Channel
@alshuju
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
269subscribers
-5 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001682278168 |
|---|---|
| Type | Channel |
| Username | @alshuju |
| Created | 27 July 2022 — measured — dated from the channel’s first post |
| First recorded | 8 August 2026 |
| Last confirmed live | 25 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 25 August 2026 |
| On Telegram | t.me/alshuju |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 25 Aug 2026, 03:24 | 269 | -3 |
| 16 Aug 2026, 19:38 | 272 | -2 |
| 8 Aug 2026, 08:46 | 274 | no change |
| 7 Aug 2026, 18:26 | 274 | first reading |
18 posts held, back to 27 July 2022 — 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 pageof 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 18 posts for this entry, the most recent from 29 December 2025. An engagement rate over an empty window would be a number about nothing.
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 100.0% |
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 1 of the 18 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 1reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 27 July 2022 to 29 December 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🌈支持平台： Telegram、WhatsApp、Viber、Facebook、Zalo、iMessage（筛蓝）、RCS、空号检测 🌈支持内容包含： 手机号开通筛选（判断是否注册 / 是否有效） TG/WS/Viber 活跃筛选、全格式画像筛选 业务类型 单位（RMB元/万条） Telegram筛开通 : 12/万 Telegram筛活跃 : 24/万 Telegram全格式 : 55/万 WhatsApp筛开通 : 1/万 WhatsApp筛活跃 : 12/万 WhatsApp全格式 : 40/万 Facebook筛开通 : 5/万 苹果筛开通 : 12/万 Zalo筛开通 : 18/万 ✅开后台独立操作，有量可议价，详情咨询客服。 ------------------…
❤1
为什么真正做推广的人，都会先把数据筛一遍？ 在 TG、WhatsApp、Facebook 这些平台上，很多人推广效果不稳定，并不是方法不对，而是数据本身就有大量无效项。 未筛选的数据里，往往混着未开通、已失效、无法触达或长期不活跃的账号，操作越多，损耗越快。 数据筛选的价值，不是让你多花钱，而是在操作前先把无效对象剔除，让账号、IP 和时间用在真正可能产生回应的人身上。 当数据足够干净，你会明显感觉到：同样的号、同样的话术，回复更集中，结果也更稳定。 与其不断试错，不如先把数据这一关做对。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
为什么真正做引流的人，都会先筛数据？ 很多引流失败，并不是因为号不行、话术不行，而是一开始就把成本花在了无效数据上。未筛选的数据里，往往混杂着大量无法联系、长期不活跃或已失效的账号，操作越多，损耗越快。 数据筛选的作用，就是在你出手之前，先把这些无效对象剔除，让账号、IP 和时间都用在真正可能产生回应的人身上。 当数据足够干净，你会明显感觉到：同样的操作，回复更集中，效果也更稳定。 与其不断试错，不如先把数据这一关做对。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
