2026 to 27 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
4.00%
1 of 25 posts carry an ad marker
Regulatory tokens
0
none — marked by hashtag only
Median views · ads
446
over 1 measured post
Median views · rest
1,320
over 24 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.

Measured over the 25 most recent posts we hold, published 6 April 2026 to 27 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

27 Aug 2026, 12:56 UTC362 views1 reactionsread 28 August 2026
Video

CX/UX Конф — конференция о клиентском опыте и человекоцентричности Почему одними продуктами хочется пользоваться снова, а другие забываются через минуту? Поговорим о том, как рождается клиентский опыт — от первых дизайн-решений до эмоций, которые остаются после взаимодействия с продуктом. Разберём: 🔘как создавать продукты, которые подстраиваются под человека, а не наоборот 🔘как проектировать эмоциональный дизайн, к

👍1

27 Aug 2026, 11:02 UTC316 viewsread 28 August 2026
Photo

Человек не всегда способен точно оценить приемлемую для себя степень риска – многое зависит от ситуации. Такой вывод можно сделать из опроса ВЦИОМ (август 2026 г., 1600 человек). Социологи предложили респондентам вначале идентифицировать себя как «осторожных» или «готовых рисковать» людей. Затем их попросили определиться с решением в трех ситуациях. В одном случае речь шла о банковских вкладах, в другом о трудоустр

27 Aug 2026, 06:24 UTC446 views1 reactionsread 28 August 2026
Advertisement

💽 3 сентября стартует последний поток курса "Анализ качественных данных". Это авторский курс Константина Ефимова и Анастасии Жичкиной, социальных психологов, исследователей с 20+ лет опыта, авторов телеграм-канала @PostPostResearch и книги "Качественные исследования в бизнесе" Повторять этот курс Константин и Анастасия больше не планируют. В этом году - скидка 15% по промокоду FINAL2026 Стоимость: 50 000 ₽ / 570

👍1

17 Aug 2026, 10:17 UTC928 views4 reactionsread 28 August 2026
Photo

Появление ИИ пока не перевернуло привычную логику поиска товаров. Покупатели встраивают его в уже знакомый процесс. По данным исследования агентства «Ашманов и партнёры», 27% респондентов часто используют ИИ как дополнение к поисковику при работе с уже найденными товарами. Заметим, что обращение к ИИ не обязательно завершает поиск. После него часть покупателей возвращается к поисковику или переходит на маркетплейс:

2👍2

10 Aug 2026, 07:03 UTC≈1,040 views1 reactionsread 28 August 2026
Photo

Подготовка к дальней поездке кажется привычным сценарием: проверить автомобиль, заправиться, проложить маршрут, рассчитать время. Однако исследование «Авито Авто» и «Самоката» показывает, что эти действия распространены неодинаково. Более половины опрошенных заранее проверяют техническое состояние автомобиля (52%) и заправляют полный бак (50%), тогда как маршрут и тайминг планируют лишь 26%. Появление похожего патте

1

28 Jul 2026, 05:59 UTC≈1,250 views3 reactionsread 28 August 2026
Forwarded from @artefactyVideo

Пьяной горечью Фалерна Чашу мне наполни, мальчик! Так Постумия велела, Председательница оргий. Вы же, воды, прочь теките И струёй, вину враждебной, Строгих постников поите: Чистый нам любезен Бахус. 18 февраля 1832 Катулл в переводе А.С.Пушкина 🥂 📖Богема отдыхает

👍21

1 Jul 2026, 09:36 UTC≈1,700 views3 reactionsread 28 August 2026
Photo

Рынок AI-решений взрослеет. Ещё недавно самой фразы «у нас есть AI» было достаточно, чтобы создать ощущение «инновационности» компании. Теперь слов недостаточно. Да, сегодня AI есть у многих, почти у всех. Но как он используется? В одних случаях это реальный инструмент, повышающий качество исследований, в других лишь маркетинговая оболочка поверх известной базовой модели. Когда технология становится массовым обещан

👍3

4 Jun 2026, 15:00 UTC≈2,080 views7 reactionsread 28 August 2026
Photo

Реклама может быть заметной, но остаться незамеченной, - парадоксально, но факт. Об этом свидетельствуют результаты исследования «Экономика внимания» компании СберСеллер и платформы Perfluence. Восприятие людьми разных форматов рекламы демонстрирует эту закономерность особенно ярко. Более визуально насыщенные креативы — карусели и HTML-баннеры — запоминались заметно лучше контекстных и менее выразительных форматов.

