An alternative to Amplitude for experimentation: Statsig

Choosing between analytics platforms feels like picking a foundation for your house - get it wrong, and you'll spend years dealing with the consequences. Amplitude has dominated product analytics for a decade, but many teams hit a wall when they need robust experimentation capabilities alongside their analytics.

That's where the comparison gets interesting. Statsig emerged from Facebook's experimentation culture with a fundamentally different approach: what if you built experimentation and analytics as one unified system from day one? This deep dive examines how these philosophical differences translate into practical tradeoffs for your team.

Company backgrounds and platform overview

Statsig launched in 2020 when ex-Facebook engineers decided to solve a specific problem: why do companies need separate tools for experimentation, feature flags, and analytics? The founding team had spent years running thousands of experiments at Facebook. They knew firsthand how painful it was to stitch together multiple platforms.

Amplitude took a different path. Starting in 2012, they focused exclusively on behavioral analytics - helping teams understand what users do inside their products. The experimentation features came eight years later as an add-on. This sequence matters because it shaped each platform's DNA.

The results show in their customer bases. Statsig attracts engineering-driven organizations like OpenAI, Notion, and Figma who want their experimentation and analytics tightly coupled. These teams care about:

• Running experiments at scale without infrastructure headaches

• Having complete visibility into how metrics are calculated

• Shipping features fast with integrated feature flags

Amplitude serves product teams who built their workflows around behavioral analytics first. They excel at showing user journeys, cohort analysis, and retention patterns. The experimentation capabilities supplement rather than drive their core analytics needs.

This cultural divide runs deeper than features. Statsig maintains its startup DNA - they ship updates weekly and engage directly with customers through Slack. Amplitude evolved into an enterprise platform with formal support tiers and quarterly release cycles. Neither approach is wrong; they serve different organizational styles.

Feature and capability deep dive

Experimentation capabilities

The technical implementation of experiments reveals stark differences between platforms. Statsig includes CUPED variance reduction by default - a statistical technique that can cut experiment runtime by 30-50%. Here's what that means practically: instead of waiting 4 weeks for results, you might get statistically significant answers in 2 weeks.

Amplitude offers standard A/B testing with basic significance calculations. They handle the fundamentals well but lack advanced statistical methods like:

• Sequential testing (checking results safely before experiments end)

• Stratified sampling (ensuring balanced user distribution)

• Heterogeneous effect detection (finding which user segments respond differently)

Feature flag architecture shows another key distinction. Statsig provides unlimited free feature flags with zero gate-check charges. You can roll out features to millions of users without worrying about costs scaling exponentially. Amplitude's feature management requires separate pricing tiers, adding both cost and complexity to your infrastructure.

The warehouse-native approach sets Statsig apart for data teams. You can run experiments directly in Snowflake, BigQuery, or Databricks while maintaining sub-millisecond flag evaluation. Amplitude requires exporting data for warehouse analysis - adding pipeline complexity and potential latency issues.

Analytics and reporting

Amplitude built its reputation on behavioral analytics, and it shows. Their cohort analysis and funnel visualization tools remain industry-leading. Product managers love how easily they can answer questions like "What do users do after hitting our paywall?" or "Which features drive retention?"

Statsig takes a different angle: every experiment result integrates seamlessly with product analytics. You're not switching between tools to understand impact. The platform processes over 1 trillion daily events with transparent SQL access - click any metric to see exactly how it's calculated.

Session replay functionality highlights the pricing philosophy gap:

• Statsig includes 50K free monthly sessions in their base tier

• Amplitude charges separately for replay features

• Both platforms handle similar scale, but the cost structure differs dramatically

The real advantage comes from unified metrics. When your experimentation and analytics share the same definitions, you eliminate the "metric mismatch" problem that plagues teams using separate tools. Brex reduced their analytics overhead by 20% just by consolidating to one platform.

Pricing models and cost analysis

Transparent pricing structures

Let's talk actual numbers. Statsig charges only for analytics events and session replays - feature flags remain free forever regardless of scale. Amplitude bills based on Monthly Tracked Users (MTUs) with additional charges for each product module.

For a typical SaaS company with 100K MAU:

• Statsig costs approximately $2,000-3,000 monthly (all features included)

• Amplitude's Growth tier runs $5,000-7,000 monthly (analytics only)

• Adding Amplitude Experiment increases costs by another 40-60%

Statsig's analysis shows 50-70% lower total costs when comparing full platform capabilities. The free tier differences are equally striking: Statsig supports 2 million events monthly with full access, while Amplitude limits free users to 50K MTUs with restricted features.

