Back to @IBM's profile

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

Middle of its size range
Per follower
0.015%
of 718K followers
Per impression
0.584%
18K views on a typical post
Reach
2.52%
of its followers see a post
Typical post
106
interactions (median)
Saved
0.094%
17 bookmarks on a typical post
Posting rate
1.5/day
active 60% of days
Peak time
14:00 UTC
Monday

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%.

p100.002%
p250.012%
p50 (median)0.08%
p750.433%
p902.10%
p99160.5%
Engagement rate as a share of followers, across the 36,654 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 106,977 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.433%
90th percentile2.10%
99th percentile160.5%

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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 14:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%231K
Monday0%288K
Tuesday-2%278K
Wednesday-1%251K
Thursday-1%245K
Friday-3%253K
Saturday+3%227K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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

    626116451828K viewsView on X
  • 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

    3607419717K viewsView on X
  • Aug 20, 20264.2x their median

    https://t.co/5dgme4ApXZ

    31597171225K viewsView on X
  • 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

    3316620827K viewsView on X
  • 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

    29670151226K viewsView on X
  • 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

    164824225K viewsView on X
  • Aug 12, 20261.8x their median

    https://t.co/OcAQrAvt47

    1314215319K viewsView on X
  • 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

    1092128731K viewsView on X
  • Jul 29, 2026

    https://t.co/lgp5ecfZGs

    753617315K viewsView on X
  • 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.

    851415121K viewsView on X

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.

Buy or sell X accounts - escrow-protected

PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.

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.

Keep going