VideosProduct TourShort narrated videos of the real platform, one feature at a time.Run head-to-head tests on copy, design, layout and timing. Pick a winner at significance, or let the AI re-balance the split every night — and read every result per audience, so you know who each version won for.
Test one element or every combination at once. Build whole landing pages and test them on your own domain. Then read the result in reporting that tells you what won, by how much, how sure, and for whom.
Hero copy, pricing pages, email subject lines, full personalization rules — run real tests on real traffic and let the data decide.
Test headlines, hero images, value props, and CTA copy on landing pages. Run multivariate combinations or simple A/B splits with built-in significance scoring.
Test pricing display, plan structure, payment flows, and trust signals. Segment by visitor type — new vs. returning, geo, source — so you don’t blow up returning revenue.
Test subject lines, sender names, hero blocks, and CTA copy. Open-time rendering means winning content stays fresh even after send. Auto-promote winner mid-campaign.
A/B test personalized vs. generic experiences on the same audience. Compare two personalization strategies head-to-head. Roll out with confidence, not faith.
The whole build in the panel — who takes part, what each version does, the goal that decides it, and the result read back by audience. Then run one on your own pages.
A/B for one decision, multivariate when several things change at once, and a holdout that keeps part of your traffic on the untouched site. Then two ways to decide: an experiment that ends with a winner, or an optimizer that never stops.
Shown to every visitor matching targeting, in any test group.
Your unchanged site — no A/B actions here. Campaign content still applies.
Decision strategy — how sure we should be before calling it. Higher = slower but safer.
| Version | Views | Clicked | Chance it is best | Current split | Recommended |
|---|---|---|---|---|---|
| Group A | 12.9k | 1.4% | 91.2% | 50% | 87% |
| Group B | 13.0k | 1.0% | 8.8% | 50% | 13% |
Views and clicks are decayed with a 28-day half-life, so recent traffic counts most. The recommendation keeps 10% of traffic exploring, so no version is ever starved of data. Scored nightly.
| # | Group 1 | Group 2 | Traffic | Visitors | Conv. rate | Lift vs control |
|---|---|---|---|---|---|---|
| C1 | Headline A | CTA green | 25% | 6,041 | 2.10% | control |
| C2 | Headline A | CTA red | 25% | 6,112 | 2.44% | +16.2% |
| C3 | Headline B | CTA green | 25% | 5,988 | 2.31% | +10.0% |
| C4 | Headline B | CTA red | 25% | 6,020 | 2.87% | +36.7% |
Which change did the work — not only which pair won.
Edit a live page directly — change copy, swap images, redesign CTAs — or build popups, banners, and forms from a library of templates. Every variant goes from idea to live in minutes, no devs.
Every test can decide in one of two ways, and most decide like this one: an experiment with an end, where the traffic stays as you set it and the winner has to earn the call. The thresholds are already set when you open a test, and they are stricter than the ones most tools ship with. No spreadsheets.
Tests ship demanding 98% confidence and a floor of 1,000 sessions before anything may be called a winner, plus a minimum runtime so a good Tuesday cannot win on Tuesday. Most tools ask for 95% and let you stop whenever you like.
Point the test at any of your twelve goal events, or at purchases per session, order value, clicks, bounce rate, pages per visit or time on site. A test that optimises for clicks and a test that optimises for revenue do not always agree — so you say which one you meant.
Set the smallest improvement you would actually act on, per goal. A variant that is ahead by a statistically real but commercially pointless margin does not get promoted, and does not get to waste a quarter of your traffic proving it again.
When the variant clears the confidence bar, the session floor, the runtime and your improvement rule, traffic moves to it — all of it, or the share you nominate, or none at all if you would rather keep the split and be emailed instead.
Variants are groups with a traffic percentage each. Give two variants 45% apiece and the remaining 10% see nothing at all — that is your control, and it keeps running for as long as the test does, so the lift you report is the lift you caused.
Before you launch, the editor shows you which other campaigns are aiming at overlapping audiences on overlapping pages. Two pop-ups arriving together is not a result, it is a collision — and you find out while you are still editing rather than from the numbers a fortnight later.
Some content is never finished — the hero banner, the seasonal offer, the block that runs all year. There is no winner worth calling, because the winner changes.
Switch the same test to AI: optimize continuously and it stops being an experiment. Every night the split shifts toward the version performing now, weighting recent traffic, moving only with statistical confidence, and always keeping 10% exploring so no version is starved of data. Nothing to declare, nothing to come back for.
Every test is also read audience by audience — the audiences Personyze discovered in your own data. The verdict says when they disagree, the report shows where, and the picks say what to do about it. Three ways it can go:
One snippet installs on Shopify, WordPress, Magento or a custom stack. From there Personyze reads the audience data you already collect, so a test can be split on who someone actually is — and writes the result back to the tools you already trust.
HubSpot
Salesforce
Segment
6sense
Tealium
Zoho
ZoomInfo
Google Tag Manager
Shopify
WordPress
Leadrebel
Segment
Tealium
GTM data layer
Klaviyo
Meta
TikTok
Amplitude
Mixpanel
ActiveCampaign
Brevo
MailchimpEvery test can fire its own event to the tools you already run, per campaign or as the account default — twelve destinations on one action. Five fire from the visitor’s browser and need that tool’s script on the page; the other seven send from Personyze’s own servers, whether or not the visitor is still on the site.
Per-variant lift, confidence intervals, segment breakdowns, and a clear decision criterion — so you can show exactly why a variant won and roll the call past skeptics.
The questions that come up before signing on. Send anything else our way and we’ll answer fast.