Hidden costs and scaling considerations

The sticker price tells only part of the story. Users report unexpected Amplitude overages when exceeding event budgets - often discovered only after the fact. These surprise bills can blow quarterly budgets. Statsig provides real-time usage dashboards and automatic alerts before you hit limits.

Enterprise contracts reveal more pricing gaps:

• Statsig publishes transparent volume discounts starting at 200K MAU

• Discounts reach 50%+ for high-volume customers

• Amplitude requires lengthy sales negotiations without published rates

Implementation costs matter too. Statsig offers 30+ SDKs with typical one-week deployment timelines. Teams get up and running fast because everything's integrated. Amplitude's modular approach often requires 3-4 weeks to fully deploy experimentation alongside analytics.

Don Browning, SVP at SoundCloud, explained their decision: "We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration."

The total cost extends beyond subscriptions. Consider engineering time spent maintaining data pipelines, reconciling metrics between tools, and debugging integration issues. Consolidation to a unified platform typically saves 15-20 engineering hours monthly.

Decision factors and implementation considerations

Developer experience and onboarding

Speed to value separates great platforms from merely good ones. Statsig engineers can launch their first experiment the same day they sign up. The platform provides comprehensive docs with one-click SQL transparency - developers see exactly how every metric calculates. When questions arise, you get direct Slack access to Statsig's engineering team.

Amplitude takes a more structured approach through Amplitude Academy. The educational materials are thorough but teams typically need 2-4 weeks to fully onboard the combined analytics and experimentation setup. Both platforms support no-code experiment creation, making them accessible to non-technical users.

The unified metrics catalog eliminates a major pain point. Instead of maintaining duplicate definitions across analytics and experimentation tools, everything shares one source of truth. This sounds simple but saves hours of debugging "why don't these numbers match?" conversations.

Enterprise readiness and support

Security requirements don't disappear at scale. Both platforms deliver 99.99% uptime and SOC 2 Type II compliance - table stakes for enterprise deployment. Statsig adds warehouse-native options for teams with strict data residency requirements. Your data stays in your infrastructure while getting full platform benefits.

Support experiences differ dramatically between platforms:

• Statsig connects you directly with data scientists and engineers

• Questions get answered by people who understand experimentation deeply

• Amplitude routes through traditional support tiers

Brex's engineering team reported: "Our engineers are significantly happier using Statsig. They no longer deal with uncertainty and debugging frustrations."

Both platforms handle massive scale without breaking. Statsig processes 6 trillion monthly events across customers without performance degradation. The infrastructure scales linearly - no surprise bottlenecks or cost cliffs as you grow.

Bottom line: why is Statsig a viable alternative to Amplitude?

The numbers tell a clear story. Statsig's pricing runs 50-70% lower than Amplitude across all usage levels. While Amplitude's costs jump significantly at scale, Statsig maintains predictable linear pricing with generous free tiers.

Architecture creates the fundamental distinction. Statsig bundles experimentation, feature flags, analytics, and session replay into one platform - no separate SKUs or complex pricing matrices. Amplitude's modular structure forces teams to buy and integrate multiple tools, increasing both cost and operational complexity.

Sumeet Marwaha, Head of Data at Brex, captured the core benefit: "The biggest benefit is having experimentation, feature flags, and analytics in one unified platform. It removes complexity and accelerates decision-making by enabling teams to quickly gather and act on insights without switching tools."

Technical advantages compound over time:

• 30+ SDKs give engineering teams implementation flexibility

• Warehouse-native deployment keeps data in your infrastructure

• CUPED variance reduction cuts experiment runtime significantly

• Sequential testing enables safe early decision-making

These capabilities helped Notion scale from single-digit to 300+ experiments quarterly. The statistical rigor isn't academic - it directly impacts how fast teams can learn and iterate.

For teams evaluating alternatives to Amplitude's experimentation features, Statsig offers a fundamentally different approach. Instead of bolting experimentation onto analytics, they built both systems together from the ground up. The result? Lower costs, faster implementation, and happier engineering teams.

Closing thoughts

Picking an experimentation platform shapes how your team builds products for years. Amplitude excels at behavioral analytics with experimentation as an add-on. Statsig flips that model - putting experimentation at the core with analytics naturally integrated. The choice depends on whether you see experiments as your primary learning mechanism or a nice-to-have feature.

Want to dig deeper? Check out Statsig's technical documentation or their customer case studies to see how teams like Notion and OpenAI run experiments at scale. You can also explore detailed pricing comparisons to model costs for your specific use case.

Hope you find this useful!