Maria Quinn engagement report
@Quinn_Codes - 79K followers on X
Measured over 28 original posts from a 30-day window, last computed on October 13, 2026.
Engagement
A typical post picks up 29 interactions against 79K followers, an engagement rate of 0.037%. Measured over 28 original posts, its engagement rate beats 32% 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 1.1K times each, and 2.53% of those impressions turn into an interaction. That is about 1.46% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.2 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 05:00 UTC, and Tuesday is the busiest day of the week. Of the 28 posts sampled, 89% carry an image or video and 39% are part of a thread. The account's strongest tracked post pulled 2.0K interactions, about 67x its own typical post.
Measured over 28 original posts from a 30-day window, last computed on October 13, 2026.
Compared with accounts its own size
Maria Quinn's engagement rate beats 32% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 6 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 67% 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 0.037%, Maria Quinn sits above the 25th percentile of the 205,676 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.679% |
| 90th percentile | 2.56% |
| 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 05:00 UTC, and Tuesday 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 | 89% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 0% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 89% 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.
- 0% 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 411 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
- Sep 27, 202667x their median
3 years of AI progress incredible. https://t.co/PGYF7vgYEA
- Sep 26, 202652x their median
Current AI tier rankings đ https://t.co/dyyrLs3UdI
- Jul 8, 202629x their median
Every company has specialized intelligence that sets it apart. With @langchain, weâre helping enterprises turn that knowledge into specialized agents they can customize, secure and improve over time. https://t.co/70dmvQsxY8
- Oct 13, 20267.8x their median
Robotics is finally moving from âlook what this robot can repeatâ to âlook what this robot can understand.â Nature Will is launching a foundation model named Natura-1 for the physical world, built to turn human instructions into real actions on real robots. The demo from @naturewill is worth watching closely. The hands tell the real story đ§”
- Sep 29, 20267.8x their median
Gemini 4 Pro benchmark scores after new leaked: https://t.co/ZQ9KTlZa3o
- Oct 2, 20266.6x their median
Sam Altman answered Elonâs âmoney wonât matter in 2036â statement Sam Altman: âClearly I think money will still matter in 10 years.â âOne of the greatest concerns I have with AI is the concentration of power and concentration of wealth.â âThere are all of these ways where I think it will make a lot of things much cheaper and better, and you donât have to buy a car, and thatâll be great.â âBut yeah, I think that there are many reasons to think that it wonât just magically solve wealth inequality.â
- Sep 30, 20266.3x their median
This was made by Al... this is Al slop... I'm speechless... Al is getting too advanced đ https://t.co/9j9kI8V50E
- Mar 30, 20262.1x their median
WILD: The first $1B company with 1 employee is inevitable. Not a team. Not a startup. One person. Running everything with AI. And itâs already starting. 𧔠https://t.co/aX9ySY1Tr0
- Aug 22, 20261.8x their median
I accidentally discovered how to compress a semester of learning into 48 hours. A grad student at MIT showed me his NotebookLM setup. I thought he was just organized. Then I watched him pass a qualifying exam on a subject he'd never studied before. Here's exactly what he did: First: he didn't upload a textbook. He uploaded 6 textbooks, 15 research papers, and every lecture transcript he could find on the subject. Then he asked NotebookLM one question: "What are the 5 core mental models that every expert in this field shares?" Not "summarize this." Not "explain this topic." Mental models. The stuff that takes professors years to develop. But the next part is what broke my brain. He followed up with: "Now show me the 3 places where experts in this field fundamentally disagree, and what each side's strongest argument is." In 20 minutes he had a map of the entire intellectual landscape of the field: the debates, the consensus, the open questions. Most students spend a full semester just figuring out what those debates even are. Then he did something I've never seen before. He asked: "Generate 10 questions that would expose whether someone deeply understands this subject versus someone who just memorized facts." He spent the next 6 hours answering those questions using the source material. Every wrong answer triggered a follow-up: "Explain why this is wrong and what I'm missing." By hour 48, he could hold a conversation with his thesis advisor without getting destroyed. The tool didn't change. The questions did. Most people treat NotebookLM like a fancy highlighter. These students are using it like a private tutor who has read everything ever written on the subject. The difference between a semester and 48 hours isn't the amount of content. It's knowing which questions to ask.
- Oct 5, 20261.6x their median
Sam Altman: the future of AI is a Renaissance, not an industrial revolution. "People often talk about AI as an industrial revolution." "The best part of AI is not about making people cogs in a machine." "I believe the future, if we get this right, can be more like a Renaissance than an industrial revolution." "AI should be about giving people more power in their lives."
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.
Buy or sell Twitter (X) accounts - escrow-protected
PlayerSells is an escrow marketplace for Twitter (X) accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 29 interactions against 79K followers, an engagement rate of 0.037%. Measured over 28 original posts, its engagement rate beats 32% 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 1.1K times each, and 2.53% of those impressions turn into an interaction. That is about 1.46% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.2 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 05:00 UTC, and Tuesday is the busiest day of the week. Of the 28 posts sampled, 89% carry an image or video and 39% are part of a thread. The account's strongest tracked post pulled 2.0K interactions, about 67x its own typical post.
- What is Maria Quinn's engagement rate on X?
- Maria Quinn (@Quinn_Codes) has an engagement rate of 0.037%, based on the median interactions across 28 original posts from the last 30 days against 78,538 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.037%, Maria Quinn sits above the 25th percentile of the 205,676 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 @Quinn_Codes have real engagement?
- Its engagement rate beats 32% 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 @Quinn_Codes post?
- Most posts go out around 05:00 UTC, and Tuesday is its busiest day, at roughly 2.2 posts per day across the measured window.