Bloomberg Originals engagement report
@bbgoriginals - 1.2M followers on X
Measured over 176 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 5 interactions against 1.2M followers, an engagement rate of 0%. Measured over 176 original posts, its engagement rate beats 6% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 6.6K times each, and 0.076% of those impressions turn into an interaction. That is about 0.555% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.3 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 21:00 UTC, and Friday is the busiest day of the week. Of the 176 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 59 interactions, about 12x its own typical post.
Measured over 176 original posts from a 30-day window, last computed on October 25, 2026.
Compared with accounts its own size
Bloomberg Originals's engagement rate beats 6% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 5% 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 under 0.001%, Bloomberg Originals sits below the 10th percentile of the 204,880 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 | 0.678% |
| 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 21:00 UTC, and Friday 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 | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 100% 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 276 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
- Sep 6, 202612x their median
Jeffrey Epstein built a network of elites across finance, politics and academia. By analyzing thousands of documents, Bloomberg mapped its reach and how it widened even as allegations against him accumulated https://t.co/mgZWijXvOT https://t.co/2nSh6d2JuD https://t.co/C2FwzJ2BFA
- Aug 16, 20268.6x their median
Jeffrey Epstein built a network of elites across finance, politics and academia. By analyzing thousands of documents, Bloomberg mapped its reach and how it widened even as allegations against him accumulated https://t.co/mgZWijXvOT https://t.co/Id75qmWb9p https://t.co/gUDLaU8OKU
- Sep 16, 20267.4x their median
Jeffrey Epstein built a network of elites across finance, politics and academia. By analyzing thousands of documents, Bloomberg mapped its reach and how it widened even as allegations against him accumulated https://t.co/mgZWijXvOT https://t.co/0BYS9YtzsN https://t.co/RsCSYhqiHo
- Sep 6, 20266.4x their median
North Korea’s Kim Jong Un has seen a $22 billion windfall that’s enriching his regime despite sweeping global sanctions. So how did he do it and why is a richer North Korea a concern for the world? https://t.co/IU5MNJdCdl https://t.co/phOtsqv9CC
- Aug 17, 20266.0x their median
ICE raids in Charlotte, North Carolina set off a chain reaction: damaging local businesses and potentially causing long-term economic harm that reaches far beyond the areas targeted https://t.co/r5zmnWdzNy https://t.co/ofWgMK8LA9 https://t.co/lsfd4UQ6BS https://t.co/4kyUMq3Gdg
- Aug 22, 20265.6x their median
North Korea’s Kim Jong Un has seen a $22 billion windfall that’s enriching his regime despite sweeping global sanctions. So how did he do it and why is a richer North Korea a concern for the world? https://t.co/IU5MNJdCdl https://t.co/Pnvsxl0C57
- Aug 21, 20265.4x their median
Fierce competition from China and high energy costs are just two of the reasons Germany’s famous industrial machine is sputtering. How did this crisis come to pass, and can Germany adapt in time? https://t.co/ffHe4pXDfN https://t.co/KZn4LXXlfH
- Sep 19, 20265.0x their median
North Korea’s Kim Jong Un has seen a $22 billion windfall that’s enriching his regime despite sweeping global sanctions. So how did he do it and why is a richer North Korea a concern for the world? https://t.co/IU5MNJdCdl https://t.co/4iQxu6DUIp
- Sep 12, 20265.0x their median
India and Russia’s relationship has endured for decades — through the Cold War, the war in Ukraine and growing pressure from the US. How did the two countries get here and why does India still keep Russia close? https://t.co/R47OdVBmOj https://t.co/cugiyMaxs3
- Sep 4, 20265.0x their median
As record temperatures sweep Europe, governments face hard trade-offs. Bloomberg Originals explores whether the continent can adapt to extreme heat amid political turmoil and economic scarcity https://t.co/urc3iZucgg https://t.co/5faxvrpn7j
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 5 interactions against 1.2M followers, an engagement rate of 0%. Measured over 176 original posts, its engagement rate beats 6% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 6.6K times each, and 0.076% of those impressions turn into an interaction. That is about 0.555% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.3 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 21:00 UTC, and Friday is the busiest day of the week. Of the 176 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 59 interactions, about 12x its own typical post.
- What is Bloomberg Originals's engagement rate on X?
- Bloomberg Originals (@bbgoriginals) has an engagement rate of 0%, based on the median interactions across 176 original posts from the last 30 days against 1,185,806 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At under 0.001%, Bloomberg Originals sits below the 10th percentile of the 204,880 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 @bbgoriginals have real engagement?
- Its engagement rate beats 6% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the bottom 10% for its size 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 @bbgoriginals post?
- Most posts go out around 21:00 UTC, and Friday is its busiest day, at roughly 6.3 posts per day across the measured window.