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Tammy Bruce engagement report

@HeyTammyBruce - 749K followers on X

Measured over 3 original posts from a 30-day window, last computed on September 1, 2026.

Engagement

Per follower
0.613%
of 749K followers
Per impression
1.14%
404K views on a typical post
Reach
53.9%
of its followers see a post
Typical post
4.6K
interactions (median)
Saved
0.027%
108 bookmarks on a typical post
Posting rate
0.47/day
active 37% of days
Peak time
00:00 UTC
Sunday

Early reading. We have captured 3 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 4.6K interactions against 749K followers, an engagement rate of 0.613%. Posts are seen about 404K times each, and 1.14% of those impressions turn into an interaction. That is about 53.9% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 00:00 UTC, and Sunday is the busiest day of the week. Of the 3 posts sampled, 33% carry an image or video and 67% link out. The account's strongest tracked post pulled 45K interactions, about 9.8x its own typical post. Only 3 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 3 original posts from a 30-day window, last computed on September 1, 2026. Recurring tag: #ripdolly.

Where this sits in the catalog

At 0.613%, Tammy Bruce sits above the 75th percentile of the 66,536 accounts in this comparison. That places it in the top 25% band, which runs 0.5% to 2.09%.

p100.002%
p250.016%
p50 (median)0.1%
p750.5%
p902.09%
p99119.7%
Engagement rate as a share of followers, across the 66,536 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,995 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 percentile0.002%
25th percentile0.016%
50th percentile0.1%
75th percentile0.5%
90th percentile2.09%
99th percentile119.7%

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 00:00 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: 00:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 00:00 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 video33% of posts+111%+108% to +115%34K
Outbound link67% of posts-41%-42% to -40%32K
Typical length--3%-3% to -2%54K
  • 33% 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.
  • 67% 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 147 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

  • Jul 17, 20269.8x their median

    https://t.co/rbe5QvMOTG

    36K5.7K2.5K8052.1M viewsView on X
  • Jul 17, 20265.7x their median

    When you picked him back up and he told you off. Little one had alot to say about being put down.. https://t.co/jBaNAxBjJO

    23K2.2K211183653K viewsView on X
  • Jul 20, 20265.5x their median

    Army Pvt. Isabella Gonzales, 19, of Carrollton gave her life in service to this country, killed in action Friday during an Iranian strike in Jordan while supporting our troops abroad. Our prayers are with her family, her fellow soldiers, and all who serve in harm’s way. https://t.co/zn7yMfULgD

    21K2.9K1.6K206195K viewsView on X
  • Aug 9, 20264.0x their median

    🫡 https://t.co/DSAkkCyAHC

    15K2.1K821243629K viewsView on X
  • Jul 20, 20263.4x their median

    I’m so proud of our Nova team for flying incredible shows for FIFA this year. This is my favorite shot from our closing show in NYC this weekend. https://t.co/lix0Fc24XF

    13K1.4K735120385K viewsView on X
  • Jul 13, 20261.7x their median

    The biggest lesson I learned in intelligence had nothing to do with secrets. People often assume intelligence is about having access to classified information. It isn't. The best intel officers I worked with weren't successful because they knew more than everyone else. They were successful because they noticed the little things that others overlooked. Before the attacks on September 11th, there were clues. Before COVID became a global pandemic, there were clues. Before Russia invaded Ukraine, there were clues. Before the Taliban rapidly retook Afghanistan, there were clues. The problem wasn't that there was no information. The problem was that the information wasn't connected, prioritized, or ACTED upon. Good intelligence starts by asking different questions. What changed? What's missing? Why now? Who benefits? Those same questions matter just as much outside the intelligence world. Whether you're evaluating a news story, making a business decision, preparing for hurricane season, or simply trying to understand what's happening around you, the goal isn't to know everything. It's to recognize patterns before everyone else does. One unusual event rarely tells you much. But when several small indicators all begin pointing in the same direction, that's when you should pay attention. Your goal is not to predict the future, it's to reduce a surprise. The next time a major story breaks, don't immediately ask whether it's true or false. Ask: (1) What do we actually know? (2) What information is still missing? (3) Who benefits from this narrative? (4) Has something like this happened before? (5) What would change my mind? Most people consume information. Think like an analyst instead. The world doesn't need more opinions. It needs more people willing to slow down, ask better questions, and pay attention.

    6.3K1.2K292106232K viewsView on X
  • Aug 11, 2026

    My Op Ed in today's @washingtonpost on the courage of @BoyGeorge and the price of principle musicians currently pay for standing with the Jewish People and Civilization. (No firewall). 🇺🇸🇮🇱🌍👊https://t.co/SC8HHczwKS

    3.7K70918436404K viewsView on X
  • Jul 30, 2026

    This piece of Fauci's diary you would not believe. So pathetic. https://t.co/dlkeNOuJ8M

    2.7K59841189212K viewsView on X
  • Jul 19, 2026

    ❤️🇺🇸 🙏 American woman Dena Karari arrives back in US after being wrongfully detained by Iran for 566 days on spying charges https://t.co/63N1msutL4

    2.7K3016623K viewsView on X
  • Jul 12, 2026

    “YES SIR!” What a lucky boy to have a coach like this man. Doesn’t matter if you are tired. You push on through. AND you show your elders respect. Brilliant. 🥳 https://t.co/2GEa0RihBH

    2.3K187501393K 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.

Recurring topics

#ripdolly

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 4.6K interactions against 749K followers, an engagement rate of 0.613%. Posts are seen about 404K times each, and 1.14% of those impressions turn into an interaction. That is about 53.9% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 00:00 UTC, and Sunday is the busiest day of the week. Of the 3 posts sampled, 33% carry an image or video and 67% link out. The account's strongest tracked post pulled 45K interactions, about 9.8x its own typical post. Only 3 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 Tammy Bruce's engagement rate on X?
Tammy Bruce (@HeyTammyBruce) has an engagement rate of 0.613%, based on the median interactions across 3 original posts from the last 30 days against 748,520 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.613%, Tammy Bruce sits above the 75th percentile of the 66,536 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 @HeyTammyBruce have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @HeyTammyBruce post?
Most posts go out around 00:00 UTC, and Sunday is its busiest day, at roughly 0.47 posts per day across the measured window.

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