If you sell into IT, DevOps, or product teams, one buying signal matters more than almost any other: what’s already in the tech stack. Atlassian’s tools, Jira, Confluence, Trello, and Bitbucket, sit at the center of how modern software teams plan, build, and ship work. Knowing which companies run Atlassian tells you who’s already invested in agile workflows, who’s likely scaling their engineering org, and who’s a warm fit for adjacent tools, services, or migrations.
This list breaks down 15 well known companies running Atlassian products, why the tool footprint matters for B2B sales and marketing teams, and how to move from “here’s a list” to an actual, workable atlassian users email database you can run campaigns against.
Atlassian isn’t a niche tool. It reports serving well over 200,000 customers worldwide, spanning startups to Fortune 500 enterprises across nearly every industry. That scale is exactly why an atlassian users mailing list is such a useful asset for go to market teams.
A company running Jira or Confluence tells you several things at once:
For sales teams building account lists, technographic signals like “uses Atlassian” are far more predictive than firmographic data alone (headcount, industry, revenue). Combining both is where a real atlassian products users email database earns its keep.
Here are 15 organizations publicly documented as Atlassian customers, based on Atlassian’s own customer references and case study materials.
NASA has used Jira across engineering and mission support teams for issue tracking and project coordination, a frequently cited example in Atlassian’s own customer materials.
Spotify’s engineering culture, widely studied in the software industry, runs on Atlassian tooling including Jira for cross squad project tracking.
As a global payments company with a massive software footprint, Visa has been named among Atlassian’s enterprise customer base for years.
Citigroup is one of the longest referenced Atlassian customers, using Jira and related tools to manage software delivery across its banking technology teams.
eBay has appeared in Atlassian’s customer materials as a long standing user of Atlassian’s issue tracking and collaboration products.
Coca-Cola’s inclusion in Atlassian’s customer roster reflects how far Atlassian’s footprint extends beyond pure play tech companies into global consumer brands.
BMW is another recurring name in Atlassian’s public customer references, representing Atlassian’s reach into automotive and manufacturing technology teams.
Netflix has been named among organizations using Atlassian’s issue tracking and collaboration tools to support its engineering operations.
Verizon’s scale as a telecom carrier makes it a representative example of Atlassian’s presence in large, regulated enterprise environments.
Bank of America has been referenced as an Atlassian customer, illustrating adoption inside heavily regulated financial services IT environments.
As a cloud storage and collaboration company itself, Dropbox’s use of Atlassian tools is a natural fit for its own engineering workflows.
General Motors appears in Atlassian’s customer references, reflecting adoption across large scale manufacturing and automotive software teams.
Walmart’s technology arm has been cited as an Atlassian customer, supporting the retailer’s expansive internal software and e commerce engineering teams.
Lyft has been named in Atlassian materials among companies relying on its tools for internal software delivery and operations.
Samsung, through its enterprise asset management usage (notably following Atlassian’s acquisition of Mindville), is documented among organizations running Atlassian connected tooling.
A list like this is a useful starting point, but it has real limits if your goal is outbound execution:
It’s a snapshot, not a live feed. Companies switch tools, expand usage, or consolidate vendors constantly. A static list from a case study page can be a year or more out of date.
It skips the contacts. Knowing that Visa or Netflix uses Atlassian doesn’t tell you who owns the DevOps budget, who evaluates tooling, or how to reach them.
It’s incomplete by design. Public case studies and press mentions surface maybe a few hundred named accounts. The real universe of Atlassian users, especially mid market and SMB companies, runs into the hundreds of thousands.
This is exactly the gap between a “list of companies that use Atlassian products” and a usable atlassian customers database built for prospecting.
If you’re building pipeline around Atlassian’s install base, here’s the practical path from a public list to a workable dataset:
Start with technographic data providers. Platforms that track technology adoption at the domain level can surface far more Atlassian users than public case studies, often segmented by product (Jira, Confluence, Bitbucket, Trello) and company size.
Layer in firmographic filters. Narrow by industry, employee count, and revenue band so your atlassian users database matches your actual ICP, not just anyone running Jira.
Append verified contact data. Technographic signals tell you which companies to target. You still need verified emails and direct dials for the actual buyers, IT directors, DevOps leads, engineering managers, and procurement, to run outbound.
Validate and refresh regularly. Tool adoption changes. Emails go stale. A mailing list built once and never refreshed decays fast, plan for periodic re verification.
Segment by intent signal, not just tool usage. Companies that recently adopted Atlassian, expanded their Atlassian footprint, or are evaluating competing tools are hotter targets than companies that have quietly run Jira for a decade with no other signals.
This is the practical difference between a headline list of 15 logos and an operational atlassian products users email database that a sales team can actually run sequences against.
The 15 companies above prove the pattern: Atlassian’s footprint spans finance, retail, media, automotive, and tech. If those verticals overlap with your ICP, the opportunity isn’t the list itself, it’s everything below the surface: the mid market and enterprise accounts running Atlassian that never make it into a public case study, plus the verified contacts inside them.
It’s a dataset of companies confirmed to run Atlassian products like Jira or Confluence, combined with verified email addresses and direct dials for the people who buy or evaluate related tools. It goes beyond a simple list of company names by including the contacts a sales team needs to reach out.
Atlassian usage signals a formalized software development process, an agile delivery model, and existing budget for collaboration and DevOps tooling. That makes these companies a plausible fit for testing tools, security add ons, integration platforms, and DevOps consulting.
A public list like this one is a snapshot based on Atlassian’s own case studies and press materials, not a live feed. Companies switch tools, expand usage, or consolidate vendors constantly, so a static list can be a year or more out of date.
A list of company names tells you who uses the tool. A database adds firmographic filters like industry, employee count, and revenue band, plus verified contact data for the actual buyers, so the information is usable for outbound campaigns rather than just a reference point.
Start with technographic data providers to find companies running Atlassian products, layer in firmographic filters to match your ICP, append verified contact data for the actual buyers, and refresh the list regularly since tool adoption and emails both change over time.
Span Global Services builds and maintains technographic and firmographic datasets, including verified emails and direct dials at companies running Jira, Confluence, and other Atlassian products.
