Most
Most product teams never run an A/B test
Designing a rigorous test loses to shipping.
Experimentation
Test that idea with guardrails
Hypothesis in. Instrumented test with rollback out.
The category
Arvad designs sample size, instrumentation, and rollback in the same workspace so the readout is a decision you can act on, not only a dashboard screenshot.
Plain-English hypothesis becomes variants, metrics, MDE, and sample size.
Variant code ships as a PR behind GrowthBook or Statsig flags.
Guardrails on revenue, latency, and errors, with auto-rollback on breach.
Sequential analysis and a plain-English decision memo on the same build record.
The gap
Why experimentation stays a slide in a deck
Everyone wants to be data-driven. Few teams have spare capacity to run rigorous tests.
Hard
Statistical validity is hard
Sample size, power, MDE, peeking. Wrong tests create confident wrong decisions.
Risk
Eng leads veto prod experiments
Without guardrails, a bad variant can hurt revenue quietly.
Glue
Flags exist; the rest is glue
Flags platforms do not write variants, instrument metrics, or design rollback.
The whole loop, not only the flag
The experimentation pipeline most teams never finish, wired into GrowthBook or Statsig.
Hypothesis → design
One-line hypothesis becomes variants, primary/secondary metrics, MDE, sample size, duration.
Stays in the workspace with plan and checks
Variants written for you
Variant B as a real PR behind the flag, with metric instrumentation.
Stays in the workspace with plan and checks
Statistical rigor
Bayesian and frequentist methods, sequential testing, multiple-testing correction.
Stays in the workspace with plan and checks
Segmentation
Stratified randomization by plan, geography, device, signup date.
Stays in the workspace with plan and checks
Guardrails
Revenue, latency, error rate, and KPIs you pick. Cross a guardrail and auto-roll back.
Stays in the workspace with plan and checks
Rollback
Every experiment ships with a tested rollback path before go-live.
Stays in the workspace with plan and checks
Results in plain English
Decision memo: what shipped, what moved, what to do next.
Stays in the workspace with plan and checks
GrowthBook & Statsig
Bring GrowthBook or Statsig. Arvad designs, writes, and analyzes; flags stay where your data team trusts them.
Stays in the workspace with plan and checks
DIY experiments vs Arvad
DIY experimentationArvad experimentation
Arvad sits where the thread keeps the plan, staging, spend, and checks.
| Capability | DIY experimentation | Arvad experimentation |
|---|---|---|
| Time to first experiment | Weeks | Days |
| Variant code | Engineering ticket | PR behind a flag |
| Guardrails | Optional | Required, with auto-rollback |
| Stats | Ad hoc | Sequential, multi-test-corrected |
| Report | p-values in Slack | Plain-English decision memo |
| Platform | You build glue | GrowthBook / Statsig native |
Hypothesis Monday. Result when the data says so.
Write one line, approve the design, ship instrumented variants behind a flag, decide from a memo.
Write one line, approve the design, ship instrumented variants behind a flag, decide from a memo.
01Write the hypothesis in one line
02Approve the design
03Ship variants behind the flag
04Run, watch, decide
Hypothesis to decision memo, end to end01 / 04
WRITE
YOUR
HYPOTHESIS
One line, plain English. “I think a softer CTA on the pricing page will lift trial-starts.” Arvad turns it into a structured proposal you can edit, no template, no PhD required.
Plain English in
Structured proposal out
Editable on the spot
No template
Scroll
What makes eng leads comfortable
All
Every variant ships with a tested rollback
Rollback path tested before go-live.
Sequential
Sequential analysis
Call the test when the data supports it.
≤ SLA
Latency guardrail
Breach triggers auto-rollback.
2
Two platforms on day one
GrowthBook and Statsig.
Straight answers
Limits stated plainly. No demo theater.
One question
When the build finishes, can you show a teammate the plan, preview, tests, and deploy status without digging through chat?
If you cannot, you still have a chat log. Arvad keeps that work in one workspace.
Keep exploring
Ship the experiment. Keep the readout.
Hypothesis, variants, guardrails, and decision in one place.