ππππ πππ engagement report
@s_chan1992 - 1.3M followers on X
Measured over 23 original posts from a 30-day window, last computed on October 31, 2026.
Engagement
A typical post picks up 6.3K interactions against 1.3M followers, an engagement rate of 0.501%. Posts are seen about 273K times each, and 2.32% of those impressions turn into an interaction. That is about 21.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 02:00 UTC, and Friday is the busiest day of the week. Of the 23 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 67K interactions, about 12x its own typical post.
Measured over 23 original posts from a 30-day window, last computed on October 31, 2026.
Where this sits in the catalog
At 0.501%, ππππ πππ sits above the 50th percentile of the 218,281 accounts in this comparison. That places it in the above the median band, which runs 0.149% to 0.705%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.149% |
| 75th percentile | 0.705% |
| 90th percentile | 2.63% |
| 99th percentile | 82.5% |
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 02:00 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | -3% | -3% to -2% | 54K |
- 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 115 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 3% 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
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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 6.3K interactions against 1.3M followers, an engagement rate of 0.501%. Posts are seen about 273K times each, and 2.32% of those impressions turn into an interaction. That is about 21.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 02:00 UTC, and Friday is the busiest day of the week. Of the 23 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 67K interactions, about 12x its own typical post.
- What is ππππ πππ's engagement rate on X?
- ππππ πππ (@s_chan1992) has an engagement rate of 0.501%, based on the median interactions across 23 original posts from the last 30 days against 1,263,403 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.501%, ππππ πππ sits above the 50th percentile of the 218,281 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 @s_chan1992 have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @s_chan1992 post?
- Most posts go out around 02:00 UTC, and Friday is its busiest day, at roughly 0.93 posts per day across the measured window.