IBM engagement report
@IBM - 718K followers on X
Measured over 10 original posts from a 30-day window, last computed on September 1, 2026.
Engagement
A typical post picks up 106 interactions against 718K followers, an engagement rate of 0.015%. Measured over 10 original posts, its engagement rate beats 39% of 3,791 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 18K times each, and 0.584% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 10 posts sampled, 30% carry an image or video, 50% are part of a thread and 20% link out. The account's strongest tracked post pulled 805 interactions, about 7.6x its own typical post.
Measured over 10 original posts from a 30-day window, last computed on September 1, 2026.
Compared with accounts its own size
IBM's engagement rate beats 39% of the tracked X accounts closest to it in follower count (3,791 accounts, accounts of similar size (decile 8 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 38% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.015%, IBM sits above the 25th percentile of the 36,654 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.433% |
| 90th percentile | 2.10% |
| 99th percentile | 160.5% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 14:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 51K |
| 01:00 UTC | -2% | 52K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 52K |
| 08:00 UTC | -4% | 61K |
| 09:00 UTC | -3% | 70K |
| 10:00 UTC | -2% | 72K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 94K |
| 14:00 UTC | -4% | 97K |
| 15:00 UTC | -2% | 101K |
| 16:00 UTC | -3% | 98K |
| 17:00 UTC | -2% | 91K |
| 18:00 UTC | -1% | 85K |
| 19:00 UTC | -1% | 80K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -1% | 57K |
| 23:00 UTC | -2% | 52K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 231K |
| Monday | 0% | 288K |
| Tuesday | -2% | 278K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 245K |
| Friday | -3% | 253K |
| Saturday | +3% | 227K |
Best tweets
- Aug 19, 20267.6x their median
Quantum progress isn't just about qubits. ⚛️ To build fault-tolerant quantum computing, refrigeration hardware must evolve alongside processors. That's why we're introducing a new modular cryogenic architecture. Here are the details 🧵👇 https://t.co/R7adUV9LLk
- Aug 27, 20264.3x their median
Some problems are too complex for today's computers. That's where quantum comes in. ⚛️ Discover the differences between quantum and classical computing below ⤵ https://t.co/Jd0OwNcvKj
- Aug 20, 20264.2x their median
https://t.co/5dgme4ApXZ
- Jul 31, 20264.0x their median
If you only look at qubit count, you're missing most of the picture. Here are the 3 hardware metrics that reveal how powerful a quantum computer really is. 🧵 https://t.co/Ly5rY8TcjO
- Jul 31, 20263.7x their median
Quantum computing is making headlines, but the bigger story is what comes next. In a recent interview on @jimcramer's @MadMoneyOnCNBC, IBM Chairman and CEO Arvind Krishna discusses how quantum can help unlock breakthroughs across materials, medicine, energy and more. Read the full conversation: https://t.co/CAmlqITvVc
- Jul 30, 20261.9x their median
hi, this is the social intern. Thanks for all the likes this summer. I'll be adding every single one to my résumé. #NationalInternDay
- Aug 12, 20261.8x their median
https://t.co/OcAQrAvt47
- Jul 21, 20261.6x their median
Data privacy regulations are tightening globally, but AI models still need massive datasets to train effectively. The workaround? Synthetic data. Here’s why the future of AI might rely on information that doesn't actually exist... 🧵 https://t.co/ut65taoBES
- Jul 29, 2026
https://t.co/lgp5ecfZGs
- Aug 17, 2026
Welcome back to Tech Term of the Week! 🥳 This week's term → agentic coding - /əˈdʒɛn.tɪk ˈkoʊ.dɪŋ/ Definition → AI systems that combine reasoning capabilities from LLMs with access to coding tools and execution environments. Why it matters → Unlike simple chat interfaces, coding agents operate across multiple layers of the development stack. This helps them test, debug, iterate and deploy solutions autonomously.
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 106 interactions against 718K followers, an engagement rate of 0.015%. Measured over 10 original posts, its engagement rate beats 39% of 3,791 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 18K times each, and 0.584% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 10 posts sampled, 30% carry an image or video, 50% are part of a thread and 20% link out. The account's strongest tracked post pulled 805 interactions, about 7.6x its own typical post.
- What is IBM's engagement rate on X?
- IBM (@IBM) has an engagement rate of 0.015%, based on the median interactions across 10 original posts from the last 30 days against 718,292 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.015%, IBM sits above the 25th percentile of the 36,654 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @IBM have real engagement?
- Its engagement rate beats 39% of the tracked X accounts closest to it in follower count (3,791 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @IBM post?
- Most posts go out around 14:00 UTC, and Monday is its busiest day, at roughly 1.5 posts per day across the measured window.