5👍1🔥1

3 Jun 2026, 15:05 UTC≈1,350 views7 reactionsread 28 August 2026
Photo

Покупатели часто приходят к блогерам за советом, но далеко не всегда готовы передавать им право окончательного выбора. Исследование Мегамаркета, Rambler&Co и Perfluence показывает, что только треть (31%) респондентов хотя бы один раз за последний год покупали товары по рекомендациям блогеров. При этом тех, кто назвал такие советы лишь дополнительным фактором при выборе, почти вдвое больше — 53%. Рекомендации блогеро

3👍3🔥1

2 Jun 2026, 11:04 UTC≈1,070 views5 reactionsread 28 August 2026
Photo

Сервис доставки обычно строится вокруг заранее определённой точки: дома, офиса или пункта выдачи. Но так будет не всегда. В исследовании Самоката и Rambler&Co респонденты полагают, что ситуация изменится, и заказ будет приходить туда, где человек находится прямо сейчас. 21% участников опроса говорят о возможности получить его «где угодно», а среди заинтересованных в аэродоставке 40% хотели бы получать покупки прямо п

👍32

1 Jun 2026, 06:10 UTC≈1,040 views4 reactionsread 28 August 2026
Photo

Туристы используют местный алкоголь не только как элемент своеобразия поездки, но и как способ сохранить впечатления, вернувшись домой. Вино (алкоголь) пьют в разных ситуациях отдыха отдыха: пляж, ресторан, вечерняя прогулка, дегустация в номере. Для части путешественников поиск новых локальных вкусов вообще становится самоценным. Исследование бренда SimpleWine и сервиса бронирований «Отелло» показало, что 43% поку

2👍2

22 May 2026, 12:45 UTC≈1,360 views3 reactionsread 28 August 2026

Коллеги! Для публикаций в тг канале Потребительское поведение нам нужны данные маркетинговых и социологических исследований, так или иначе связанных с поведением потребителей в любой сфере экономики. В первую очередь, интересуют исследования о процедурах принятия решений, новых потребительских практиках, нормах, привычках и изменениях повседневного поведения людей. Обратите внимание: речь не об измерениях параметров

👍3

Showing the 12 most recent of 25 posts we hold for @c_behavior. 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

Named by 3 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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Нильсен
@nielsenrussia · 33,712
Telegram ranks this channel #4 of 99 here — alongside 98 others — read 4 September 2026
FMCG Report
@fmcg_ru · 42,904
Telegram ranks this channel #8 of 97 here — alongside 96 others — read 29 August 2026
Книжная полка маркетолога
@Knizhnaya_polka_marketologa · 35,481
Telegram ranks this channel #12 of 83 here — alongside 82 others — read 2 September 2026
Психология Маркетинга
@marketpsy · 175,001
Telegram ranks this channel #21 of 98 here — alongside 97 others — read 12 August 2026
Постмаркетинг
@pstmarketing · 65,079
Telegram ranks this channel #32 of 99 here — alongside 98 others — read 21 August 2026
Зубастый маркетолог
@marketolog_digital · 49,215
Telegram ranks this channel #34 of 80 here — alongside 79 others — read 26 August 2026
PORNSTAT / статистика
@pornstat · 32,577
Telegram ranks this channel #63 of 93 here — alongside 92 others — read 5 September 2026

This channel appears in 7 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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

“Потребительское поведение; факты и тренды” (@c_behavior), 8,892 subscribers as measured 3 September 2026. Telegram Register, tgregister.com/channel/c_behavior.

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.