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Iris Hayes engagement report

@irisneural - 57K followers on X

Measured over 5 original posts from a 30-day window, last computed on October 6, 2026.

Engagement

Per follower
0.159%
of 57K followers
Per impression
1.31%
6.9K views on a typical post
Reach
12.1%
of its followers see a post
Typical post
91
interactions (median)
Saved
0.158%
11 bookmarks on a typical post
Posting rate
1.47/day
active 3% of days
Peak time
00:00 UTC
Monday

Early reading. We have captured 5 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 91 interactions against 57K followers, an engagement rate of 0.159%. Posts are seen about 6.9K times each, and 1.31% of those impressions turn into an interaction. That is about 12.1% 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, though only 3% of days saw any activity at all. Most posts go out around 00:00 UTC, and Monday is the busiest day of the week. Of the 5 posts sampled, 60% carry an image or video and 60% link out. The account's strongest tracked post pulled 1.0K interactions, about 11x its own typical post. Only 5 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 5 original posts from a 30-day window, last computed on October 6, 2026.

Where this sits in the catalog

At 0.159%, Iris Hayes sits above the 50th percentile of the 205,048 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 205,048 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,894 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 percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.678%
90th percentile2.55%
99th percentile82.4%

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 00:00 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: 00:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 00:00 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: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
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 video60% of posts+111%+108% to +115%34K
Outbound link60% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 60% 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.
  • 60% 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 523 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

  • Oct 5, 202611x their median

    Everyone got a coding agent. Nobody got a QA engineer. Until today. Meet Ship, your Autonomous Quality Engineer. It tests deployed PRs, reproduces bugs from Slack and Linear, and hands Claude or Codex the context to fix them. Try it free: https://t.co/iKhsWrVxu9 https://t.co/lgTklYYuwT

    62881139154538K viewsView on X
  • Jun 26, 20261.7x their median

    SHOCKING 🚨 : i think the call center as we know it just died. i watched an ai agent take a furious customer, canceled flight, about to miss his sister's wedding, and calm him down better than most humans would. no script. this is ElevenAgents 🧵 https://t.co/ZJp7XhK5yt

    913821154K viewsView on X
  • Oct 5, 20261.5x their median

    Can an AI tool turn a vague idea into an app I can actually use, without me building it? For quite some time, I’ve been curious about this. Recently, I found one and decided to put it to the test and share my feedback. I gave it a single prompt: “Make a YouTube clipping app that turns long videos into short clips for social.” No spec. No wireframes. What happened next surprised me 👇

    68343526.9K viewsView on X
  • Oct 5, 2026

    Jack Ma told Elon Musk humans will always be smarter than machines. Musk’s reaction says everything. “Computers may be very clever, but human beings are much smarter. We invented the computer. I've never seen a computer invent a human being.” Ma's argument was simple. Computers are tools. They calculate faster, remember more, but humans still hold something machines don't: experience, judgment, wisdom. Musk clearly didn't buy it. “What would be an example of something that humans are better than a computer at?” Watching this exchange now feels completely different than it did then. AI agents aren't just calculating anymore. They're writing code, analyzing documents, planning tasks, deciding what to do next on their own. METR found that the length of software tasks frontier agents can complete autonomously has historically doubled roughly every seven months, with signs of even faster progress through parts of 2024. That's where Ma's argument starts to buckle. For decades, technology automated what humans did. AI is starting to automate what we assumed required a human to think. And companies were already learning to create enormous value with almost no people before this wave even arrived. Instagram sold for $1 billion with 13 employees. WhatsApp sold for $19 billion with 55. Now picture what happens when a small team can direct hundreds of machines that never sleep, never take a salary, never need an office. The question was never just which jobs disappear. It's what happens to the money once fewer humans are needed to create it in the first place. That's the question behind 2028: The Economy Without Humans. Who gets the money when machines do the work?

    4837601.2K viewsView on X
  • Oct 5, 2026

    Eleven v4 is free on ElevenCreative until October 12 for Creator plans and above. Here's your guide to making the most of it and turning your scripts into ads that keep your audience hooked. https://t.co/HMmZNbmuxc

    569815125K viewsView on X
  • Oct 5, 2026

    https://t.co/VW8ItaYKh8

    140114.9K 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.

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Reading these numbers

A typical post picks up 91 interactions against 57K followers, an engagement rate of 0.159%. Posts are seen about 6.9K times each, and 1.31% of those impressions turn into an interaction. That is about 12.1% 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, though only 3% of days saw any activity at all. Most posts go out around 00:00 UTC, and Monday is the busiest day of the week. Of the 5 posts sampled, 60% carry an image or video and 60% link out. The account's strongest tracked post pulled 1.0K interactions, about 11x its own typical post. Only 5 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 Iris Hayes's engagement rate on X?
Iris Hayes (@irisneural) has an engagement rate of 0.159%, based on the median interactions across 5 original posts from the last 30 days against 57,329 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.159%, Iris Hayes sits above the 50th percentile of the 205,048 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 @irisneural have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @irisneural post?
Most posts go out around 00:00 UTC, and Monday is its busiest day, at roughly 1.47 posts per day across the measured window.

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