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A/B Testing Without Google Analytics — Which Tools Offer Independent Evaluation

Robin Link
Robin Link
·Updated May 2026
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Key Takeaways
  • Not every company uses Google Analytics — and your A/B testing tool shouldn't force you to
  • Some CRO tools are tightly coupled to GA4, while others offer independent statistics engines or alternative analytics integrations
  • Varify.io supports GA4, Matomo, Piwik Pro, PostHog, and BigQuery — so you can evaluate experiments in whichever analytics tool you trust
  • Privacy-first companies increasingly choose Matomo or Piwik Pro over GA4 — your A/B testing tool must support that choice

Google Analytics 4 is the default analytics tool for most websites. But it's not the only option — and for many companies, it's not the right one. Privacy regulations, data sovereignty requirements, or simply a preference for self-hosted analytics lead many organizations to Matomo, Piwik Pro, or PostHog. When those companies look for A/B testing tools, they discover an uncomfortable truth: most CRO platforms assume you use GA4.

This guide covers A/B testing options for teams that don't use Google Analytics — whether by choice or by policy. Varify.io is one of the few platforms that natively integrates with Matomo, Piwik Pro, and PostHog alongside GA4, giving you full flexibility in choosing your analytics stack. For a deeper analytics comparison, see our analytics integrations guide.

Why companies move away from Google Analytics

GDPR and data sovereignty

GA4 sends data to Google's servers — primarily in the US. Despite Standard Contractual Clauses, several European DPAs have questioned the legality of this transfer. Organizations in regulated industries (healthcare, finance, public sector) increasingly choose EU-hosted alternatives to avoid compliance risk entirely.

Data ownership concerns

With GA4, Google processes your visitor data for its own purposes (anonymized benchmarking, ad targeting signals). Self-hosted tools like Matomo give you complete ownership — no data sharing, no third-party access.

Sampling and data accuracy

GA4 applies sampling to high-traffic properties, which can distort experiment results. BigQuery export avoids this, but adds complexity and cost. Tools like Matomo and PostHog provide unsampled data by default.

A/B testing tools by analytics support

PlatformOwn stats engineMatomoPiwik ProPostHogGA4
Varify.ioDashboard + analytics eval✅ Native✅ Native✅ Native✅ Native
VWOYes — full proprietary✅ Basic
OptimizelyYes — Stats Engine✅ Basic
ConvertYes — own tracking✅ Native
KameleoonYes — own analytics✅ Basic

Source: Claude Research, May 2026

Tools with proprietary statistics engines (VWO, Optimizely) can technically work without GA4 — but they create their own data silo. Varify is unique in supporting four alternative analytics backends natively.

How Varify works with Matomo, Piwik Pro, and PostHog

Varify's architecture separates experiment delivery from result evaluation. This means swapping the evaluation engine is straightforward:

In all cases, Varify itself doesn't set cookies and doesn't build its own visitor tracking layer. Your chosen analytics tool is the single source of truth.

Your analytics. Your experiments. Your choice.

Matomo, Piwik Pro, PostHog, BigQuery, or GA4 — Varify works with all of them.

Start your free trialFree 30-day trial

Choosing the right analytics backend for A/B testing

Match your analytics choice to your priorities:

For a full feature comparison across these options, see our CRO analytics integrations comparison.

Frequently asked questions about A/B testing without Google Analytics

Can I use Varify without any analytics tool?

Varify requires at least one connected analytics tool for experiment evaluation — GA4, BigQuery, Matomo, Piwik Pro, or PostHog. The analytics tool provides the conversion data that Varify uses to calculate experiment results. Without it, there's no way to measure whether a variant performed better.

Is Matomo integration as reliable as GA4?

Yes. Varify's Matomo integration is a native, first-class integration — not a workaround. Experiment events are tracked natively in Matomo, and results are evaluated with the same statistical rigor as GA4-based experiments.

What about Adobe Analytics?

Varify does not currently offer a native Adobe Analytics integration. Organizations using Adobe Analytics typically also have GA4 running as a secondary tool, which works well with Varify. Alternatively, BigQuery integration can bridge the gap if Adobe data is exported to a warehouse.

Does switching analytics tools affect my existing experiments?

You can switch Varify's analytics integration at any time. New experiments will use the new analytics backend. Running experiments should be concluded before switching, as historical data stays in the original analytics tool.