Do I need a developer to set up an experiment?

No. The visual editor lets you change content, layout, and copy directly on the page without writing code or opening a deploy pipeline. For logic-level tests (pricing, feature flags, backend variants), Intempt connects to your product events directly.

How do experiment winners connect to personalization?

When an experiment reaches significance and you select a winner, you can promote it to a Personalize rule in one click. The winning variant becomes a live personalization rule targeting the same audience - no separate setup required.

Can I target experiments to specific segments?

Yes. Any Intempt segment can be the audience for an experiment: RFM cohorts, behavioral groups, acquisition source, plan type, or any combination. Segment-level targeting lets you run the same experiment against different audiences and compare results.

How does Intempt Experiments differ from Optimizely?

Optimizely is a standalone experimentation tool. Intempt Experiments runs on the same behavioral data layer as your segments, journeys, and personalization. You can target experiments by product behavior, promote winners to live rules, and attribute experiment results to revenue - all without a separate analytics integration.

Experiments

You've shipped 'winners' that were never significant.

You test the page in one tool and send the email in another, so no result ties back to revenue. Here the Experimentation Lead agent checks sample size before a test ships. That guardrail catches 82-88% of underpowered tests, and bandits then route traffic to the real winner live.

Start for free

Run 3x more experiments on the same traffic

0.0on G2

10B+events

500M+users

7+years profitable

50+enterprises

Set up an A/B test without opening a ticket No deploy needed.

Change content, layout, copy, and logic directly on the page. The visual editor lets non-technical teams run experiments without waiting on engineering.

Any element, no codeSet up an A/B or multivariate test on any element on the page.
Target on any attributeSegment, acquisition source, plan type or anything else you track.
Preview before launchSee exactly what each audience gets before any traffic is assigned.

Learn more about Visual editor

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

Reach significance 3 weeks faster on the same traffic Same traffic, faster answer.

CUPED variance reduction uses pre-experiment behavioral data to cut the time you need to reach statistical significance by 20-40%. More experiments shipped. Fewer wasted weeks.

CUPED variance reductionUses each user's pre-experiment history, so significance arrives on fewer sessions.
Thresholds set per experimentChoose the acceptable risk for each test rather than inheriting one default.
Sequential testingWatch results as they come in without inflating the false-positive rate.

Learn more about CUPED

Reach significance faster on the same traffic

Test content, logic, and pricing - not just button color Go deeper.

Most A/B tools stop at the UI layer. Intempt experiments connect to product events, pricing logic, and backend feature flags, so you can test what moves revenue and trace the winner back to the email or journey that sent the traffic.

Tests reach past the pageProduct flows, pricing tiers and feature availability, not only copy and layout.
Product events are the metricThe same events that trigger the test are the ones that measure it.
Winners promote in one clickThe winning variant becomes a Personalize rule without being rebuilt.

Learn more about Test depth

Intempt vs the experimentation tools

Optimizely is the deeper testing product. The rows below are about what the winning variant is allowed to do next.

CapabilityIntemptOptimizelycompare

Client-side testing

Visual editor and front-end experiments

Included

Best in class

Server-side testing

Flags, rollouts and remote config

Included

Best in class

Stats engine

Variance reduction and sequential testing

CUPED

Stats Accelerator

Email and SMS testing

Running the same experiment in a message

Included

Not offered

In-app and push testing

Experiments inside the product

Included

Not offered

Customer profiles

Who the visitor actually is

Included

Visitor IDs only

Product analytics

Funnels and retention on the same events

Included

Separate tool

Revenue attribution

The test result tied to closed revenue

Included

Test metric only

Winner triggers the next step

Shipping the result into a journey or a send

Included

Not offered

Who operates it

Who has to be on staff for the tool to pay off

No dedicated team required

A dedicated optimisation team

Pricing model

How the bill moves as you grow

On demand, no overage

Annual contract

Every claim above is argued in full, with what they do better, on the linked pages.

Wired into the toolsyour team already opens.

Slack, Stripe, Twilio, SendGrid, Gmail, Google Calendar, Firebase, Apache Kafka, AWS. Blu Agent operates them for you without a browser tab.

See the full list

In the words of50+ live tenants.

“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

“Intempt helped us turn real browsing and purchase signals into personalized experiences that drive repeat buying. We finally have one system that sees the whole customer journey.”

Eric Gardner

COO, FieldsUSA

“With Intempt, we built a signal-led pipeline driven by real behaviors. Follow-ups are triggered by intent signals instead of timelines, so we only focus on users who are truly engaging.”

Tadas Kertenis

Co-founder, Hoperfy

Frequently askedquestions.

Everything you need to know about Intempt Experiments.

01 / 06

What is CUPED and how does it help?

CUPED (Controlled-experiment Using Pre-Experiment Data) uses pre-experiment behavioral data as a covariate to reduce variance in your metric. The practical result: you reach statistical significance 20-40% faster on the same traffic. Instead of waiting 3 weeks for significance, most teams hit it in under a week.

CUPED (Controlled-experiment Using Pre-Experiment Data) uses pre-experiment behavioral data as a covariate to reduce variance in your metric. The practical result: you reach statistical significance 20-40% faster on the same traffic. Instead of waiting 3 weeks for significance, most teams hit it in under a week.

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).

Intempt Marketing

Run 2 experiments a week, not 2 a quarter.

Connect your data source and your first experiment is live in the same session. CUPED is on by default - reach significance faster from day one. You hold the strategy layer: what to test and what a win is worth. The Experimentation Lead agent runs the play and holds anything underpowered before it ships. No consultant, no stats team.

Start for free