June vs Statsig: Which Is Better in 2026?

June is a product analytics tool designed specifically for B2B SaaS companies, focused on giving instant, account-level insight into how companies — not just individual users — engage with your product. Most analytics tools are built around individual user events, but in B2B what matters is the account: which companies are active, which are at risk, which are expanding, and how teams within them adopt your features. June reorients analytics around this reality, making it far more useful for SaaS teams trying to drive retention and growth.

What sets June apart is how quickly it delivers meaningful insights. Instead of requiring you to build dashboards from scratch, it auto-generates relevant reports and metrics out of the box, surfacing things like active accounts, feature usage, user and company engagement, and signs of churn or growth with minimal setup. This "instant analytics" approach means small teams without dedicated data analysts can still understand their product usage and act on it, rather than drowning in raw events or never getting around to building reports.

June emphasizes connecting product usage to the people and companies in your business, integrating with tools like CRMs, Slack and customer messaging so insights reach the teams that need them — alerting customer success when an account's usage drops, or sales when a company hits an expansion signal. This bridges the gap between product data and revenue action. It's a fit for early and growth-stage B2B SaaS companies that want clear, account-centric product analytics without the complexity and overhead of enterprise platforms. For SaaS teams that want to quickly understand how their accounts use the product, spot risks and opportunities, and put that insight to work driving retention and expansion, June offers a focused, fast and genuinely B2B-native analytics solution.

Statsig is a unified platform for feature flags, experimentation (A/B testing) and product analytics that helps teams ship features safely and measure their real impact. It combines the ability to roll out features gradually and control them with flags, run rigorous experiments to test changes, and analyze product data — all in one place — so teams can move fast while making data-driven decisions about what to build and ship. This integration of flags, experimentation and analytics is its key strength.

With Statsig, developers can wrap new features in flags to release them gradually, target specific users, and turn them off instantly if something goes wrong, reducing the risk of every launch. Teams can run A/B tests and experiments to measure whether changes actually improve key metrics, getting statistically sound answers rather than relying on intuition. And because it includes product analytics, teams can see how features affect user behavior and outcomes directly, closing the loop between shipping and understanding impact. This lets product and engineering teams iterate confidently, backed by data.

Statsig is aimed at product and engineering teams — from startups to large companies — that want to adopt a data-driven, experimentation-led approach to building software, with the tooling to do it well. By bringing feature management, experimentation and analytics together, it removes the need to stitch together separate tools and makes rigorous, measured development accessible. It's known for being powerful and developer-friendly, with pricing and capabilities that have attracted a wide range of teams. As more organizations embrace experimentation and data-informed product development, integrated platforms that enable it are increasingly valuable. For teams that want to ship features safely with flags, test their impact with experiments, and measure results with analytics — all in one platform — Statsig offers a powerful, unified and genuinely useful solution.