SCOTTY BEAM engagement report
@ScottyBeamIO - 78K followers on X
Measured over 2 original posts from a 30-day window, last computed on October 15, 2026.
Engagement
Early reading. We have captured 2 original posts 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 210 interactions against 78K followers, an engagement rate of 0.271%. Posts are seen about 193K times each, and 0.109% of those impressions turn into an interaction. That is about 246.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.8 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 18:00 UTC, and Thursday is the busiest day of the week. Of the 2 posts sampled, 100% link out. The account's strongest tracked post pulled 1.1K interactions, about 11x its own typical post. Only 2 original posts 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 2 original posts from a 30-day window, last computed on October 15, 2026.
Where this sits in the catalog
At 0.271%, SCOTTY BEAM sits above the 50th percentile of the 204,956 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 18:00 UTC, and Thursday 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 | 0% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | -3% | -3% to -2% | 54K |
- 0% 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 127 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
- Jun 16, 202611x their median
https://t.co/rua4N4akAh
- Jul 22, 20262.2x their median
https://t.co/DhszHZLFGk
- Sep 1, 20261.9x their median
https://t.co/UnzJtqTMTi
- Oct 8, 2026
Grok Bot just got a MASSIVE upgrade – starting at $20/month. It's own email. Smarter agents. Better coding tools. Tasks straight from X. Set it up once. Give it a goal. Let it keep working while you sleep. https://t.co/WBKWI5K5gx
- Sep 18, 2026
https://t.co/1zlRUMg2Z9
- Jul 30, 2026
https://t.co/sgDl2xBLQs
- Jul 30, 2026
https://t.co/PgwTlyjqP8
- Aug 9, 2026
ONE ROBOT JUST HANDLED A $25,000-A-MONTH PIZZA KITCHEN WORKFLOW – WITHOUT A SALARY, BREAKS OR OVERTIME A pizza restaurant doesn't just pay someone to make pizza. It pays for someone to prep ingredients, spread the sauce, add toppings, operate the oven, slice the pizza, box it – and do it again hundreds of times a day. Now watch this clip. The humanoid robot handles the entire process from start to finish. Sauce. Toppings. Oven. Slicing. Boxing. Serving. No human input. Just one machine repeating the same workflow with consistent movements. And that's where this gets interesting. A kitchen worker might spend 8 hours doing essentially the same sequence over and over again. The robot doesn't get tired halfway through a dinner rush. It doesn't need a smoke break. It doesn't call in sick. And it doesn't care if the 50th pizza looks exactly like the first. The honest catch: this is still a controlled demonstration. A real restaurant kitchen is chaotic – orders change, ingredients run out, customers ask for modifications, ovens behave differently, and someone eventually drops an entire tray of dough on the floor. The robot isn't replacing an entire kitchen tomorrow. It doesn't have to. If one machine can eventually handle even 30% of the repetitive kitchen workload, restaurants could serve more orders with fewer labor hours. Now multiply that across thousands of restaurants, delivery hubs and cloud kitchens. The global pizza market alone is worth tens of billions of dollars. And the robot doesn't need to make the world's best pizza. It just needs to make the same pizza, at the same quality, hundreds of times a day. That's when food automation stops being a cool demo. And starts becoming a business model.
- Aug 9, 2026
THIS ROBOT JUST TOOK A $50,000-A-YEAR PACKAGE-SORTING JOB AND IT DOESN’T NEED A SALARY, BREAKS OR OVERTIME The video shows a humanoid robot working inside a parcel sorting center, picking up packages and sorting them on the conveyor just like a human employee. But instead of ignoring it, every worker around it pulled out their phone. They couldn’t look away. And honestly, it’s easy to see why. The robot doesn’t need coffee breaks, sick days, weekends, or overtime. It can keep sorting packages for hours while a human worker eventually gets tired and slows down. Now think about the economics. If one robot could eventually replace even one $40–50K annual position, a company could save hundreds of thousands of dollars over several years. Put 10 robots in a warehouse? That’s potentially $400K–$500K+ in annual labor costs before even accounting for payroll taxes, benefits and turnover. The catch? This is still a demonstration. Real warehouses are messy. Packages come in different shapes, sizes and weights, and robots still struggle with unpredictable situations. But that’s not the point. The point is that a machine can already perform one of the most repetitive jobs in the logistics industry using the same physical environment as human workers. And unlike humans, it can keep doing the same motion thousands of times without getting bored or exhausted. The workers filming it aren’t just watching a robot. They’re watching what their workplace could look like in 5 years.
- Aug 11, 2026
THE CREATOR OF THE MOST TERRIFYING ROBOT ONLINE SAYS HE MADE IT LOOK LIKE A NIGHTMARE ON PURPOSE – "IF YOU DON'T KNOW WHAT IT IS, STAY AWAY FROM IT" Meet 3Halves, built by Satyress Robotics – a two-person team – for the most dangerous job that exists in wildfire country: brush clearing and forestry work near active fire lines. The design looks unsettling on purpose. Half goat, half horse, half person, according to its own creator. And that's intentional – he built it to look dangerous specifically so people instinctively keep their distance from something that's heavy, unstable, and potentially armed with a chainsaw attachment. It's not autonomous. It's fully controlled by a human with an Xbox-style controller – the robot goes into the danger zone so the person doesn't have to. The trees it's clearing aren't random. They're dead trees that could fall across a fire line, trees near power lines, trees already damaged and unstable – exactly the kind of job where human injuries and deaths actually happen during wildfire season. The creator put the site up almost two years ago with barely any attention. One post on X later, it nearly crashed his own website from the traffic. This is what happens when a two-person team builds something for a real problem instead of a demo reel. Bookmark this, you'll want to come back to it later.
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 210 interactions against 78K followers, an engagement rate of 0.271%. Posts are seen about 193K times each, and 0.109% of those impressions turn into an interaction. That is about 246.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.8 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 18:00 UTC, and Thursday is the busiest day of the week. Of the 2 posts sampled, 100% link out. The account's strongest tracked post pulled 1.1K interactions, about 11x its own typical post. Only 2 original posts 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 SCOTTY BEAM's engagement rate on X?
- SCOTTY BEAM (@ScottyBeamIO) has an engagement rate of 0.271%, based on the median interactions across 2 original posts from the last 30 days against 78,170 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.271%, SCOTTY BEAM sits above the 50th percentile of the 204,956 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 @ScottyBeamIO have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @ScottyBeamIO post?
- Most posts go out around 18:00 UTC, and Thursday is its busiest day, at roughly 0.8 posts per day across the measured window.