Channel
@McKinsey_insights
On this record: Topic · Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry
9,140subscribers
+213 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001255603027 |
|---|---|
| Type | Channel |
| Username | @McKinsey_insights |
| Created | Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 19 September 2026 |
| Measurements held | 14 |
| Confirmed unchanged | 1 time, most recently 19 September 2026 |
| On Telegram | t.me/McKinsey_insights |
Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 19 Sept 2026, 13:00 | 9,140 | +33 |
| 14 Sept 2026, 23:17 | 9,107 | +10 |
| 11 Sept 2026, 03:01 | 9,097 | +26 |
| 6 Sept 2026, 02:37 | 9,071 | +34 |
| 1 Sept 2026, 18:54 | 9,037 | +15 |
| 29 Aug 2026, 17:57 | 9,022 | +12 |
| 26 Aug 2026, 19:47 | 9,010 | +16 |
| 24 Aug 2026, 03:17 | 8,994 | +6 |
| 20 Aug 2026, 04:33 | 8,988 | +14 |
| 17 Aug 2026, 14:28 | 8,974 | +23 |
| 14 Aug 2026, 12:48 | 8,951 | +12 |
| 11 Aug 2026, 02:53 | 8,939 | +10 |
| 7 Aug 2026, 17:57 | 8,929 | +2 |
| 7 Aug 2026, 05:45 | 8,927 | first reading |
20 posts held, back to 28 November 2024 — the 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.
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 17 December 2024. An engagement rate over an empty window would be a number about nothing.
53 reactions across 9 posts, in 2 distinct kinds. The most used accounts for 54.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 29 | 54.7% | |
| ❤ | 24 | 45.3% |
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 11 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 53 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 28 November 2024 to 17 December 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.
Blackstone’s Gilles Dellaert on private credit and insurance https://www.mckinsey.com/industries/financial-services/our-insights/blackstones-gilles-dellaert-on-private-credit-and-insurance The leader of Blackstone Credit and Insurance looks at where the industries have been and where they’re headed.
❤13👍7
The battery chemistries powering the future of electric vehicles https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/the-battery-chemistries-powering-the-future-of-electric-vehicles Battery chemistry for electric vehicles is evolving rapidly, leading to repercussions for the entire value chain.
👍8❤1
The economic state of Latinos in America: Building up small businesses https://www.mckinsey.com/featured-insights/diversity-and-inclusion/the-economic-state-of-latinos-in-the-us Despite a range of challenges, Latino-owned small businesses are growing rapidly. Investing in their potential can support future generations of Latino entrepreneurs and boost the US economy.
👍6❤3
Finding a route to fiscal stability for US transit agencies https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/finding-a-route-to-fiscal-stability-for-us-transit-agencies US transit agencies face a daunting moment in which revenue and funding struggle to keep pace with the escalating costs of growth and innovation. How can balance sheets get back on track?
👍2
How to deliver on the promise of mixed-use real estate developments https://www.mckinsey.com/industries/real-estate/our-insights/how-to-deliver-on-the-promise-of-mixed-use-real-estate-developments McKinsey partner James Patchett discusses the success factors that mixed-use developers are wise to keep top of mind.
👍3❤2
Reflections post COP29: The landscape has shifted—are you adapting fast enough? https://www.mckinsey.com/capabilities/sustainability/our-insights/reflections-post-cop29-the-landscape-has-shifted-are-you-adapting-fast-enough After COP29, as everyone looks ahead to 2025, the outlook on sustainability and related investments is not straightforward. This article captures reflections from our discussions in and around CO…
❤1
2024: The year in charts https://www.mckinsey.com/featured-insights/year-in-review/year-in-charts Here’s a look back at some of our favorite data visualizations from the year.
2024: The year in images https://www.mckinsey.com/featured-insights/year-in-review/year-in-images Explore a visual journey of the imagery that accompanied some of our authors’ biggest ideas and most timely insights in 2024, helping to shape a future defined by innovation and resilience.
❤4
Redefining success: A new playbook for African fintech leaders https://www.mckinsey.com/industries/financial-services/our-insights/redefining-success-a-new-playbook-for-african-fintech-leaders As African fintechs evolve, businesses and investors are shifting their focus from a growth-at-all-costs approach to investing in sustainable paths to success.
Investing in the future of tech: Lessons from winning companies https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/investing-in-the-future-of-tech-lessons-from-winning-companies Survey results suggest that while the overall outlook for tech investments is strong, only a select few companies are investing in the foundations and people that can support future success.
BCBS 239 2.0 resurgence: Strengthening risk management and decision making https://www.mckinsey.com/capabilities/risk-and-resilience/our-insights/bcbs-239-2-0-resurgence-strengthening-risk-management-and-decision-making A renewed focus on the 2013 data risk management regulatory standard poses new challenges and opportunities for European and US banks. Achieving compliance will take a structured, top-led approach.
What is a context window? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-a-context-window A context window is how information is entered into a large language model (LLM). The larger the context window, the more information the LLM is able to process at once.
Showing the 12 most recent of 20 posts we hold for @McKinsey_insights. 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.
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.
This channel appears in 12 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 19 September 2026 — this entry's latest reading, not the date you are reading this.
“McKinsey Insights” (@McKinsey_insights), 9,140 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/McKinsey_insights.
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.