marissamayer engagement report
@marissamayer - 1.3M followers on X
Measured over 23 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 36 interactions against 1.3M followers, an engagement rate of 0.003%. Posts are seen about 24K times each, and 0.149% of those impressions turn into an interaction. That is about 1.83% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 7.8 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 17:00 UTC, and Tuesday is the busiest day of the week. Of the 23 posts sampled, 70% carry an image or video, 13% are part of a thread and 48% link out. The account's strongest tracked post pulled 21K interactions. Recurring topics include #fortunempw, #fortunedaily, #iwasdazzled.
Measured over 23 original posts from a 30-day window, last computed on October 25, 2026. Recurring tags: #fortunempw, #fortunedaily, #iwasdazzled.
Where this sits in the catalog
At 0.003%, marissamayer sits below the 10th percentile of the 204,424 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 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 17:00 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 | 70% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 48% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 70% 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.
- 48% 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 289 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
- Feb 4, 2026
Our Q4/FY’25 results are in. Thanks to our partners & employees, it was a tremendous quarter, exceeding $400B in annual revenue for the first time. Our full AI stack is fueling our progress, and Gemini 3 adoption has been faster than any other model in our history. We’re really well positioned and excited going into 2026. Much more to come!
- Jan 15, 2025
New randomized, controlled trial of students using GPT-4 as a tutor in Nigeria. 6 weeks of after-school AI tutoring = 2 years of typical learning gains, outperforming 80% of other educational interventions. And it helped all students, especially girls who were initially behind https://t.co/abE1JMUBEs
- Mar 14, 2025
You can start your party at 6 pm instead of 9 pm and be just as cool.
- Jan 28, 2025
I think the Deepseek moment is not really the Sputnik moment, but more like the Google moment. If anyone was around in ~2004, you'll know what I mean, but more on that later. I think everyone is over-rotated on this because Deepseek came out of China. Let me try to un-rotate you. Deepseek could have come out of some lab in the US Midwest. Like say some CS lab couldn't afford the latest nVidia chips and had to use older hardware, but they had a great algo and systems department, and they found a bunch of optimizations and trained a model for a few million dollars and lo, the model is roughly on par with o1. Look everyone, we found a new training method and we optimized a bunch of algorithms! Everyone is like OH WOW and starts trying the same thing. Great week for AI advancement! No need for US markets to lose a trillion in market cap. The tech world (and apparently Wall Street) is massively over-rotated on this because it came out of CHINA. I get it. After everyone has been sensitized over the H1BLM uproar, we are conditioned to think of OMG Immigrants China as some kind of Alien Other. As though the Alien-Other Chinese Researchers are doing something special that's out of reach and now China The Empire is somehow uniquely in possession of Super Efficient AI Power and the US companies can't compete. The subtext of "A New Fearsome Power Now Under The Command of the CCP" is what's driving the current sentiment, and it's not really valid. Like, no. These are guys basically working on the same problems we are in the US, and not only that, they wrote a paper about it and open-sourced their model! It is not actually some sort of tectonic geopolitical shift, it is just Some Nerds Over There saying "Hey we figured out some cool shit, here's how we did it, maybe you would like to check it out?" Sputnik showed that the Soviets could do something the US couldn't ("a new fearsome power"). They didn't subsequently publish all the technical details and half the blueprints. They only showed that it could be done. With Deepseek, if I recall correctly, a lab in Berkeley read their paper and duplicated the claimed results on a small scale within a day. That's why I say it's like the Google moment in 2004. Google filed its S-1 in 2004, and revealed to the world that they had built the largest supercomputer cluster by using distributed algorithms to network together commodity computers at the best performance-per-dollar point on the cost curve. This was in contrast to every other tech company, who at that time just bought what were essentially larger and larger mainframes, always at the most expensive leading edge of the cost curve. (To the young people reading this, this will sound incredible to you) I worked at PayPal at the time, and in order to keep pace with the rising transaction volume, the company was forced to buy bigger and bigger database servers from Oracle. We were totally Oracle's bitch. At one point when we ran into scalability issues, the Oracle