Channel
@b2broker
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
9,044subscribers
-61 since we began measuring on 5 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001069582772 |
|---|---|
| Type | Channel |
| Username | @b2broker |
| Description | N1 Financial Technology and Liquidity Provider for FOREX and CRYPTO |
| Created | Between 1 July 2016 and 30 April 2017— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 25 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 25 August 2026 |
| On Telegram | t.me/b2broker |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 25 Aug 2026, 01:47 | 9,044 | -17 |
| 21 Aug 2026, 18:06 | 9,061 | -15 |
| 18 Aug 2026, 18:03 | 9,076 | -5 |
| 15 Aug 2026, 19:24 | 9,081 | -7 |
| 12 Aug 2026, 07:18 | 9,088 | -16 |
| 9 Aug 2026, 13:11 | 9,104 | -3 |
| 6 Aug 2026, 23:40 | 9,107 | +2 |
| 6 Aug 2026, 02:52 | 9,105 | no change |
| 5 Aug 2026, 23:21 | 9,105 | first reading |
27 posts held, back to 23 June 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 28 pagesof Telegram’s post history, 20 posts per page.
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 9 of 11 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 August 2026 |
|---|---|
| Posts held | 27 (23 June 2026 – 26 August 2026) |
| Views total | 3,049 |
| Reactions total | 23 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 26 Aug 2026, 08:35 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.
Lifetime counters from Telegram’s own channel header, read 26 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
76 reactions across 24 posts, in 5 distinct kinds. The most used accounts for 65.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| custom 5355075699801596795 | 50 | 65.8% | |
| ❤ | 15 | 19.7% | |
| ⚡ | 9 | 11.8% | |
| 🏆 | 1 | 1.32% | |
| 👀 | 1 | 1.32% |
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 25 of the 27 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 78reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 27 most recent posts we hold, published 23 June 2026 to 26 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.
Should You Outsource or Perform In-house Maintenance? Your platform needs someone watching it at 3am on a Sunday. The question is whether that someone is on your payroll. 🛠 Platform maintenance is three jobs bundled under one word: — Infrastructure (server health monitoring, OS patching, network latency management) — Application (bug fixes, updates, third-party integrations, MT4/MT5 plugin configuration) — Complia…
🛠 In-House vs Ready-Made CRM Software: What to Choose? Most brokers don't lose to competitors on features. ⏱️ They lose the 12–24 months it takes to build their own CRM. 📊 A Broker CRM is the system that runs everything around the trade: onboarding, KYC, wallets, payments, client segmentation, IB payouts, and reporting — all synced in real time. Either build one, or deploy a ready CRM. Here’s how they compare: 👇 …
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🏛 Starting a Broker-Dealer? License Is Only a Part of the Journey Launching in the US involves much more than submitting an application. Your business model affects everything from capital requirements to compliance staffing and technology infrastructure. What you need to plan 🎯 📄 SEC registration and FINRA membership 🛡 SIPC enrolment and state-level filings 💰 Net capital requirements based on your operating model…
❤3
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⚡️ Liquidity Provider vs Market Maker Most brokers pick a model without fully stress-testing it. That’s where margin calls (and headaches) come from. Do you actually know the difference 🤔 📊 Liquidity Provider = external pricing, A-book flow, lower risk 🎲 Market Maker = internal pricing, B-book exposure, higher margin 🔀 Hybrid = the middle ground most growing brokers land on The right model depends on your client m…
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📊 Last Look vs No-Last Look Execution: What Brokers Must Know ⚖️ Choosing the right execution model influences pricing transparency, risk exposure, and client experience. 👉 Last Look gives LPs discretion before confirming orders, while No-Last Look commits immediately. What’s the trade off? Key differences: 🔎 Execution certainty vs risk control 💱 Price quality implications 🌐 Infrastructure & partner consideration…
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💡 What Actually Happens Between Brokers & Liquidity Providers? Every trade your client executes travels through a chain — and most brokers don’t fully understand it until something breaks. 🔗 The flow looks like this: 1️⃣ Client places order 2️⃣ Broker routes it (A-book, B-book, or hybrid) 3️⃣ LP prices it and fills it (or doesn’t) 4️⃣ Execution quality determines your reputation 📊 Your choice of LP shapes spreads…
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🔐 Compliance Solutions for Brokers: Evaluate & Integrate ⚖️ Compliance isn’t a checkbox — it’s the foundation of trust, market access, and long-term sustainability for any brokerage or trading platform. Why is it important? 🤔💭 🚫 Gaps in compliance mean fines, restricted access, reputational risk. ✅ Staying ahead means embedding robust solutions into your tech stack. This way, your brokerage is: 🔒 Protected from r…
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📈 Buy-Side vs 📉 Sell-Side Liquidity: Key Differences for Brokers Liquidity comes from buy-side demand and sell-side supply. This is what brokers need to understand to fine-tune execution settings and risk management. 🔒 🔎 Our guide compares each side’s influence on depth, pricing, and fill quality. What you’ll learn: 📊 How buy-side & sell-side liquidity differ 💱 Impact on spreads and execution 💻 What it means for …
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🌐 MetaTrader Liquidity Providers: Improve Your Execution Setup 🔗 MT platforms rely on quality liquidity providers for competitive pricing and execution. This is how you reduce rejection and slippage. 🔎 This article shows where brokers can source, evaluate, and integrate MetaTrader liquidity partners that support scalable execution models. What you’ll learn: 💡 🔷 MT-specific liquidity challenges 🔷 Evaluation criter…
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⁉️ Ever Heard of Last Look in FX? What You Need to Know 🔍 Last Look is an execution model where liquidity providers may accept or reject orders before completion. It is not necessarily a good or bad thing. How does it affect traders? 🤔 It depends on the provider’s response (accept or reject). Understanding Last Look helps balance risk management with execution quality and client fairness. 📖 Learn more: Last Look i…
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Showing the 12 most recent of 27 posts we hold for @b2broker. 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.
Citation-graph rank — 736,771 of 1,604,161entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
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 25 August 2026 — this entry's latest reading, not the date you are reading this.
“B2BROKER | Fintech Infrastructure & Liquidity Solutions” (@b2broker), 9,044 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/b2broker.
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.