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Telegram profile photo for Catalina create

Channel

Catalina create

@catalinacreate

On this record: Growth · Engagement · Posts · Citations · Cite this entry

70subscribers

+13 since we began measuring on 3 November 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1004337853554
TypeChannel
Username@catalinacreate
Created2 November 2026 — measured — dated from the channel’s first post
First recorded3 November 2026
Last confirmed live3 November 2026
Measurements held2
Confirmed unchanged1 time, most recently 3 November 2026
On Telegramt.me/catalinacreate

Growth

577063.53 Nov 2026, 06:22 — 57 subscribers3 Nov 2026, 19:47 — 70 subscribers3 Nov 2026, 06:223 Nov 2026, 19:47
2 measurements taken within a single day, net +13. 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 55–72 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
3 Nov 2026, 19:4770+13
3 Nov 2026, 06:2257first reading

Engagement

7 posts held, back to 2 November 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 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
95.5%
avg views ÷ 70 subscribers
Avg views / post
66.8
6 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
WindowRolling 30 days · latest post in window 3 November 2026
Posts held7 (2 November 2026 – 3 November 2026)
Views total401
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Nov 2026, 06:22 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.

Recent posts

3 Nov 2026, 00:41 UTC36 viewsread 3 November 2026
Photo

очень рада, что моё последнее видео на ютюбе собрало такой большой отклик и просмотры. на самом деле, кто занимается контентом, тот понимает, насколько тяжело набирать просмотры на ютюбе, особенно в длинном формате. ты буквально конкурируешь за его время. нужно сделать так, чтобы человек захотел провести с тобой 10, 20, а иногда и 40 минут своей жизни. и здесь уже работает совершенно другая механика: удержание ауд…

3 Nov 2026, 00:02 UTC38 viewsread 3 November 2026
Voice message

Прикол из жизнь + Почему так важно нишеваться #podcast

2 Nov 2026, 14:09 UTC104 viewsread 3 November 2026
Photo

🤍ОБО МНЕ И ЭТОМ КАНАЛЕ🤍 Я Каталина. Помимо музыки, танцев и развития собственного бренда одежды, в моей жизни есть ещё одна большая сфера - маркетинг. Сейчас я учусь на втором курсе СПбГЭУ по направлению Рекламы. Параллельно уже работаю в этой сфере, занимаюсь продвижением проектов, разрабатываю стратегии и применяю свои знания на практике. На протяжении всего своего пути я самостоятельно занимаюсь продвижением ли…

2 Nov 2026, 13:34 UTC82 viewsread 3 November 2026
File

ПОЧЕМУ ВАЖНО ПОНИМАТЬ МОДЕЛЬ СВОЕГО БЛОГА? Одна из самых распространённых ошибок в продвижении - отсутствие чёткого позиционирования. Ты можешь регулярно публиковать контент, набирать просмотры и даже привлекать новых подписчиков. Но если у твоего блога нет понятной концепции, удерживать аудиторию будет гораздо сложнее. Это не значит, что в одном блоге нельзя совмещать разные темы. Можно. И даже нужно, если это с…

2 Nov 2026, 13:34 UTC73 viewsread 3 November 2026
Voice message

ПОДКАСТ *пересылка из основного аккаунта Нишевание в экспертных блогах - необходимо для того чтобы захаслить продажи #marketing

2 Nov 2026, 12:45 UTC68 viewsread 3 November 2026

🤎🤎🤎🤎🤎🤎🤎🤎🤎 Помогаю авторам развивать личный бренд, привлекать аудиторию и выстраивать продажи через социальные сети. 𝐒𝐓𝐀𝐑𝐓 𝐇𝐄𝐑𝐄 ↳ Обо мне ↳ Услуги ↳ Вебинары 𝐅𝐑𝐄𝐄 𝐌𝐀𝐓𝐄𝐑𝐈𝐀𝐋𝐒 ↳ Материалы для аудита аккаунта 𝐋𝐄𝐓’𝐒 𝐓𝐀𝐋𝐊 ↳ #podcast - подкасты и мысли ↳ #marketing - маркетинг и продвижение 𝐅𝐈𝐍𝐃 𝐌𝐄 ↳ instagram ↳ tiktok ↳ youtube 𝐆𝐄𝐓 𝐈𝐍 𝐓𝐎𝐔𝐂𝐇 ↳ @catalinamedia

Showing the 7 most recent of 7 posts we hold for @catalinacreate. 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 1 registered channel — 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.

Named by

Channels on the register whose posts name this channel's handle.

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

“Catalina create” (@catalinacreate), 70 subscribers as measured 3 November 2026. Telegram Register, tgregister.com/channel/catalinacreate.

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.