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A/B & multivariate testing

A/B & multivariate testing that proves the winner.

Run rigorous experiments across pages, products, and pricing without writing code. Bayesian stats, segment-aware verdicts, and revenue lift — not just CVR. Our AI reads every result, flags the winner, and tells you why — in plain English.

A/B test results — Variant A control 2.84% CVR vs Variant B winner 3.62% CVR, +28.6% revenue lift, AI explains why B won

Any test type, one editor

A/B, A/A, multivariate, split-URL, and redirect tests share a single visual editor and stats engine.

Segment-aware verdicts

See which audience is actually moving the needle. Per-segment significance and lift, not just topline.

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Revenue, not just clicks

Tie experiments to orders, AOV, refund rate, and LTV. Stop optimizing vanity metrics.

Stats engine

Bayesian by default. Frequentist on tap.

Most teams just want to know: "Did B win, and by how much?" We answer that in plain English. Power users can switch to frequentist with full p-values, effect size, and MDE planning.

  • Sequential testing — peek without inflating false positives
  • Auto sample-size calculator built into every test
  • SRM (sample ratio mismatch) detector flags broken splits
Verdict
Updated 12 min ago
B is the winner
B beat Control with 98% probability. Expected revenue lift: +27.4%. Safe to promote to 100% traffic.
P(B>A)
0.98
Expected lift
+27.4%
Loss risk
$112/wk
Experiment splits by segment
🌐 Returning · India · Mobile42.1k+34.2%
🎯 First-time · US · Desktop28.4k+18.9%
💸 Cart $50+ · All regions14.9k+11.2%
🌙 Returning · EU · Tablet3.2k−4.1%
💡 Insight: Winner is concentrated in IN mobile. Consider rolling out only to that segment first.
Segments

Where exactly is the lift coming from?

Slice every experiment by 40+ pre-built segments — geo, device, traffic source, cart value, returning vs. new — or bring your own from Segment, RudderStack, or GA4.

  • Per-segment confidence intervals
  • Auto-detected "winning segments" in every report
  • Roll out to a segment, hold the rest as control
CustomFit felt like swapping clunky boots for running shoes. More tests, bolder personalization, results in front of us.
AS
Ankit Shard
Associate VP, E-commerce · Bellavita
+11%
Conversion rate within 60 days
+15%
ROI on experimentation spend
Test velocity vs. prior tool
One engine, every method

Run any test type without switching tools

The same Bayesian + frequentist engine powers every experiment — pick the method that fits the question.

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A/B & A/B/n

Classic head-to-head on one or more variants.

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A/A validation

Prove your setup is unbiased before you trust a result.

🎛

Multivariate

Test combinations of elements to find the best mix.

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Split-URL

Compare entirely separate pages or redesigns.

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Multi-page / funnel

Hold a variant across a whole journey, not one page.

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Server-side

Experiment below the page for pricing, logic & APIs.

The fundamentals

What is A/B & multivariate testing?

A/B testing shows two or more variations of a page or element to different visitor segments to learn which converts best; multivariate testing varies several elements at once to find the winning combination. Both let you replace opinion with evidence — so every change you ship is one you’ve proven lifts revenue.

Quick facts

A/B compares whole variations; MVT tests element combinations
Winners are decided on statistical significance, not gut feel
Run client-side, server-side, or split-URL from one editor
Every test reports revenue per visitor, not just clicks
Why it matters

Why A/B & multivariate testing matters for D2C

🎲

Stop guessing

Most "best practices" don’t hold for your store. Testing tells you what actually works on your traffic.

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Protect revenue

A losing redesign shipped to everyone is expensive. Testing contains the risk to a slice of traffic.

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Compound wins

A steady cadence of small, proven wins compounds into outsized revenue growth over a year.

Who it’s for

Built for your whole growth team

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Growth & CRO teams

Run a high-velocity testing program without engineering bottlenecks.

✍️

Marketers

Test copy, offers, and layouts yourself — no code, no tickets.

🧑‍💻

Developers

Server-side and API testing for pricing, logic, and checkout.

The complete guide

Understanding A/B and multivariate testing

A/B testing (split testing) compares two or more versions of a page or element to learn which drives more conversions, while multivariate testing varies several elements at once to find the winning combination. For D2C and ecommerce brands, A/B testing replaces opinion with evidence — every headline, price, image, layout, and CTA change is validated on real traffic before it ships to everyone.

CustomFit.ai runs client-side, server-side, and split-URL experiments from one visual editor, with a statistical engine that reports both Bayesian probability-to-beat-baseline and frequentist significance. Crucially, every test is judged on revenue per visitor and AOV — not just click-through — so a variant that lifts conversions but quietly erodes margin is caught by guardrail metrics.

A disciplined A/B testing program compounds: a steady cadence of small, proven wins adds up to outsized revenue growth over a year. With AI-assisted idea generation, no-code variant building, and autonomous traffic allocation, CustomFit lets growth teams ship more experiments per week without engineering bottlenecks.

What is the difference between A/B and multivariate testing?

A/B testing compares whole variations of a page; multivariate testing varies several elements simultaneously to find the best-performing combination. Use A/B for big, distinct changes and multivariate when you want to understand how individual elements interact.

How long should an A/B test run?

Until it reaches statistical significance for your traffic and effect size — typically 1–2 weeks for most D2C stores. CustomFit shows a live significance readout so you know exactly when a result is trustworthy.

Does A/B testing hurt SEO?

No. CustomFit serves variants over your canonical pages with no cloaking, so search engines index your primary content while you test.

How long until I get a verdict?

Most ecom A/B tests reach statistical confidence in 7–14 days at typical traffic. CustomFit shows you the live probability-to-beat and the minimum sample needed, so you'll know exactly when you can call it.

Will the editor break my theme?

No. Variants are layered on top of your live theme via our SDK — never edited in your repo. Rollback is instant, and Core Web Vitals stay green thanks to edge evaluation.

Can engineers run code-based tests too?

Yes. Visual edits live alongside JS/TS variants, server-side flag evaluation, and custom-event tracking. The same stats engine evaluates both.

Does it work without flicker?

Edge-side variant resolution means the right version renders on first paint, so your LCP and CLS metrics stay clean.

Do I need a developer to use CustomFit.ai?

No. Marketers build experiments in a no-code visual editor; developers can use the API and SDKs when they want deeper control.

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Mamaearthfree-shipping band +12.4% AOVGIVAfestive collection page +34% revenueBellavitaPDP CTA test +27.4% CVRKapivaQuiz-driven recs +9.48% CTRThe Sleep Colanding personalized 2× capturesPlumReturning shopper swap +18.2% CVRMamaearthfree-shipping band +12.4% AOVGIVAfestive collection page +34% revenueBellavitaPDP CTA test +27.4% CVRKapivaQuiz-driven recs +9.48% CTRThe Sleep Colanding personalized 2× capturesPlumReturning shopper swap +18.2% CVR