Tools to track A/B tests

The problem, in plain words: “I need a single place to track all A/B tests across multiple clients, including hypotheses, results, and learnings.”

Client Notes fits best, with 2 more that fit too.

You need a single, shareable repository to record hypotheses, experiment setups, results, and learnings across many client accounts.

Updated July 2026.

What fits

Client Notesstrong · 86

Built for consultants and freelancers to keep each client in one place with per-client timelines, notes, searchable records, AI summaries, and export options—this directly supports a central, shareable experiment history per client.

Best for: Independent consultants and small agencies who want a client-organized repository with notes, timelines, and easy exports for sharing learnings.

Caveat: Designed as a client-focused CRM for one-on-one relationships, so experiment-specific analytics and statistical tooling are not the main focus.

PostHogstrong · 80

PostHog combines product analytics and experiment management so you can record experiments, link results to events/metrics, and keep experiment histories alongside product data—useful when you want experiments tied to tracked metrics and user behavior.

Best for: Consultants who want experiments recorded alongside event analytics and results tied to concrete product metrics.

Caveat: Positioned primarily for product and developer teams, so multi-client or agency-style separation may need deliberate workspace or project setup.

GrowthBookstrong · 78

GrowthBook is an experimentation and feature-flagging platform whose core purpose is running and documenting A/B experiments and their metrics, which maps directly to keeping hypotheses, results, and learnings in one place.

Best for: Teams or consultants who run experiments tied to feature flags and want experiment definitions and results stored with metric tracking.

Caveat: Framed for product and developer teams, so using it as a multi-client repository may require per-client projects or an organizational pattern you set up.

Partly fits

Survicate Insights Hubpartial · 56

Centralizes user feedback from many sources and extracts insights, which helps capture learnings related to experiments but is focused on feedback rather than a full experiment repository.

Won’t cover: Acts as a feedback-aggregation and insight tool rather than a dedicated experiment tracker that records hypotheses, variations, and statistical results across clients.

ClientSignalpartial · 52

Automates white-labeled client reporting by pulling marketing data into scheduled reports, which helps sharing results with clients but doesn't serve as a centralized experiment repository.

Won’t cover: Generates scheduled reports from connected ad and analytics sources but does not function as a searchable, hypothesis-first experiment database across multiple clients.

A/B Test Significance Calculatorpartial · 45

Provides quick statistical checks for experiment results so you can validate outcomes, which complements a repository but does not itself store hypotheses, learnings, or multi-client history.

Won’t cover: Only evaluates statistical significance and does not offer experiment organization, per-client records, or a learnings log.

ConvertCROpartial · 45

An AI conversion assistant that audits pages and helps run A/B tests, which assists with generating experiments and analysis but is focused on site-level CRO rather than cross-client experiment documentation.

Won’t cover: Oriented toward running and analyzing CRO experiments on sites rather than serving as a cross-client, searchable experiment archive with hypothesis and learnings fields.

Questions

What's the best tool to track A/B tests?

Client Notes is the strongest match — Built for consultants and freelancers to keep each client in one place with per-client timelines, notes, searchable records, AI summaries, and export options—this directly supports a central, shareable experiment history per client. One caveat: designed as a client-focused CRM for one-on-one relationships, so experiment-specific analytics and statistical tooling are not the main focus.

Is there a tool that fully solves this?

3 products match this closely.

What won't these tools cover?

Acts as a feedback-aggregation and insight tool rather than a dedicated experiment tracker that records hypotheses, variations, and statistical results across clients. · Generates scheduled reports from connected ad and analytics sources but does not function as a searchable, hypothesis-first experiment database across multiple clients. · Only evaluates statistical significance and does not offer experiment organization, per-client records, or a learnings log. · Oriented toward running and analyzing CRO experiments on sites rather than serving as a cross-client, searchable experiment archive with hypothesis and learnings fields.

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