Visitors are split between versions on the traffic you set — 50/50 for a classic A/B, even slices for an A/B/n test, or 45/45 with 10% held out on the untouched site to measure the lift you actually caused. By default a visitor keeps the same version on every visit.
Then the test decides one of two ways. Pick a winner at significance: traffic stays as you set it, and when a version beats the rest on your goals at the confidence, session floor, runtime and minimum improvement you chose, it is promoted and the test concludes. AI: optimize continuously: there is no conclusion — every night the split shifts toward the version performing now, weighting recent traffic, moving only with statistical confidence, and always keeping 10% exploring. Either way the result is also read per discovered audience, so you see who each version won for.
Yes. AB testing, A/B testing and split testing are the same method: two or more versions of a page, popup or email go to comparable visitors, and the one that does better on your goal wins. Personyze is an AB testing tool that also runs multivariate tests — every combination at once — and reads each result per audience.
Pick a winner when you need an answer you will act on once: a redesign, a pricing layout, a checkout change. It runs a fair fixed split until one version proves itself, tells you the lift and how sure it is, and stops. You can defend that call.
Optimize continuously when the content is always-on and the right answer drifts: hero banners, offers, seasonal blocks, anything you would otherwise re-test every quarter. It never asks you to come back and declare anything; it keeps the split where the recent data says it should be, and keeps 10% exploring so it notices when that changes. Switch between them on the campaign at any time; the choice applies when you save. The long version, with the nightly pass step by step.
Each night the optimizer re-runs the test thousands of times in simulation from the data it has, and counts how often each version comes out on top. That share is its chance of being the true best; near-even numbers mean the data cannot tell the versions apart yet, and then the split stays put. The recommended split follows that chance, with 10% of traffic always divided evenly among the versions — so a losing version keeps earning the data that could redeem it, and a version that was best two months ago can still lose today. Views and clicks are decayed with a 28-day half-life, so recent traffic counts most.
You choose per test. Rotate users, the default: a visitor keeps the same version on every visit, right for funnels and anything measured over days. Visits: the same visitor can get a different version on each visit, for banner and headline tests where the impression is what is measured. Random: every page view picks afresh. No rotation turns the split off, so the groups are layers of content that all apply rather than competing versions.
The verdict does; the split, today, does not. Every test is scored inside each discovered audience separately — the rate per version, the leader there and how sure it is — and a campaign still serves one split to everyone. To act on a per-audience winner, target a copy of the campaign at that audience with its winning version; the campaign rule picker lists discovered audiences as a category. Serving a different split per audience automatically is on the roadmap.
No. Personyze is built to be no-code: the visual editor lets you change copy, swap images, redesign CTAs, or replace whole sections by clicking on them on the live page. Popups, banners, and forms are built from a 20+ widget template library — no engineering team required.
For the rare cases where you want bespoke logic (custom JavaScript, server-rendered variants, integrations with proprietary data) there\'s a JS action you can drop in and a REST API for server-side variant assignment. Most teams never need either.
Personyze A/B testing is fully platform-agnostic. It works on Shopify, Magento, BigCommerce, WooCommerce, Salesforce Commerce, WordPress, Webflow, custom React or Vue apps, Next.js, headless setups, and plain HTML sites. Integration is a single JavaScript snippet.
For server-side variants there’s a REST API. For email A/B tests, Personyze injects content at email-open time. And for data, Personyze plugs into your existing martech: Google Analytics 4, Mixpanel, Segment, HubSpot, Salesforce, Marketo, ActiveCampaign, and any tool with a REST API or webhooks.
The terms are used interchangeably — both describe splitting traffic between two or more variants and measuring which performs better. “A/B testing” is the more common phrasing for landing-page and CRO experiments; “split testing” is sometimes used to specifically describe URL-based tests where each variant lives on a different page.
Personyze handles both: same-page A/B variants via the visual editor, and full-page split tests where you redirect a percentage of traffic to a different URL. Multivariate (A/B/n) and holdout tests are also supported in the same UI — no separate tool required.
From a fresh account, most teams launch their first campaign in under 15 minutes: pick a template, choose a trigger, define the audience, hit publish. No code, no developer queue.
For more complex setups (custom CRM data, ABM IP lookups, multi-step flows) plan on a few hours or schedule a free implementation session with our success team.
No. The Personyze script is under 30KB gzipped, loaded asynchronously, and decisions are made in under 50ms. We don’t block render. Customers consistently report no measurable impact on Core Web Vitals after deploying.
Yes — every popup, bar and banner is built from standard HTML/CSS, so you can use the visual editor, or drop in your own custom HTML and inherit your site’s CSS. Though you rarely need to: Personyze offers to apply your brand to any template it shows you — your colours, your fonts and your language — so a design starts on-brand instead of being restyled into it.
Yes — native integrations for HubSpot, Salesforce, Mailchimp, Klaviyo, ActiveCampaign, and Marketo. Captures from popup forms can be auto-pushed to your CRM as new leads, with custom field mapping. Webhooks let you connect anything else.
Yes — testing is built into every capability rather than bolted on. Test recommendation algorithms against each other, pit popup offers and triggers head-to-head, and prove which landing page variants win for each audience.
Yes, and the report is built to say so. Every test is also read per discovered audience: the rate per arm inside the audience, the leader there, and the confidence of a disagreement with the overall leader, measured against the arm it disagrees with. A one-line verdict at the top of the results names the biggest audience that disagrees; the A/B tests by audience report lists every audience with enough traffic, with a conclusive-only filter. Membership is as of the pass that tagged the sessions, which the panel says in its tooltip.
Launch your first A/B test in 15 minutes. Real significance, real guardrails, no statistician on staff required.