UI tests are surface-level changes—headlines, images, button colors, layout tweaks. Deeper logic personalization means things like showing different pricing, changing product recommendations based on behavior, or altering checkout flows. Intempt handles both (full-stack), so you're not limited to cosmetic changes.

Pretty granular. You can target based on real behavior (pages viewed, actions taken), lifecycle stage (new visitor, active user, at-risk), campaign source, or AI-predicted intent (likely to convert, churn risk). Combine conditions to get as specific as you need.

Traditional A/B tests make you wait until the end to draw conclusions—or risk false positives if you peek early. Sequential testing lets you monitor results continuously with statistical safeguards built in. You can act on clear winners sooner without inflating your error rate.

CUPED uses historical data about your users to reduce random noise in test results. Less noise means a cleaner signal, which means you hit statistical significance much faster. You're not waiting extra weeks just because your audience has high natural variability.

It works across both web and mobile from one platform. You build experiences and run experiments across web and mobile apps without duplicate work. Same targeting logic, same reporting, same workflows, just deployed wherever your users are.