A/B test documentation and analysis workbench
Problem
An indie maker running A/B tests on a small product wants to collect acquisition-flow data, see trends across variants, and document findings, but can't find a tool that handles tracking, analysis, AND documentation of experiments together. Existing platforms cover only the metrics side, leaving experiment knowledge scattered and unrecorded.
Opportunity
A lightweight experimentation journal that combines A/B test tracking, results analysis, and structured documentation of learnings, so small teams build a searchable archive of what worked and why instead of forgetting every concluded test.
Market analysis
The metrics side is a funded land-grab — Statsig, GrowthBook, and PostHog all bundle flags, analytics, and experiment results with generous free tiers — but the knowledge-management side is genuinely underserved for small teams: growth practitioners currently write entire blog series about hand-building experiment repositories in Notion. A lightweight journal that integrates with the metrics platforms instead of replacing them is the viable wedge.
Market · Indie makers and small growth teams running a few tests per month; discussion of 'experiment repositories' is trending in growth circles but tooling remains enterprise-shaped.
Pricing · Statsig and GrowthBook have free/open-source tiers, which anchors willingness to pay low; a documentation-layer journal could realistically charge $10-20/mo per team, with Notion templates as the free default.
Pros
- + The documentation gap is real and practitioners actively complain about it.
- + Complements rather than competes with Statsig/GrowthBook via API integration.
- + Fully solo-buildable as a CRUD-plus-search product with no heavy infra.
Cons
- − Metrics platforms could add a learning-library feature in one roadmap cycle.
- − Notion is the default free competitor and inertia is strong.
- − Indie makers' willingness to pay for documentation tooling is historically weak.
Existing / similar tools
- → GrowthBook ↗
- → Statsig ↗
- → PostHog ↗
Source
Hacker News (Ask HN)
The trap is building a journal that people have to remember to write in. Documentation tools die quietly when updating them is manual work, and a concluded A/B test is the moment of lowest motivation — the result is already known, the next test is waiting. The winning form factor is auto-capture: pull the numbers from Statsig or GrowthBook via API, auto-generate the summary and significance readout, and leave the human only the ‘why did this happen’ paragraph. If the archive fills itself, it compounds and becomes searchable institutional memory; if it needs discipline, it becomes another abandoned Notion template. Sell it as the layer that makes the team’s existing experimentation platform smarter, not as yet another place to log results.