Bluesky Is Growing Fast – But Measurement Is Still Catching Up
Bluesky’s open protocol architecture makes it genuinely different from every major social platform that came before it. Built on the AT Protocol, the network allows third-party developers to build tools directly on top of its data layer – which means analytics tools have appeared faster here than they did in Twitter’s early days. The catch is that most of these tools are still rough around the edges, built by indie developers and open-source contributors rather than venture-backed analytics companies.
That scrappiness, though, is exactly what makes them useful for tracking early adopter engagement. The accounts building audiences on Bluesky right now are not casual users – they are developers, journalists, creators, and marketers who came specifically because they wanted something different. Tracking how those people interact with your content requires tools that understand the network’s structure, not tools designed for algorithmic feeds and ad-driven reach metrics. The five options below each approach that problem differently, and all of them are free to use at the basic tier.
1. Bluesky Stats (bsky.ms)
Bluesky Stats, accessible through the bsky.ms domain, is among the most straightforward public profile analysis tools on the network. Enter any handle and the tool pulls follower counts, post frequency data, and a breakdown of engagement by post type. It does not require authentication, which means you can run competitor analysis without connecting your own account. That open access design is a direct product of the AT Protocol’s public data model – every post and interaction is readable by any application that queries the right endpoints.
Where it earns its place in an early adopter strategy is in the follower-to-engagement ratio view. Because Bluesky’s user base skews toward technically engaged users, follower counts are lower than what those same accounts might have on Instagram or X – but reply rates are often disproportionately high. Bluesky Stats surfaces that gap clearly, letting you see whether an account with 2,000 followers is generating the kind of conversation that a 50,000-follower account on another platform rarely achieves. That ratio tells you more about genuine community traction than raw numbers ever could.
The tool updates on a rolling basis rather than real-time, so it works better for weekly trend analysis than for monitoring a post in the first hour after publishing. For teams running content experiments on Bluesky, it functions best as a benchmarking instrument – check it at the start of a campaign period, then again at the end.
2. Clearsky (clearsky.app)
Clearsky started as a moderation transparency tool designed to show users which lists they appear on and which accounts have blocked or muted them. But its underlying data capabilities have made it genuinely useful for engagement analysis beyond its original purpose. Specifically, it lets you trace the social graph around any account – seeing who follows whom and identifying the connector accounts that sit at the center of specific communities. In an early adopter network, those connector accounts are the ones worth tracking most closely.
When a piece of content starts moving on Bluesky, it rarely goes wide through an algorithm. It spreads through trusted accounts amplifying to their specific audiences. Clearsky gives you visibility into which accounts are functioning as those amplification hubs within a niche. If you are marketing to developers, for example, you can identify which 30 or 40 accounts are doing the actual spreading inside that community. That kind of structural insight is largely invisible on platforms that route everything through a recommendation engine.
3. Wolfgang Analytics’ Bluesky Tracker
Wolfgang Analytics, the Dublin-based digital performance agency, released a free Bluesky tracking template built inside Google Looker Studio. The template pulls public AT Protocol data and maps it against a dashboard that marketers already know how to read. It is not a standalone application – you connect it to a Google account and it renders inside Looker Studio’s familiar interface. That design choice matters because it lowers the learning curve considerably for teams already running Google Analytics or Search Console dashboards.
The tracker focuses on post-level performance: likes, reposts, replies, and quote posts broken out by date. What makes it more useful than a simple spreadsheet is the time-series visualization, which lets you spot patterns across a posting schedule. Post at 9am on a Tuesday and compare it against 7pm on a Thursday – the visual output makes those gaps obvious in a way that raw numbers do not. Early adopter audiences on Bluesky tend to be active during specific windows that differ from mainstream platform behavior, and finding those windows is one of the more valuable things a free tool can help you do.
4. Skyfeed Builder Analytics
Skyfeed is primarily known as a custom feed creation tool for Bluesky – it lets users build algorithmic feeds based on keywords, hashtags, or specific accounts. But the analytics layer built into its feed management interface gives creators and brands something valuable: real data on how content performs within a custom feed context, not just on the main timeline. This distinction matters because Bluesky’s feed ecosystem is where a significant portion of engaged reading actually happens.
When someone subscribes to a curated feed on Bluesky – a tech news feed, a design community feed, or a local politics feed – they are signaling a high level of intentional interest in that topic. Tracking how your content performs when it appears inside those feeds, versus when it appears on a user’s main following timeline, gives you a clearer picture of who is actively seeking out your subject matter versus who is passively scrolling past it. Skyfeed’s analytics surface that difference, and for brands trying to build topical authority on the network, that data point changes how you approach content positioning.
The tool is free for feed creation and basic analytics, with usage limits that are generous enough for individual creators and small marketing teams. The interface is technical enough that it rewards some patience during the setup phase, but the output is worth it. No other free tool on the network currently breaks down performance by feed context in the same way.
5. Redact + Manual AT Protocol Queries
This one is less plug-and-play than the others, but it is worth including because it offers something none of the packaged tools above can match: completely raw access to your engagement data with no intermediary filtering. Bluesky’s AT Protocol exposes a public API that anyone can query without authentication. By combining a tool like Redact (which helps export your post history) with direct API calls to endpoints like app.bsky.feed.getAuthorFeed, you can build a custom engagement dataset that you own entirely and can analyze in any spreadsheet or BI tool you choose.
The practical application for engagement tracking is straightforward. Pull your post history as a JSON export, filter by reply count and repost count, and sort by date. You will immediately see which content types are generating replies (a signal of genuine conversation) versus which are generating reposts (a signal of sharing intent). On Bluesky’s early adopter audience, those two signals often point to very different kinds of content performing well – technical threads tend to generate replies, while opinion pieces and links tend to generate reposts. Understanding that split helps you calibrate what to post more of.
This approach requires more manual work than the other four tools, and it is not practical for daily monitoring. But for a quarterly audit of your Bluesky presence – or for a competitor analysis where you want unfiltered numbers – it is the most honest data source on this list. There is no algorithm standing between you and the raw engagement counts, which on a platform that is specifically trying to move away from black-box systems, feels appropriate.
How to Use These Tools Together
None of these tools are complete solutions on their own. Each was built with a specific slice of the analytics problem in mind – one handles social graph mapping, another handles feed-level performance, another handles raw data export. The most effective approach is to pair two or three of them based on what you are actually trying to measure.
For anyone tracking growth in a specific niche community, Clearsky combined with Skyfeed analytics gives you a picture of both who the key connectors are and how your content is performing within the feeds those connectors have built. For anyone doing cross-platform comparison to understand whether Bluesky is worth continued investment, the Wolfgang Looker Studio template gives you a format that translates directly into the same reporting structure your team is already using elsewhere. And if you want to track a specific decentralized social strategy more broadly – not just on Bluesky but across AT Protocol and ActivityPub networks – pairing these tools with insights from free Mastodon analytics gives you a more complete view of how open social ecosystems are actually behaving.
The unresolved tension with all of these tools is sustainability. They are free because they are mostly built by individuals or small teams who find the project interesting. As Bluesky’s user base grows, the pressure on these tools will increase – and the question of whether they stay free, stay accurate, or stay maintained at all is genuinely open. The platform you are building an audience on now may require very different measurement infrastructure in eighteen months.
