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Lookonchain engagement report

@lookonchain - 711K followers on X

Measured over 76 original posts from a 30-day window, last computed on October 2, 2026.

Engagement

Middle of its size range
Per follower
0.055%
of 711K followers
Per impression
0.55%
71K views on a typical post
Reach
10.0%
of its followers see a post
Typical post
392
interactions (median)
Saved
0.02%
14 bookmarks on a typical post
Posting rate
3/day
active 50% of days
Peak time
14:00 UTC
Wednesday

A typical post picks up 392 interactions against 711K followers, an engagement rate of 0.055%. Measured over 76 original posts, its engagement rate beats 61% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 71K times each, and 0.55% of those impressions turn into an interaction. That is about 10.0% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 14:00 UTC, and Wednesday is the busiest day of the week. Of the 76 posts sampled, 100% carry an image or video and 86% link out. The account's strongest tracked post pulled 3.4K interactions, about 8.7x its own typical post. Recurring topics include #binance, #ethereum, #bitcoin.

Measured over 76 original posts from a 30-day window, last computed on October 2, 2026. Recurring tags: #binance, #ethereum, #bitcoin.

Compared with accounts its own size

Lookonchain's engagement rate beats 61% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 33% 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 0.055%, Lookonchain sits above the 25th percentile of the 204,798 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 204,798 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,879 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 14:00 UTC, and Wednesday 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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
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 link86% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 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.
  • 86% 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 231 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

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

  • Jan 5, 20258.7x their median

    What a smart #AI coin trader! Profits exceeded $5.14M on $GOAT. Profits exceeded $4.5M on $ai16z. Profits exceeded $4M on $Fartcoin. Profits exceeded $4M on $arc. Let’s take a look at which tokens he is buying. 1/ A thread🧵 https://t.co/UkD36wuH6Z

    2.6K530276341.2M viewsView on X
  • Aug 22, 20266.2x their median

    Machi(@machibigbrother), who has been liquidated nearly 500 times, turned just $152K into $12.72M in only 3 days, making a profit of over $12.5M! Looks like he doesn't need to sell his Bored Apes to keep his longs going anymore. https://t.co/mQLVsDGoSP https://t.co/EpJXACA9GV

    2.0K14318095619K viewsView on X
  • Aug 18, 20263.6x their median

    Smart #Solana whale (GvHYQQ) bought another 47,535 $SOL($3.6M) after over 2 years of inactivity. The whale perfectly bought the dip in August and October 2023, buying 291,790 $SOL ($6.82M) at an average price of just $23.37. Then $SOL started to skyrocket. As $SOL surged, the whale took profit by selling 191,789 $SOL ($24.62M) at an average price of $128.36, making over $20M in realized profit. Now, after 2 years of inactivity, the whale is buying the $SOL dip again. https://t.co/7UlLjOA5hk

    1.2K1267327232K viewsView on X
  • Aug 20, 20263.0x their median

    What a coincidence! 13 hours ago, a whale created a new wallet (0xedcd), deposited 20M $USDC into Hyperliquid, and opened a 4x long on 20,000 $ETH($45.38M). Shortly after he opened the position, $ETH started surging. He is now sitting on an unrealized profit of $6.66M. https://t.co/q60hDVdWQk

    1.0K627922251K viewsView on X
  • Sep 12, 20262.9x their median

    Pump fun(@Pumpfun) sold another 77,705 $SOL ($7.88M) 6 hours ago. In total, https://t.co/TcwYRTArT2 has sold 5,188,629 $SOL ($842M) at an average price of $162.3. https://t.co/kyztoJLCjt https://t.co/9K7jprKuxy

    8446613777230K viewsView on X
  • Sep 1, 20262.7x their median

    This guy must be feeling terrible right now. A month ago, he spent 181 $ETH ($443K) to buy 7.99M ethereum:0x07f5b6823751c2e2cd4560f28af75ff887102241. After the price dropped, he sold all 7.99M ethereum:0x07f5b6823751c2e2cd4560f28af75ff887102241 for 135K solana:2u1tszSeqZ3qBWF3uNGPFc8TzMk2tdiwknnRMWGWjGWH, taking a $308K loss. Those 7.99M ethereum:0x07f5b6823751c2e2cd4560f28af75ff887102241 are now worth $3.46M — he would've made over $3M if he had held! https://t.co/aRMshTWpve

    881529122224K viewsView on X
  • Sep 5, 20262.6x their median

    loracle.hl(@loraclexyz), who lost $70M on $HYPE, keeps adding to his $PONS short. He is now short 17.79M $PONS($16.31M), with an unrealized loss of $6.57M. https://t.co/LGxIJ77eMt https://t.co/XlYnIp5x6z

    8365510539276K viewsView on X
  • Sep 6, 20262.5x their median

    Unipcs(@theunipcs)' 10.9M $PONS is now worth over $10.27M! He initially invested just $67.7K to buy 10.9M $PONS and is now sitting on a massive $10.15M unrealized profit — a 150x return! https://t.co/0G2gsAtrDZ https://t.co/AkPM2J9oYX

    866365711121K viewsView on X
  • Sep 10, 20262.4x their median

    Someone still hasn't given up on $LAPTOP. After $LAPTOP crashed 98%, this guy spent $170K to "buy the dip," buying 28,448.72 $LAPTOP at $5.97. It's now worth just $21K — down another 87%. https://t.co/MduOcPiaz6 https://t.co/g0tSR3okzj

    7734511026109K viewsView on X
  • Sep 9, 20262.4x their median

    Wintermute received 2.5M $LAPTOP from the Laptop Token team and is now dumping it on-chain. So far, Wintermute has sold 466,255 $LAPTOP ($2.08M) at an average price of $4.47. https://t.co/Dhh7ZfDOuu https://t.co/At9EgpLVSf

    751618147140K 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

#binance#ethereum#bitcoin#gate#bybit

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 392 interactions against 711K followers, an engagement rate of 0.055%. Measured over 76 original posts, its engagement rate beats 61% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 71K times each, and 0.55% of those impressions turn into an interaction. That is about 10.0% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 14:00 UTC, and Wednesday is the busiest day of the week. Of the 76 posts sampled, 100% carry an image or video and 86% link out. The account's strongest tracked post pulled 3.4K interactions, about 8.7x its own typical post. Recurring topics include #binance, #ethereum, #bitcoin.

What is Lookonchain's engagement rate on X?
Lookonchain (@lookonchain) has an engagement rate of 0.055%, based on the median interactions across 76 original posts from the last 30 days against 711,419 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.055%, Lookonchain sits above the 25th percentile of the 204,798 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 @lookonchain have real engagement?
Its engagement rate beats 61% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range 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 @lookonchain post?
Most posts go out around 14:00 UTC, and Wednesday is its busiest day, at roughly 3 posts per day across the measured window.

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