Intempt
A/B Testing

You can't optimize what you're not testing.

Intempt runs web, mobile, and server-side tests with CUPED variance reduction, cutting time to statistical significance* so you can run more tests per quarter on the same traffic.

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G2
4.5on G2
Trusted by GTM teams
StockInvestFieldsUSAHoperfy

Experiments that run faster and teach you more.

Test without a developer. Win by segment. Make it permanent.

No-code A/B test setup with a visual editor.

Click on any element on your page. Set what variant B looks like. Define your success metric. Launch. No code required.

  • Point-and-click variant creation for any page element
  • Traffic split and holdout group controls
  • Preview variants before launch across device sizes

Visual A/B Test Editor

No deploy needed
Homepage Hero
Current

Control

Variant B

Traffic split

50% / 50%

Conversion to purchase

Reach significance faster on the same traffic.

Standard A/B tests need a lot of traffic and a lot of time. CUPED uses pre-experiment behavioral data to reduce variance, meaning your tests reach significance 20–40% faster* without inflating false positive rates.

  • CUPED applied automatically to all eligible experiments
  • Faster time to significance without compromising statistical rigor
  • Sequential testing mode to avoid peeking inflation

Time to significance

CUPED active

Without CUPED · 45 days

With CUPED · 18 days

40% faster

Same significance threshold. No false positive inflation.

Verified
Pre-experiment covariate adjustment reduces variance

Test deeper than just the UI.

Some of your most important experiments aren't visual. Intempt's server-side experiments let you test pricing, feature access, recommendation logic, and backend behavior with the same statistical rigor as front-end tests.

  • Choose API for server-side experiment assignment
  • Mobile A/B tests for iOS and Android
  • SDK-level experimentation for native app experiences

Segment-level analysis

Subgroup winners found

Overall test result

No winner

2.8% vs 3.0% (p=0.12) — not significant

Segment breakdown

Paid social visitors

+41% CVR

Organic search

+8% CVR

Email visitors

-3% CVR

Promoting winner for: Paid Social

Winning variants promoted to personalization rules.

When your A/B test produces a clear winner, you don't need a new deploy or a ticket to engineering. Intempt promotes the winning variant to a personalization rule for the winning segment permanently.

  • One-click promotion from test to personalization rule
  • Segment-specific winners for different audience segments
  • Full experiment history and documentation for every test

Conversion by acquisition channel

Organic Search

4.8% CVR

Email nurture

3.2% CVR

Paid Social

0.9% CVR

Build your test queue around revenue, not volume

Use cases built for the metrics that matter.

Three outcomes teams measure from day one.

Customer LTV scoring and churn prevention

Connect every trusted source.

Plug into the tools your team already runs on.

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Certified & Compliant

Shopify Plus Certified App
HubSpot App Partner
Stripe Partner
AICPA SOC 2 Certified
GDPR Compliant

Your customer data stays yours, and stays secure.

The teams that made the switch

Jim Stromberg
StockInvest
01 / 03
We were losing visitors before they signed up. Intempt's personalized experiences changed that - we started meeting people where they were instead of guessing. Once they're in, Intempt's automated email takes over and keeps the relationship moving. Acquisition and retention finally feel like one connected motion instead of two separate problems.

Jim Stromberg, CEO

StockInvest

Case Study

StockInvest needed to turn anonymous traffic into registered users before any retention strategy could work. With Intempt's Experiences, they personalized the anonymous visitor flow, surfacing the right content and CTAs to boost signup conversion. Once users signed up, automated Journeys nurtured them through onboarding and deeper engagement, steadily increasing lifetime value.

FAQ

Frequently asked questions

With CUPED, significantly less than standard tools. We recommend at least 1,000 unique visitors per variant per week as a starting baseline.

Sources

* CUPED (Controlled-experiment Using Pre-Experiment Data) achieves 7–45% variance reduction depending on covariate selection. Deng et al. (Microsoft Research, 2013); Eppo, Statsig documentation (2024–2025). The 20–40% figure reflects typical production deployments.

Your first test, live this week.

Connect your site, build your first variant in the visual editor, and launch without touching your codebase.

Intempt - Agentic Growth Platform for Marketing & Sales