reps told us we were their biggest installation so they had no other reference point on how to help us overcome our scalability issues. We literally resorted to flipping random config switches and rebooting it. (This heavily influenced me when I was a young manager later at Facebook. I deliberately torpedoed an Oracle salesman's pitch to try and get us to switch from open source MySQL databases to an Oracle contract: of course we had scalability problems, but at least when we had them, we could open up the hood and figure out how to fix it ... assuming we had good enough engineers, and we did. When it's closed-source infra, you're at the mercy of the vendor's support engineers) Back to Google - in their S-1, they described how they were able to leapfrog the scalability limits of mainframes and had been (for years!) running a far more massive networked supercomputer comprised of thousands of commodity machines at the optimal performance-per-dollar price point - i.e. not the more expensive leading edge - all knit together by fault-tolerant distributed algorithms written in-house. Some time later, Google published their MapReduce and BigTable papers, describing the algorithms they'd used to manage and control this massively more cost-effective and powerful supercomputer. Deepseek is MUCH more like the Google moment, because Google essentially described what it did and told everyone else how they could do it too. In Google's case, a fair bit of time elapsed between when they revealed to the world what they were doing and when they published a papers showing everyone how to do it. Deepseek, in contrast, published their paper alongside the model release. Now, I've also written about how I think this is also a demonstration of Deepseek's trajectory, but that's also no different from Google in ~2004 revealing what it was capable of. Competitors will still need to gear up and DO the thing, but they've moved the field forward. But it's not like Sputnik where the Soviets have developed technology unreachable to the US, it's more like Google saying, "Hey, we did this cool thing, here's how we did it." There is no reason to think nVidia and OAI and Meta and Microsoft and Google et al are dead. Sure, Deepseek is a new and formidable upstart, but doesn't that happen every week in the world of AI? I am sure that Sam and Zuck, backed by the power of Satya, can figure something out. Everyone is going to duplicate this feat in a few months and everything just got cheaper. The only real consequence is that AI utopia/doom is now closer than ever. ==== Bonus: This is also a little similar the Ethereum PoS moment, when AI finally has a counterpoint to the environmentalists who say AI uses so much electricity. We just brought down the cost of inference by 97%!
- Apr 18, 2025
A British couple we know visited SF this past week. They like to walk, and walked all over the city. They said it seemed cleaner and safer than London. So while there is still work to do, SF is now definitely fine to visit. If you feel like visiting the US, that is.
- Mar 4, 2025
We probably don’t realize that robotic capabilities have just exploded overnight https://t.co/b8ovGsnrnZ
- Apr 27, 2025453x their median
https://t.co/svUgwti9q3
- Oct 20, 202641x their median
No one changes the world alone Introducing Ampersand - the first model built for us. Ampersand is a collaborator trained to help people achieve their individual and collective goals. In multi-month simulations, users collaborating with Ampersand accomplished more than with Fable and other frontier models Available to everyone through our API
- Mar 5, 2025
Digg: Old Rivals, New Vision Sign up to get early access when invites go live. Link in profile. https://t.co/o8gJwgPquh
- Oct 22, 202616x their median
Introducing Boba - the social intelligence that understands your goals and your community. Text Boba today or message it online at https://t.co/ZrF5yBrp2g https://t.co/zpyIAEVwqL
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 36 interactions against 1.3M followers, an engagement rate of 0.003%. Posts are seen about 24K times each, and 0.149% of those impressions turn into an interaction. That is about 1.83% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 7.8 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 17:00 UTC, and Tuesday is the busiest day of the week. Of the 23 posts sampled, 70% carry an image or video, 13% are part of a thread and 48% link out. The account's strongest tracked post pulled 21K interactions. Recurring topics include #fortunempw, #fortunedaily, #iwasdazzled.
- What is marissamayer's engagement rate on X?
- marissamayer (@marissamayer) has an engagement rate of 0.003%, based on the median interactions across 23 original posts from the last 30 days against 1,322,313 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.003%, marissamayer sits below the 10th percentile of the 204,424 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 @marissamayer have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @marissamayer post?
- Most posts go out around 17:00 UTC, and Tuesday is its busiest day, at roughly 7.8 posts per day across the measured window.