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Jason Elsom engagement report

@JasonElsom - 100K followers on X

Measured over 21 original posts from a 30-day window, last computed on August 21, 2026.

Engagement

Bottom 10% for its size
Per follower
0.005%
of 100K followers
Per impression
0.269%
1.9K views on a typical post
Reach
1.88%
of its followers see a post
Typical post
5
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
1.13/day
active 50% of days
Peak time
18:00 UTC
Sunday

A typical post picks up 5 interactions against 100K followers, an engagement rate of 0.005%. Measured over 21 original posts, its engagement rate beats 8% of 1,003 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 1.9K times each, and 0.269% of those impressions turn into an interaction. That is about 1.86% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 18:00 UTC, and Sunday is the busiest day of the week. Of the 21 posts sampled, 100% carry an image or video and 19% are part of a thread. The account's strongest tracked post pulled 101K interactions, about 20200x its own typical post. Recurring topics include #clearthelist, #british, #driving.

Measured over 21 original posts from a 30-day window, last computed on August 21, 2026. Recurring tags: #clearthelist, #british, #driving.

Compared with accounts its own size

Jason Elsom's engagement rate beats 8% of the tracked X accounts closest to it in follower count (1,003 accounts, accounts of similar size (decile 3 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 11% 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 0.005%, Jason Elsom sits above the 10th percentile of the 11,249 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.007%.

p100.001%
p250.007%
p50 (median)0.05%
p750.336%
p902.48%
p99322.2%
Engagement rate as a share of followers, across the 11,249 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 358,007 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 percentile0.001%
25th percentile0.007%
50th percentile0.05%
75th percentile0.336%
90th percentile2.48%
99th percentile322.2%

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 18:00 UTC, and Sunday 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: 18:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 96%Busiest hour: 18:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC0%15K
01:00 UTC+4%15K
02:00 UTC-1%14K
03:00 UTC-2%15K
04:00 UTC-5%12K
05:00 UTC-5%12K
06:00 UTC-7%13K
07:00 UTC-6%14K
08:00 UTC-7%17K
09:00 UTC-2%19K
10:00 UTC-2%20K
11:00 UTC-2%22K
12:00 UTC-1%24K
13:00 UTC+1%27K
14:00 UTC-2%29K
15:00 UTC-1%30K
16:00 UTC-1%30K
17:00 UTC-1%28K
18:00 UTC+1%25K
19:00 UTC0%24K
20:00 UTC0%22K
21:00 UTC+1%19K
22:00 UTC+1%17K
23:00 UTC+1%15K
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: Sunday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 96%Busiest day: Sunday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+8%59K
Monday+8%72K
Tuesday+1%94K
Wednesday-4%78K
Thursday-3%71K
Friday-5%73K
Saturday+2%64K
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+79%+73% to +85%5.8K
Outbound link5% of posts-49%-50% to -47%6.1K
Typical length--7%-8% to -5%9.0K
  • 100% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 79% above the same accounts' other posts.
  • 5% of its posts carry a link off X. Across the catalog, posts with an outbound link run 49% below the same accounts' other posts.
  • Its average post runs 165 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 7% below 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 18, 202620200x their median

    France vs. England match highlights.. https://t.co/oap5ygDuFq

    91K9.2K5244569.1M viewsView on X
  • Aug 19, 20262282x their median

    Outstanding marketing from Spark Car Wash… https://t.co/P7dE2fJo5S

    11K172277766K viewsView on X
  • Aug 14, 20261214x their median

    This is absolutely NOT what the #emergencyalert system is for! https://t.co/XiZ7pGlNMH

    5.3K175561711.2M viewsView on X
  • Aug 12, 202623x their median

    We grabbed an incredible spot to watch the solare eclipse! Only in England… https://t.co/r68GcXIiU6

    10912143K viewsView on X
  • Jul 15, 202616x their median

    A VITALLY IMPORTANT MESSAGE https://t.co/DUyk9z6cKV

    7190057K viewsView on X
  • Jul 9, 20268.6x their median

    Does anyone know where I can buy the same fan Queen Camilla is using? @AmazonUK @JohnLewisRetail @LidlGB @AldiUK perhaps? https://t.co/TRph2HFPjr

    28015019K viewsView on X
  • May 13, 20262.2x their median

    6M. That's how many times my websites were hit yesterday. >70% came from LLMs - ChatGPT, Claude, Perplexity, Gemini - reading content in real time. Not last month. Yesterday. A few months ago I checked the server logs out of curiosity. Most of the traffic wasn't human. Every LLM you've heard of was quietly consuming the content as fast as it could be published. And growing. Here's what nobody's saying out loud: The web was built for humans clicking links. The next web is being built for AI reading at scale. Every question you ask ChatGPT is answered by some piece of content that exists somewhere. The companies that own those pieces will own the answers. I've been quietly building one... WhatSchool - currently the world's largest cradle-to-grave education corpus. 138 nations. 2.4 billion data points. It's #1... The What* family is in production. More verticals. Each becoming the authoritative knowledge layer for its space. Each consumed by AI before humans even notice it exists. I'm not selling AI. I'm building the thing AI uses. If you want to watch a category get built in real time - wins, scars, and "wait, did that just work?" moments - follow along. Say What*.

    62301.4K viewsView on X
  • Aug 16, 20262.0x their median

    Do you agree or disagree #british #driving madness https://t.co/tWSKH83nQQ

    60313.9K viewsView on X
  • Jul 15, 20262.0x their median

    Interesting World Cup Data! https://t.co/2NUfWSbbyS

    7210664 viewsView on X
  • Aug 15, 20261.6x their median

    Wildfire map now live! Following this evening’s National Emergency Alert, we’ve built a live wildfire map showing major active and recently extinguished fires across the UK. It brings together satellite detections from NASA and other sources, with information on reported fire intensity, wind direction and potential proximity to populated areas. It’s still in testing and we’ll be refining it throughout the weekend — but you can explore it now: https://t.co/nsKjsqghXM #Wildfire #EmergencyAlert #UKWildfires #WildfireMap

    32303.1K 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

#clearthelist#british#driving#drought#eduprotocols

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 5 interactions against 100K followers, an engagement rate of 0.005%. Measured over 21 original posts, its engagement rate beats 8% of 1,003 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 1.9K times each, and 0.269% of those impressions turn into an interaction. That is about 1.86% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 18:00 UTC, and Sunday is the busiest day of the week. Of the 21 posts sampled, 100% carry an image or video and 19% are part of a thread. The account's strongest tracked post pulled 101K interactions, about 20200x its own typical post. Recurring topics include #clearthelist, #british, #driving.

What is Jason Elsom's engagement rate on X?
Jason Elsom (@JasonElsom) has an engagement rate of 0.005%, based on the median interactions across 21 original posts from the last 30 days against 99,852 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Jason Elsom sits above the 10th percentile of the 11,249 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 @JasonElsom have real engagement?
Its engagement rate beats 8% of the tracked X accounts closest to it in follower count (1,003 accounts), which puts it in the bottom 10% for its size 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 @JasonElsom post?
Most posts go out around 18:00 UTC, and Sunday is its busiest day, at roughly 1.13 posts per day across the measured window.

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