Channel
@activemarketingjungle
On this record: Growth · Engagement · Reactions · Posts · Cite this entry
8,245subscribers
-37 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001359936958 |
|---|---|
| Type | Channel |
| Username | @activemarketingjungle |
| Created | Between 1 April 2018 and 17 March 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 1 September 2026 |
| Measurements held | 11 |
| Confirmed unchanged | 1 time, most recently 1 September 2026 |
| On Telegram | t.me/activemarketingjungle |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 1 Sept 2026, 22:04 | 8,245 | -1 |
| 29 Aug 2026, 11:28 | 8,246 | -6 |
| 26 Aug 2026, 16:16 | 8,252 | -7 |
| 23 Aug 2026, 20:15 | 8,259 | -6 |
| 20 Aug 2026, 15:14 | 8,265 | -3 |
| 17 Aug 2026, 17:28 | 8,268 | -4 |
| 14 Aug 2026, 20:13 | 8,272 | -2 |
| 11 Aug 2026, 19:32 | 8,274 | -9 |
| 9 Aug 2026, 05:52 | 8,283 | +1 |
| 6 Aug 2026, 13:00 | 8,282 | no change |
| 6 Aug 2026, 12:53 | 8,282 | first reading |
20 posts held, back to 17 March 2021 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 21 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 5 January 2024. An engagement rate over an empty window would be a number about nothing.
298 reactions across 14 posts, in 5 distinct kinds. The most used accounts for 60.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 179 | 60.1% | |
| ❤ | 101 | 33.9% | |
| 🔥 | 15 | 5.03% | |
| 👏 | 2 | 0.671% | |
| 😁 | 1 | 0.336% |
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 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 298 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 17 March 2021 to 5 January 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Here's a tip to become a great Product Manager. Build something approach. Find a problem, chat with 10-20 people about it, just ask questions, and organize all the feedback. I prefer to use the Opportunity Solution Tree to visualize my thinking and the best path to my desired outcome. Now, use some cool no-code like Bubble.io, WordPress, or AI tools and create a small product yourself. Maybe even a landing page …
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Product team cases where a #productteams improved content discovery Case: Netflix and Personalized Content Recommendations Problem: Netflix wanted to improve user engagement by enhancing content discovery and reducing churn. Solution: Using a product outcome mindset, Netflix's product team developed a recommendation algorithm that analyzed user viewing behavior and preferences to offer personalized content suggest…
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Let's talk AI basics - Prompt Engineering vs. Blind Prompting Do you want to get the most out of AI? There are two main approaches: prompt engineering and blind prompting. Prompt engineering is a technique where you carefully craft a prompt that guides the Large language models (LLM) to generate the desired output. For example, if you want the LLM to write a list of places to go with kids, you might give it a promp…
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Product management tools & tech stack Tools for capturing qualitative user feedback ▪ Zoom and Chorus.ai for conducting interviews ▪ Slack, Google Docs, or Notion for making notes of key points and action items ▪ Zendesk and Intercom for meeting customers where they are ▪ Saleforce for better understanding the needs and pain points of prospects Tools for capturing quantitative feedback ▪ FullStory records how …
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Channel name was changed to «Product Management»
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Huge company, slim margins Few industries are as competitive as making and selling cars — and Ford's financials are a prime example of this. Despite being a giant, Ford ekes out a slender profit margin. Since 2012 Ford's average net profit margin has averaged just 2.7%. With revenues regularly north of $150bn, that still translates into a sizeable profit of $4bn a year (on average) — but it doesn't leave much room f…
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Showing the 12 most recent of 20 posts we hold for @activemarketingjungle. 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.
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 1 September 2026 — this entry's latest reading, not the date you are reading this.
“Product Management” (@activemarketingjungle), 8,245 subscribers as measured 1 September 2026. Telegram Register, tgregister.com/channel/activemarketingjungle.
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.