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Walrus engagement report

@WalrusProtocol - 369K followers on X

Measured over 15 original posts from a 30-day window, last computed on September 1, 2026.

Engagement

Middle of its size range
Per follower
0.017%
of 369K followers
Per impression
0.667%
9.3K views on a typical post
Reach
2.51%
of its followers see a post
Typical post
62
interactions (median)
Saved
0.011%
1 bookmarks on a typical post
Posting rate
2.6/day
active 40% of days
Peak time
14:00 UTC
Monday

A typical post picks up 62 interactions against 369K followers, an engagement rate of 0.017%. Measured over 15 original posts, its engagement rate beats 34% of 6,874 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 9.3K times each, and 0.667% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 15 posts sampled, 73% carry an image or video, 7% are part of a thread and 27% link out. The account's strongest tracked post pulled 2.3K interactions, about 37x its own typical post. Recurring topics include #walrusmemory, #walrus.

Measured over 15 original posts from a 30-day window, last computed on September 1, 2026. Recurring tags: #walrusmemory, #walrus.

Compared with accounts its own size

Walrus's engagement rate beats 34% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 8 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 37% 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 0.017%, Walrus sits above the 25th percentile of the 66,258 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.6%
Engagement rate as a share of followers, across the 66,258 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,968 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 percentile0.002%
25th percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile119.6%

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 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: 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: 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 video73% of posts+111%+108% to +115%34K
Outbound link27% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 73% 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.
  • 27% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 462 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

  • Aug 26, 202637x their median

    working with ai agents is like if all your employees had dementia

    2.0K1221052064K viewsView on X
  • Aug 28, 202619x their median

    I receive around 3-5 requests to test a new AI product daily. Almost all of them require creating a new account and logging into a separate website or app. Meanwhile, I basically only use ChatGPT, Grok, etc to do everything on my computer and browser. These harnesses already have all my context and I don't want to start over from scratch with a new website or tool that only understands a small slice of my data. So with a few exceptions, the new products that I'm mostly likely to adopt need to work in today's top AI harnesses. I realize only a small segment of users behave this way but I bet this segment will expand drastically soon.

    925402111182K viewsView on X
  • Aug 24, 20262.4x their median

    Moving your AI memory has never been more necessary. @kostascrypto @gazza_jenks on @theblockco. https://t.co/ssUV7ylVw5

    122188215K viewsView on X
  • Aug 10, 20262.3x their median

    🧵1/3: Claude Code's auto memory only lives on your machine, in one repo. Switch machines, or open Codex, and it starts from zero. You could commit it to your repo instead. Now it's a file everyone with repo access can read, and it still never leaves Claude Code.

    1071521122K viewsView on X
  • Aug 27, 20262.0x their median

    Live in Lagos @SuiHubAfrica: over 30 builders gathered in person to learn prompt design and build with Walrus Memory and context. Taking our online Prompt Jam 5 format offline, this session gives builders hands-on guidance to explore what is possible with portable agent memory. Looking forward to seeing what the teams build.

    951510211K viewsView on X
  • Sep 1, 20262.0x their median

    Around 4B paper documents circulate through the $25T global trade market, making document fraud a massive, systemic risk. @blockticity is changing that by bringing over 1M authenticated records ($7.7B+ in real-world assets) onto Walrus. By mirroring 15TB+ of trade evidence across five commercial verticals, Blockticity gives partners public, cryptographic proof of origin while keeping sensitive commercial data protected. Read the full announcement: https://t.co/U0fvb0Qzw0

    9717526.0K viewsView on X
  • Aug 21, 2026

    Most exam prep tools re-test material students already understand. Today's Prompt Jam spotlight: Exam Mistake Memory by @eazitechh, (@/eazitech1) on Github. Exam Mistake Memory tracks errors, pinpoints specific knowledge gaps, and generates targeted practice sessions based on past attempts. Explore the prompt: https://t.co/15kukEn0pi

    7663210K viewsView on X
  • Sep 1, 2026

    August brought verifiable AI trading, new Walrus Memory tutorials, and $WAL to 80M+ Revolut users. Here is everything that shipped: ⬛️ Launched the Walrus Verifiable Trading Standard with @Astros_ag to make market data machine-readable and auditable. ⬛️ Shipped three new tutorials for adding portable Walrus Memory across TypeScript SDK, Claude Code, and Claude Desktop. ⬛️ Published a 4-part deep dive breaking down agentic memory and context engineering. ⬛️ $WAL went live on @Revolut, expanding access to 80M+ users across 40+ countries. ⬛️ @KostasCryptos broke down verifiable infra on @TheBlockCo's Starting Block podcast and @ThePaypers. ⬛️ Rebuilt the Docs with product-first navigation across Walrus, Walrus Memory, and Walrus Sites. ⬛️ Catch us next month at @HumanXCo in Amsterdam, and grab your tickets for Sui Basecamp in Singapore (Oct 7–8). Need links to the events? Let us know in the comments and we can reshare them.

    458723.5K viewsView on X
  • Aug 20, 2026

    We're announcing Session Lagos: Walrus Memory x AI Prompt, a hands-on hackathon hosted at SuiHub. Participants will build an AI agent with real memory using Walrus Memory, then share the exact prompt so others can build the same thing. No coding or web3 background required. $300 WAL prize pool. 📍 SuiHub Lagos, 27th August 🕑 12:00 PM · Judging (virtual), 28th August

    3210933.1K viewsView on X
  • Sep 1, 2026

    Decentralized notes, stored on Walrus. Tune in tomorrow for our next Builder AMA featuring @Edcriptofi, Founder of @wal_notes. We'll be diving into how they use Walrus for storage and answering questions live. We're giving away exclusive merch for the best questions shared in our @discord [ama-questions] channel! 📅 Sept 2 @ 3 PM UTC 📍 Walrus Discord: https://t.co/4CrUUipBkL You'll want to bookmark this one.

    385724.4K 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

#walrusmemory#walrus

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.

Buy or sell X accounts - escrow-protected

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Reading these numbers

A typical post picks up 62 interactions against 369K followers, an engagement rate of 0.017%. Measured over 15 original posts, its engagement rate beats 34% of 6,874 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 9.3K times each, and 0.667% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 15 posts sampled, 73% carry an image or video, 7% are part of a thread and 27% link out. The account's strongest tracked post pulled 2.3K interactions, about 37x its own typical post. Recurring topics include #walrusmemory, #walrus.

What is Walrus's engagement rate on X?
Walrus (@WalrusProtocol) has an engagement rate of 0.017%, based on the median interactions across 15 original posts from the last 30 days against 368,500 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.017%, Walrus sits above the 25th percentile of the 66,258 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 @WalrusProtocol have real engagement?
Its engagement rate beats 34% of the tracked X accounts closest to it in follower count (6,874 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 @WalrusProtocol post?
Most posts go out around 14:00 UTC, and Monday is its busiest day, at roughly 2.6 posts per day across the measured window.

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