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pod2g engagement report

@pod2g - 292K followers on X

Measured over 1 original post from a 30-day window, last computed on September 19, 2026.

Engagement

Per follower
0.003%
of 292K followers
Per impression
0.135%
7.4K views on a typical post
Reach
2.53%
of its followers see a post
Typical post
10
interactions (median)
Saved
0.013%
1 bookmarks on a typical post
Posting rate
0.07/day
active 3% of days
Peak time
01:00 UTC
Friday

Early reading. We have captured 1 original post 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 10 interactions against 292K followers, an engagement rate of 0.003%. Posts are seen about 7.4K times each, and 0.135% of those impressions turn into an interaction. That is about 2.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.07 posts a day over the last 30 days, though only 3% of days saw any activity at all. Most posts go out around 01:00 UTC, and Friday is the busiest day of the week. Of the 1 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 446 interactions, about 45x its own typical post. Only 1 original post 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 1 original post from a 30-day window, last computed on September 19, 2026.

Where this sits in the catalog

At 0.003%, pod2g sits above the 10th percentile of the 156,711 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.

p100.003%
p250.022%
p50 (median)0.127%
p750.604%
p902.32%
p9983.5%
Engagement rate as a share of followers, across the 156,711 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 26,082 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 percentile0.003%
25th percentile0.022%
50th percentile0.127%
75th percentile0.604%
90th percentile2.32%
99th percentile83.5%

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 01:00 UTC, and Friday 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: 01:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 01:00 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: Friday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Friday
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 280 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

  • Nov 29, 201745x their median

    Seriously, the quality of macOS High Sierra is a shame. I really don’t understand how that root login without a password story could happen. Especially when you consider all the good security engineering around (SEP, code signing, sandbox, entitlements). I feel sad.

    299121224View on X
  • Oct 17, 202228x their median

    Quick summary of my perception of the iOS world after Hexacon. Apple’s SEAR team has done a tremendous work over the last couple of years, to the point that many of my iOS fellow senior researchers have moved to Android (for this reason). [1/3]

    2264362View on X
  • Sep 9, 201527x their median

    I have no idea why some people complain about the Apple Keynote. Come on! 3 new products released! Awesomeness.

    135105340View on X
  • Nov 16, 201817x their median

    Hey! I’m at the @GrehackConf today. Any iOS security researcher would like to meet? We could share some thoughts! :)

    11515323View on X
  • Oct 21, 202415x their median

    We are excited to welcome Yarden Shafir (@yarden_shafir ) to the team!!!

    13645261K viewsView on X
  • Oct 3, 202213x their median

    Today I am thrilled to announce that I am joining @mdowd and @amatcama at @vigilant_labs! Super excited to do state-of-the-art research with the team! 👨‍🔬💻🎆

    1057153View on X
  • Nov 29, 201712x their median

    I absolutely don’t think the last High Sierra bug is a backdoor or intentional (responding to some comments on my previous tweet). It is just a mistake illustrating the complexity of maintaining such a huge software code base. Anytime you change anything you may introduce bugs.

    7930105View on X
  • Jun 21, 201512x their median

    Battery % of the iPhone on the watch is so convenient that Apple could have made it. @Surenix' http://t.co/HokeR8dt2i http://t.co/M7Di98jnQ2

    704370View on X
  • May 22, 201611x their median

    Cool! Just saw @DJQbert at Maker Faire. Q-bert and friends are performing live the whole afternoon! https://t.co/H5LHBjfsPx

    911560View on X
  • Apr 22, 202510x their median

    Today I am thrilled to join Epsilon Cyber SL ( @epsilon_sec ) as VP of Research. Excited to collaborate with an amazing team on groundbreaking cyber security projects!

    9643125K 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 10 interactions against 292K followers, an engagement rate of 0.003%. Posts are seen about 7.4K times each, and 0.135% of those impressions turn into an interaction. That is about 2.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.07 posts a day over the last 30 days, though only 3% of days saw any activity at all. Most posts go out around 01:00 UTC, and Friday is the busiest day of the week. Of the 1 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 446 interactions, about 45x its own typical post. Only 1 original post 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 pod2g's engagement rate on X?
pod2g (@pod2g) has an engagement rate of 0.003%, based on the median interactions across 1 original posts from the last 30 days against 292,302 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.003%, pod2g sits above the 10th percentile of the 156,711 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 @pod2g have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @pod2g post?
Most posts go out around 01:00 UTC, and Friday is its busiest day, at roughly 0.07 posts per day across the measured window.

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