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UX Magazine engagement report

@uxmag - 242K followers on X

Measured over 3 original posts from a 30-day window, last computed on September 10, 2026.

Engagement

Per follower
0.001%
of 242K followers
Per impression
0.097%
3.1K views on a typical post
Reach
1.27%
of its followers see a post
Typical post
3
interactions (median)
Saved
0.065%
2 bookmarks on a typical post
Posting rate
0.1/day
active 10% of days
Peak time
14:00 UTC
Tuesday

Early reading. We have captured 3 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 3 interactions against 242K followers, an engagement rate of 0.001%. Posts are seen about 3.1K times each, and 0.097% of those impressions turn into an interaction. That is about 1.27% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.1 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 3 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 7 interactions, about 2.3x its own typical post. Recurring topics include #ai, #enterpriseai, #aiadoption. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 3 original posts from a 30-day window, last computed on September 10, 2026. Recurring tags: #ai, #enterpriseai, #aiadoption.

Where this sits in the catalog

At 0.001%, UX Magazine sits below the 10th percentile of the 66,258 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.016%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.6%
Engagement rate as a share of followers, across the 66,258 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,968 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 percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile119.6%

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 Tuesday 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 111%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%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video100% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 100% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 100% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 281 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Jul 20, 20262.3x their median

    #AI doesnโ€™t understand users. It just recognizes patterns in language. Ignoring this distinction is a design flaw, and it has real consequences. Tushar Deshmukh continues revealing the traps AI creates for designers and showing how to avoid them: https://t.co/qnoXNQHfWV https://t.co/9qSqshKYrT

    33101.8K viewsView on X
  • Aug 11, 20261.7x their median

    #AI doesn't fail because the model isn't smart enough. It fails because enterprises try to build features before structure. Evan J. Schwartz explains why successful #AIAdoption starts with outcomes, actors, and boundaries, not prompts. ๐ŸŽ™๏ธ https://t.co/VBryeJ0QyB #EnterpriseAI https://t.co/3vzlejCJpl

    50003.1K viewsView on X
  • Aug 10, 20261.7x their median

    AI can explain concepts, answer questions, and personalize lessons. But can it truly make a student feel acknowledged, supported, and inspired? ๐Ÿ“– Read more: https://t.co/FhzxWwbEfZ #AI #Education #EdTech https://t.co/G2B1gYywc7

    41003.3K viewsView on X
  • Jul 14, 20261.7x their median

    "#VibeCoding" is a useful term for a specific behavior, but it was never a description of design leadership. Jim Gulsen, an accomplished UX/UI designer, breaks down a more intentional approach to #AI-assisted design. ๐Ÿ‘‰ Read the full piece: https://t.co/P30aowJg2S #UXDesign https://t.co/pdEBz2HbHC

    31102.0K viewsView on X
  • May 15, 20261.7x their median

    The hardest design skill in agile? Thinking smaller. Pรคivi Salminen discusses how designing small is one of the hardest skills to learn in agile environments. ๐Ÿ‘‰ Read the full piece: https://t.co/ENJxaKhkbn #Agile #ProductDesign #UserResearch #UXDesign https://t.co/Dy93XSU048

    41001.3K viewsView on X
  • Jun 10, 2026

    Bad gamification is just homework with points ๐ŸŽฎ Montgomery Singman explains why younger users spot bad gamification instantly and what it really takes to get their attention. ๐Ÿ‘‰ Read the full piece: https://t.co/JJ1Sn8b0kW #GameDesign #ProductDesign #UXDesign https://t.co/bOdmFg4ZL4

    40001.1K viewsView on X
  • Jun 2, 2026

    How do we build #AI systems that earn genuine human trust? After six months of moving past viral prompts and #vibecoding, that central question remains. ๐Ÿค” Anina Botha explores the complexities of human-AI interaction. ๐Ÿ‘‰ Explore the full insights: https://t.co/FbvdMt7ST6 https://t.co/sseloAqKR3

    31002.1K viewsView on X
  • May 19, 2026

    Your AI system looks good: dashboards are green, alerts are quiet, and it is still failing. Kwansah Madani outlines why silent failure is the signature challenge of AI systems. ๐Ÿ“– Read the full piece: https://t.co/eTRD2UOOtw #AI #MachineLearning #SoftwareDevelopment https://t.co/m5NYowPlm1

    31001.1K viewsView on X
  • Aug 13, 2026

    You can build AI agents in a day. Governing them? That lasts for as long as they're in production. A practical read for anyone building or managing AI agents: https://t.co/FnHJyMYQpD #AI #EnterpriseAI #AgenticAI #AIGovernance https://t.co/YkMwsVrIha

    21003.4K viewsView on X
  • Aug 4, 2026

    The FIFA World Cup 2026 marks the largest tournament in football history, but the most profound evolution isn't taking place on the pitch. Nayyer Abbas, a seasoned UX expert, examines how #AI and #UX are together redefining the game: https://t.co/iIMKoJu8DE #FIFAWorldCup2026 https://t.co/sN5eJBQg4X

    30003.6K 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.

Recurring topics

#ai#enterpriseai#aiadoption#agenticai#aigovernance

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 3 interactions against 242K followers, an engagement rate of 0.001%. Posts are seen about 3.1K times each, and 0.097% of those impressions turn into an interaction. That is about 1.27% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.1 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 3 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 7 interactions, about 2.3x its own typical post. Recurring topics include #ai, #enterpriseai, #aiadoption. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is UX Magazine's engagement rate on X?
UX Magazine (@uxmag) has an engagement rate of 0.001%, based on the median interactions across 3 original posts from the last 30 days against 242,035 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.001%, UX Magazine sits below the 10th percentile of the 66,258 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 @uxmag have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @uxmag post?
Most posts go out around 14:00 UTC, and Tuesday is its busiest day, at roughly 0.1 posts per day across the measured window.

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