Glen Gilmore engagement report
@GlenGilmore - 268K followers on X
Measured over 30 original posts from a 30-day window, last computed on October 28, 2026.
Engagement
A typical post picks up 14 interactions against 268K followers, an engagement rate of 0.005%. Measured over 30 original posts, its engagement rate beats 17% of 21,185 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 530 times each, and 2.54% of those impressions turn into an interaction. That is about 0.197% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 05:00 UTC, and Wednesday is the busiest day of the week. Of the 30 posts sampled, 80% carry an image or video and 93% link out. The account's strongest tracked post pulled 3.4K interactions, about 241x its own typical post. Recurring topics include #blockchain, #fintech, #onchain.
Measured over 30 original posts from a 30-day window, last computed on October 28, 2026. Recurring tags: #blockchain, #fintech, #onchain.
Compared with accounts its own size
Glen Gilmore's engagement rate beats 17% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 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 69% 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%, Glen Gilmore sits above the 10th percentile of the 213,098 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.147% |
| 75th percentile | 0.698% |
| 90th percentile | 2.61% |
| 99th percentile | 82.9% |
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 05:00 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.
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 | 80% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 93% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 80% 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.
- 93% 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 214 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
- Sep 13, 2026241x their median
✨🇨🇳China's Xiaomi car—this feature is so cool! https://t.co/LpQv1FdwFW
- Oct 27, 2026111x their median
Today we’re out of stealth, and we’ve raised a $40m seed round co-led by @creandum and @usv, to bring Instant Robot Learning to life. For the past few months, we‘ve been busy building a new company. Machenta. This follows results from a new kind of robot foundation model we’ve built, which I’m so excited to share with you today! Usually, it takes hours/days of data collection and training to teach a robot. We’ve built a model that learns tasks instantly: one demonstration, no further training. A model trained entirely in simulation, without a single pixel of real-world data. A model where teaching robots is so quick and easy, it feels like physical vibe coding. A model for robots that learn like humans do, from someone like you. Welcome to the era of Instant Robot Learning. Thank you @Kathi_Wilhelm, @rebeccakaden, @hkanji, @jonno_evans and all of our angels for your support! @Machenta_ Learn more: https://t.co/P1woKrXtjH See below for what you can do with Instant Robot Learning!
- May 31, 202420x their median
INTERVIEW: “Sara.” An AI humanoid robot speaking 🗣️ on how to use #AIforGood: ✅ Advance health by improving medical diagnostics 🩺 🩻 #MedTech ✅ #ClimateAction by improving environmental shifts. ✅ #Education by personalizing learning 🎓 #edutech “The possibilities are endless.“ ⚠️ The challenges of AI? “We must address #Bias in algorithms, #DataPrivacy, and job displacement — but innovators worldwide are working on solutions.” @AIforGood GlobalSummit 🇺🇳 📍Geneva 🇨🇭 @ITU #SDGs 🤖 Creator @qltyss #KSA #Humanoid #Robotics #Robot #GenerativeAI #GenAI
- Sep 19, 20264.5x their median
Anthropic selects Accenture as first embedded evaluator to help implement Amodei's slowdown proposal “Anthropic announced it will embed Accenture employees within the company to help test the safety of its AI models.” https://t.co/jq0KB6SMlI https://t.co/dAOt8xQzqO
- Oct 11, 20264.3x their median
Denmark tests humanoid robots in supermarkets to help to ease staff workload at night https://t.co/0R5DCLlWKF @euronews AI workforce https://t.co/Dfp6xIIG8s
- Sep 14, 20263.6x their median
Plug-in solar "not an overnight proposition," says Australian energy minister Bowen, as pressure mounts to legalise it within 10 months “Germany has had over a million of these systems plugged in for years,” notes Glen Morris, who is a solar engineer and director of Smart Energy Lab, explaining that the path to safe plug-in solar is “not complicated.” “We do not need to invent anything. We need a product standard so the inverter shuts down instantly when unplugged, a cap of around 800 watts so it cannot overload a normal power circuit, and a simple registration with the network so they know it is there.” Thoughts? 😎 https://t.co/2F90D7zla4
- Sep 17, 20263.4x their median
Iran strikes on Amazon data centers caused permanent loss of customer data ““The damage to our infrastructure spanned multiple Availability Zones and exceeded what our regional and multi-AZ services are designed to withstand,” the AWS update said. https://t.co/VxKdSbJVjU https://t.co/jplVLJiJgJ
- Sep 5, 20263.4x their median
Agentic AI Is Here: Is Your Data Ready? https://t.co/4raOwVPlby AI. Governance https://t.co/2ok8kEKcLP
- Sep 17, 20263.3x their median
Anthropic CEO renews call for AI slowdown as Nvidia’s urges acceleration Huang argues that new regulations were not necessary, advising AI companies to simply wait to release products until they know they are safe rather than begging the US government to intervene. | AI governance https://t.co/mDXsdvyCT1
- Sep 18, 20262.6x their median
AI Governance Must Become a Strategic Pillar | @KPMG “To govern AI effectively, organisations should establish: A board-approved AI ambition and risk appetite. A value-led portfolio of AI initiatives with clear ownership and measurable outcomes. An enterprise-wide inventory of AI applications, models, data sources and third-party providers. Robust lifecycle controls covering data quality, security, testing, monitoring and incident response. Workforce policies, training and clear guidance on the responsible use of AI. https://t.co/zAG4P11xg1
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
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 14 interactions against 268K followers, an engagement rate of 0.005%. Measured over 30 original posts, its engagement rate beats 17% of 21,185 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 530 times each, and 2.54% of those impressions turn into an interaction. That is about 0.197% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 05:00 UTC, and Wednesday is the busiest day of the week. Of the 30 posts sampled, 80% carry an image or video and 93% link out. The account's strongest tracked post pulled 3.4K interactions, about 241x its own typical post. Recurring topics include #blockchain, #fintech, #onchain.
- What is Glen Gilmore's engagement rate on X?
- Glen Gilmore (@GlenGilmore) has an engagement rate of 0.005%, based on the median interactions across 30 original posts from the last 30 days against 268,445 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.005%, Glen Gilmore sits above the 10th percentile of the 213,098 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 @GlenGilmore have real engagement?
- Its engagement rate beats 17% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the bottom quarter 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 @GlenGilmore post?
- Most posts go out around 05:00 UTC, and Wednesday is its busiest day, at roughly 1.4 posts per day across the measured window.