The Lifecycle Marketer agent personalizes every visit on one customer context, so the page reacts to what someone actually did in your product. No second tool to stitch behavior to content.
0.0on G2No code required. Personalization starts the moment behavior is tracked, and every rule you write is a guardrail the agent works inside.
Open the visual editor, point and click on any element, and define what different visitors see. Hero text, banners, CTAs, product showcases - all personalized based on rules you set. You hold the strategy layer, the Lifecycle Marketer agent applies it on every visit.
A visitor who bought three times sees different content than someone visiting for the first time. Behavioral targeting reads behavior in real time, not on a schedule - the same product events your analytics reads, with no export to a second tool first. Targeting runs as a standing skill on every tracked event.
Create a specific experience for trial users, paid customers, VIP buyers, at-risk churners, or any segment you define. Content, banners, and CTAs swap automatically. Each segment rule runs as a standing play against the same customer context every Blu agent reads, so you define it once and it holds for every visit after.
Three outcomes teams measure from day one.
Slack, Stripe, Twilio, SendGrid, Gmail, Google Calendar, Firebase, Apache Kafka, AWS. Blu Agent operates them for you without a browser tab.
“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
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).
Connect your sources in minutes. Ship your first personalized experience and measure lift the same day. Nothing goes live until you publish it.
