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Atlassian engagement report

@Atlassian - 107K followers on X

Measured over 32 original posts from a 30-day window, last computed on October 12, 2026.

Engagement

Middle of its size range
Per follower
0.027%
of 107K followers
Per impression
0.918%
3.2K views on a typical post
Reach
2.95%
of its followers see a post
Typical post
29
interactions (median)
Saved
0.079%
2 bookmarks on a typical post
Posting rate
1.8/day
active 60% of days
Peak time
16:00 UTC
Wednesday

A typical post picks up 29 interactions against 107K followers, an engagement rate of 0.027%. Measured over 32 original posts, its engagement rate beats 32% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.2K times each, and 0.918% of those impressions turn into an interaction. That is about 2.95% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.8 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 16:00 UTC, and Wednesday is the busiest day of the week. Of the 32 posts sampled, 97% carry an image or video, 38% are part of a thread and 25% link out. The account's strongest tracked post pulled 134 interactions, about 4.6x its own typical post.

Measured over 32 original posts from a 30-day window, last computed on October 12, 2026.

Compared with accounts its own size

Atlassian's engagement rate beats 32% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 8 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 39% 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 0.027%, Atlassian sits above the 25th percentile of the 212,741 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.697%
p902.61%
p9982.8%
Engagement rate as a share of followers, across the 212,741 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,375 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 percentile0.146%
75th percentile0.697%
90th percentile2.61%
99th percentile82.8%

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 16:00 UTC, and Wednesday 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: 16:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 16:00 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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
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 video97% of posts+111%+108% to +115%34K
Outbound link25% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 97% 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.
  • 25% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 261 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

  • Aug 25, 20264.6x their median

    We handed @WilliamsF1 driver Carlos Sainz the support line. “My day is full of meetings.” → “Schedule a meeting to resolve it.” https://t.co/Lv1545amQ8

    96263921K viewsView on X
  • Oct 2, 20263.7x their median

    F1 isn't just a race of cars. It’s a race of data. 📊 The fastest way forward? Knowing where you’ve been. See how Atlassian @WilliamsRacing applies and converts context into chasing lap time. 👇 https://t.co/onjAK6GISZ

    9581413K viewsView on X
  • Oct 7, 20263.6x their median

    Your AI just got a massive upgrade. ✨ Atlassian MCP now expands across 220+ tools for searching, reasoning, and taking action. One request can now span your full workflow—from Loom transcripts to Bitbucket PRs. See what’s new: https://t.co/4Jl4R5ZAjF https://t.co/2iRiIR3CkH

    7471675.2K viewsView on X
  • Oct 7, 20263.4x their median

    Most AI is a solo act. We’re making it a team sport. Today at Team ‘26 Europe, we’re introducing Agentic Multiplayer Protocol (AMP). How it works: 🤝 Work alongside your agents across every surface. 🤝 Know who’s who, who’s doing what, and who did what, when. 🤝 Agents are grounded in organizational context to deliver real impact.

    6072483.8K viewsView on X
  • Oct 6, 20262.6x their median

    Atlassian + @OpenAI are teaming up to connect AI to how teams actually plan, build, and deliver. By grounding frontier intelligence in the Atlassian Teamwork Graph, we’re moving AI from guessing to knowing. The result: context-aware action that keeps humans in the loop. More on the partnership: https://t.co/dqqzLcK1vh

    5855717K viewsView on X
  • Oct 9, 20262.0x their median

    ☑️ AMP ☑️ Rovo Work ☑️ Atlassian MCP ☑️ Loom AI Overlays ☑️ DX Agent Effectiveness All the hits from our Team '26 Europe Founder Keynote in <2 mins. 👇 https://t.co/vkuYMnQFa9

    435913.3K viewsView on X
  • Sep 30, 20261.7x their median

    94% of engineering teams have adopted AI. Only 6% are actually set up to run an AI-native SDLC. The missing piece? Context. Our CEO & Co-Founder @mcannonbrookes and @vercel CEO @rauchg discuss the future of software development and how real results come from connecting agents to organizational knowledge and intent. Full session below. ⬇️

    325746.4K viewsView on X
  • Oct 5, 20261.6x their median

    Meet Carlos, the Decision Driver. Inspired by @Carlossainz55 and Atlassian @WilliamsRacing, this Rovo agent helps teams make tough, data-backed calls fast. Less second-guessing. More forward motion. 🏁 https://t.co/CVYQhveL6N

    359204.2K viewsView on X
  • Oct 8, 20261.5x their median

    Can an agent really be a teammate if no one can see what it’s doing? When agentic work happens locally, the rest of the team is in the dark. We’re changing that by bringing local agent sessions into Jira. Now you can: → See active local sessions on your board. → Drag a session into a column to create a work item. → Bring human and agent work together in one view, with full context. Shipping soon. See what else dropped at Team '26 Europe: https://t.co/CXDP29Kgji

    333623.8K viewsView on X
  • Oct 7, 2026

    You have AI. What’s next? Making it work for your business. 💡 Our engineers worked with 100+ customers to find what actually drives results. One big win: a manufacturer cut triage effort by ~50% by starting with their messiest workflow. Explore more success stories in the FDE Playbook ➡️ https://t.co/XNhbPWB3e3

    300932.9K 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 29 interactions against 107K followers, an engagement rate of 0.027%. Measured over 32 original posts, its engagement rate beats 32% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.2K times each, and 0.918% of those impressions turn into an interaction. That is about 2.95% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.8 posts a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 16:00 UTC, and Wednesday is the busiest day of the week. Of the 32 posts sampled, 97% carry an image or video, 38% are part of a thread and 25% link out. The account's strongest tracked post pulled 134 interactions, about 4.6x its own typical post.

What is Atlassian's engagement rate on X?
Atlassian (@Atlassian) has an engagement rate of 0.027%, based on the median interactions across 32 original posts from the last 30 days against 107,172 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.027%, Atlassian sits above the 25th percentile of the 212,741 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 @Atlassian have real engagement?
Its engagement rate beats 32% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range 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 @Atlassian post?
Most posts go out around 16:00 UTC, and Wednesday is its busiest day, at roughly 1.8 posts per day across the measured window.

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