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Anaconda engagement report

@anacondainc - 84K followers on X

Measured over 21 original posts from a 30-day window, last computed on October 3, 2026.

Engagement

Bottom quarter for its size
Per follower
0.005%
of 84K followers
Per impression
0.257%
1.6K views on a typical post
Reach
1.86%
of its followers see a post
Typical post
4
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
0.77/day
active 63% of days
Peak time
20:00 UTC
Thursday

A typical post picks up 4 interactions against 84K followers, an engagement rate of 0.005%. Measured over 21 original posts, its engagement rate beats 11% of 15,519 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 1.6K times each, and 0.257% of those impressions turn into an interaction. That is about 1.86% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.77 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 20:00 UTC, and Thursday is the busiest day of the week. Of the 21 posts sampled, 90% carry an image or video and 95% link out. The account's strongest tracked post pulled 49 interactions, about 12x its own typical post.

Measured over 21 original posts from a 30-day window, last computed on October 3, 2026.

Compared with accounts its own size

Anaconda's engagement rate beats 11% of the tracked X accounts closest to it in follower count (15,519 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 13% 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 0.005%, Anaconda sits above the 10th percentile of the 157,374 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.

p100.003%
p250.022%
p50 (median)0.128%
p750.604%
p902.32%
p9983.4%
Engagement rate as a share of followers, across the 157,374 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 26,055 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 percentile0.003%
25th percentile0.022%
50th percentile0.128%
75th percentile0.604%
90th percentile2.32%
99th percentile83.4%

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 20:00 UTC, and Thursday 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: 20:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 20:00 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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Thursday
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 video90% of posts+111%+108% to +115%34K
Outbound link95% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 90% 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.
  • 95% 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 288 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

  • Jul 15, 202612x their median

    Anaconda has acquired @kilocode, the open-source coding agent used by 3M+ developers. This further cements Anaconda as the AI-native development platform for the enterprise. Enabling security and governance – without the need to trade off velocity. https://t.co/YObzcwYb63 https://t.co/UX12LJmGDs

    355815.5K viewsView on X
  • Jul 28, 20264.8x their median

    Everyone's fixated on Claude Code vs Codex vs Cursor. But buried in @theinformation's new report is a smaller storyline that matters more long term. In this piece, our co-founder @s_breitenother explains how Kilo, an open-source alternative recently acquired by @anacondainc, is seeing a real jump in enterprise interest and contract size. https://t.co/mdIeexWWgn

    141315.0K viewsView on X
  • Aug 3, 20264.3x their median

    Ever find a #Python package that looks promising, but hesitate to install it just to see what it does? Now, for select packages on https://t.co/kG1EFncVv8, you can run an example directly in your browser with the new "Try This Package" feature. https://t.co/H90XiaYIl9

    113302.8K viewsView on X
  • Jul 15, 20263.8x their median

    Enterprises want to adopt AI-native workflows but lack the visibility to assess whether the benefits outweigh the risks. Anaconda’s acquisition of @kilocode solves this — closing the gap between the AI developers want to use and the AI orgs can trust: https://t.co/YObzcwYb63 https://t.co/bPE8H1iSSs

    102302.7K viewsView on X
  • Sep 10, 20263.5x their median

    Declare dependencies → develop in a browser or VS Code → build the environment into a container → run the same code in the cloud. Watch the full demo of the developer experience in the Anaconda Platform: https://t.co/BStcPGKgHC https://t.co/GEmKY26Cbe

    82402.6K viewsView on X
  • Jun 30, 20264.3x their median

    A century before modern AI, Andrey Markov manually counted 20k letters in a Pushkin poem to show that predictable patterns can emerge from sequences where each item depends on the one before it. The core concept still lives on in today’s LLMs. https://t.co/bI9On2IS2L

    102011.7K viewsView on X
  • Jul 31, 20263.0x their median

    Anaconda has signed the Open Weights and American AI Leadership letter, signed by the likes of NVIDIA, Microsoft, and 230+ organizations. Openness may be one of the most important paths to AI safety and security. Read our statement of support here: https://t.co/F2dpJw5htm https://t.co/MmJXs1aNiE

    93002.1K viewsView on X
  • Jul 24, 20263.0x their median

    Make this your Summer of Shipping with Anaconda ☀️ With @kilocode, Anaconda is bridging the gap from local experimentation to enterprise-ready AI with an open, trusted platform built for the full AI-native development lifecycle: https://t.co/E6cyUx8tSJ https://t.co/BY682cNJBm

    74102.7K viewsView on X
  • Jul 23, 20262.5x their median

    On @TechstrongTV, Anaconda CEO @david_desanto explains why the acquisition of Kilo Code is about much more than adding another coding agent. The goal is to give developers an end-to-end experience. Watch his full conversation with @ashimmy: https://t.co/kIO3Mkz8AS https://t.co/47tByTSyWO

    45012.5K viewsView on X
  • Jul 21, 20262.5x their median

    Last week, we acquired @kilocode. This is just the latest milestone as Anaconda builds an open, model-agnostic, and enterprise-ready platform that supports the full AI-native development lifecycle. Catch up on the news in @UniteAi: https://t.co/TIpkIbdbuU https://t.co/1BgJM7NqXu

    72012.0K 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.

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Reading these numbers

A typical post picks up 4 interactions against 84K followers, an engagement rate of 0.005%. Measured over 21 original posts, its engagement rate beats 11% of 15,519 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 1.6K times each, and 0.257% of those impressions turn into an interaction. That is about 1.86% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.77 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 20:00 UTC, and Thursday is the busiest day of the week. Of the 21 posts sampled, 90% carry an image or video and 95% link out. The account's strongest tracked post pulled 49 interactions, about 12x its own typical post.

What is Anaconda's engagement rate on X?
Anaconda (@anacondainc) has an engagement rate of 0.005%, based on the median interactions across 21 original posts from the last 30 days against 83,649 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Anaconda sits above the 10th percentile of the 157,374 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 @anacondainc have real engagement?
Its engagement rate beats 11% of the tracked X accounts closest to it in follower count (15,519 accounts), which puts it in the bottom quarter 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 @anacondainc post?
Most posts go out around 20:00 UTC, and Thursday is its busiest day, at roughly 0.77 posts per day across the measured window.

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