Back to @annewoj23's profile

Anne Wojcicki engagement report

@annewoj23 - 440K followers on X

Measured over 1 original post from a 30-day window, last computed on September 28, 2026.

Engagement

Per follower
0.017%
of 440K followers
Per impression
0.454%
16K views on a typical post
Reach
3.65%
of its followers see a post
Typical post
71
interactions (median)
Saved
0.122%
19 bookmarks on a typical post
Posting rate
0.23/day
active 10% of days
Peak time
15:00 UTC
Sunday

Early reading. We have captured 1 original post 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 71 interactions against 440K followers, an engagement rate of 0.017%. Posts are seen about 16K times each, and 0.454% of those impressions turn into an interaction. That is about 3.55% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.23 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 15:00 UTC, and Sunday is the busiest day of the week. Of the 1 posts sampled, 100% link out. The account's strongest tracked post pulled 11K interactions, about 154x its own typical post. Only 1 original post 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 1 original post from a 30-day window, last computed on September 28, 2026.

Where this sits in the catalog

At 0.017%, Anne Wojcicki sits above the 10th percentile of the 213,282 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.

p100.004%
p250.025%
p50 (median)0.147%
p750.698%
p902.61%
p9982.9%
Engagement rate as a share of followers, across the 213,282 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,403 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 percentile0.004%
25th percentile0.025%
50th percentile0.147%
75th percentile0.698%
90th percentile2.61%
99th percentile82.9%

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 15:00 UTC, and Sunday 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: 15:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 15:00 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: Sunday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Sunday
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 video0% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 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 215 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

  • Apr 17, 2026154x their median

    I'm lucky enough to have a great doctor and access to excellent Bay Area medical care. I've taken lots of standard screening tests over the years and have tried lots of "health tech" devices and tools. With all this said, by far the most useful preventative medical advice that I've ever received has come from unleashing coding agents on my genome, having them investigate my specific mutations, and having them recommend specific follow-on tests and treatments. Population averages are population averages, but we ourselves are not averages. For example, it turns out that I probably have a 30x(!) higher-than-average predisposition to melanoma. Fortunately, there are both specific supplements that help counteract the particular mutations I have, and of course I can significantly dial up my screening frequency. So, this is very useful to know. I don't know exactly how much the analysis cost, but probably less than $100. Sequencing my genome cost a few hundred dollars. (One often sees papers and articles claiming that models aren't very good at medical reasoning. These analyses are usually based on employing several-year-old models, which is a kind of ludicrous malpractice. It is true that you still have to carefully monitor the agents' reasoning, and they do on occasion jump to conclusions or skip steps, requiring some nudging and re-steering. But, overall, they are almost literally infinitely better for this kind of work than what one can otherwise obtain today.) There are still lots of questions about how this will diffuse and get adopted, but it seems very clear that medical practice is about to improve enormously. Exciting times!

    9.6K6284752294.1M viewsView on X
  • Sep 6, 2025

    1/ Last year, I lost my sister Susan to lung cancer. Lung cancer in people who never smoked is the 5th leading cause of cancer globally. It kills more people than breast, colon, and prostate cancer combined. Today at 23andMe, we’re announcing steps to accelerate breakthroughs:

    787656817584K viewsView on X
  • Apr 9, 202610x their median

    Every mammogram should be supported by 3 different AIs for improved detection of cancer, prevention, and risk of heart disease. At no cost to patients. My new @TheLancet essay reviews the evidence and the lack of implementation https://t.co/AslAZroL73 https://t.co/znfjtV04HB

    53515913969K viewsView on X
  • Apr 8, 20264.6x their median

    Delighted to share our latest research from the @23andMeResearch Team, just published in @Nature ! We looked at data from >27,000 participants to uncover how human genetics influences weight loss efficacy and side effects of GLP-1 medications like semaglutide. A thread 🧵👇

    23766141061K viewsView on X
  • Apr 30, 20262.8x their median

    Craig Venter always kept me on my toes. From the earliest days of @23andMe till conversations last month, he was full of excitement about the potential of understanding the human genome and the ways it would benefit society. What a legacy. 🧬🧬 https://t.co/mGtXpFiTH3

    169247215K viewsView on X
  • May 12, 2026

    Carrying out Susan’s mission is an important initiative for our family. Susan was shocked when she learned she had lung cancer and even more surprised to learn that it’s the number one cancer killer. https://t.co/hbiXgsHQ3L

    66113413K viewsView on X
  • Feb 10, 2026

    In my 52 years I have never had twins in my eggs! Anyone else see this before? https://t.co/2E8gwbB1Iy

    5022839.5K viewsView on X
  • Sep 20, 2026

    “This mutation is so rare that we weren’t able to get population-level risk estimates without the size of a database like that from 23andMe.” - Dr. LoPiccolo at Dana Farber Cancer Institute https://t.co/hKw7ynPM6u

    5963316K viewsView on X
  • May 12, 2026

    https://t.co/tOb5U8HuIW

    49146110K viewsView on X
  • Oct 28, 2025

    Delighted to see our method, PRSformer, at #NeurIPS2025! PRSformer is AI model for population-scale disease-risk prediction from individual genomes. It lays the groundwork for phenome-wide risk prediction. https://t.co/LqlbOwzfuO

    4810218.0K 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.

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 71 interactions against 440K followers, an engagement rate of 0.017%. Posts are seen about 16K times each, and 0.454% of those impressions turn into an interaction. That is about 3.55% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.23 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 15:00 UTC, and Sunday is the busiest day of the week. Of the 1 posts sampled, 100% link out. The account's strongest tracked post pulled 11K interactions, about 154x its own typical post. Only 1 original post 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 Anne Wojcicki's engagement rate on X?
Anne Wojcicki (@annewoj23) has an engagement rate of 0.017%, based on the median interactions across 1 original posts from the last 30 days against 440,472 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.017%, Anne Wojcicki sits above the 10th percentile of the 213,282 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 @annewoj23 have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @annewoj23 post?
Most posts go out around 15:00 UTC, and Sunday is its busiest day, at roughly 0.23 posts per day across the measured window.

Keep going