为什么数据筛选是所有引流的基础？ 无论是群发、私信还是投放，引流效果不稳定，往往不是方法问题，而是数据本身存在大量无效项。未筛选的数据中，常见问题包括账号未开通、已失效、无法触达或长期不活跃，这些都会直接消耗账号、IP 和操作成本。 数据筛选的核心价值，在于提前排除无效对象，让每一次操作都面对真实、可联系的人群。这样不仅能降低损耗，还能让回复率和转化表现更加稳定。 当数据足够干净，话术和工具才能真正发挥作用；否则，再复杂的策略也只是在放大无效消耗。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
🧠【数据认知】 真正决定你效果的，不是数据量，而是“无效率” 很多人选数据时，第一眼看的是： 有多少万？ 多少钱一条？ 但真正拉开差距的，其实是一个很少有人算的指标： 👉 无效率 无效率高，意味着什么？ 账号白白消耗 IP 权重被拉低 时间被无意义对话拖死 你以为你是在“多打一轮”， 实际上是在不断放大损耗。 数据筛选存在的意义，不是让你多花一笔钱， 而是帮你在最开始，就把 30%–60% 的无效行为砍掉。 当你发现： 同样的操作、同样的号、同样的话术， 结果却明显更稳定—— 那不是你技术变强了， 而是数据终于干净了。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
为什么真正做推广的人，都会把“数据筛选”当成第一步？ 很多人一开始做推广，会把精力放在： 软件怎么选 话术怎么写 账号怎么养 但真正跑过量的人，最后都会回到一个最底层的问题： 👉 你发给的是不是“有可能回复的人” 如果一批数据里包含大量： 未开通账号 长期不活跃账号 已封或异常账号 那么不管你用什么方式推广，结果都会是： 回复率低 账号损耗快 成本越跑越高 这也是为什么很多人会觉得： “刚开始还能跑，越跑越难。” 📊 问题不在操作，而在数据本身。 数据筛选的本质，其实不是“提高转化”，而是“减少浪费”。 很多人算账时，只看单价： 一条数据多少钱 一次群发成本多少 但真正决定亏不亏的，是： 👉 无效数据占比 举个很现实的例子： 不筛数据：10 万条，真正可用可能只有 2–3 万，但你要花10万条的营销成本。 筛过数据：10 万条，过滤掉7-8万无效数据，只需要2-3万有效成本。 这…
🧠【数据认知】 真正决定你效果的，不是数据量，而是“无效率” 很多人选数据时，第一眼看的是： 有多少万？ 多少钱一条？ 但真正拉开差距的，其实是一个很少有人算的指标： 👉 无效率 无效率高，意味着什么？ 账号白白消耗 IP 权重被拉低 时间被无意义对话拖死 你以为你是在“多打一轮”， 实际上是在不断放大损耗。 数据筛选存在的意义，不是让你多花一笔钱， 而是帮你在最开始，就把 30%–60% 的无效行为砍掉。 当你发现： 同样的操作、同样的号、同样的话术， 结果却明显更稳定—— 那不是你技术变强了， 而是数据终于干净了。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
🧩【数据结构】 一份数据，至少可以分 3 层 真正会用数据的人， 不会只看“这一批好不好”。 而是拆成： 1️⃣ 可用层 2️⃣ 低响应层 3️⃣ 淘汰层 这样数据才能反复利用， 而不是用一次就丢。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
🧠【数据认知】 筛选不是加工数据，是“清理噪音” 很多人理解错了筛选的作用： 以为是把数据“变好”。 实际上筛选做的只有一件事： 👉 把不能用的、低价值的、干扰判断的全部剔除。 数据一旦干净， 转化是自然发生的结果。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
📈 什么样的数据，才值得继续投入？ 你可以用一个很简单的判断标准： 👉 你愿不愿意用“付费账号”去打这批数据？ 如果你自己都不敢用号打， 那这批数据大概率是有问题的。 好数据的核心不是“看起来多”， 而是 敢不敢用、能不能复用。 📩 数据筛选 / 合作咨询 👉 私信联系：@alangcn
很多人做营销，第一步就错了。 ❌ 没筛直接群发 ❌ 没检测直接投放 ❌ 用“看起来很多”的数据自我安慰 但现实是： 未开通 = 100%浪费 不活跃 = 几乎无转化 画像不匹配 = 纯消耗账号 📉 真正拉高成本的，从来不是单价 📈 而是 无效数据比例 数据筛选的意义只有一句话： 👉 把钱花在“有回应可能性的人”身上
很多客户问： 为什么同样是群发，有人能跑量，有人号死得很快？ 原因往往不是软件，也不是账号质量， 而是【你发给了谁】。 📉 大量无效号码会导致： - 发送失败率高 - 风控异常 - 账号权重快速下降 📊 筛过的数据： - 有真实使用行为 - 有更高互动可能 - 对账号更友好 所以筛料，本质也是一种“养号保护”
Showing the 12 most recent of 18 posts we hold for @alshuju. 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 — 1,130,390 of 1,605,487entries 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
“阿浪数据自动化营销中心” (@alshuju), 269 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/alshuju.
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.