For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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  • Getting Started
    • Welcome
    • Installation
    • Quickstart
    • How It Works
    • Janine in action
  • Dashboard
    • Overview
    • Analytics
  • Configuration
    • Thresholds
    • Channels
    • Email Domain Setup
    • Janine AI Agent
  • Knowledge Base
    • Managing Documents
  • Checkout Agent
    • How It Works
    • Hesitation Detection
    • Cross-Merchant Intelligence
  • Lifecycle Agent
    • Overview
    • Pre-Purchase Nurturing
    • Post-Purchase & Winback
  • Storefront Chat
    • Overview
  • Billing
    • Pricing Model
    • Plans
  • Support
    • FAQ
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On this page
  • What it does
  • Example
  • How it decides when to follow up
  • Why it works
Lifecycle Agent

Pre-purchase nurturing

Following up with context, not templates.
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Post-purchase & winback

Cross-sells, review requests, and re-engagement after the first purchase.

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Built with

The Lifecycle Agent is available on the Enterprise plan.

What it does

When a visitor browses your store, looks at products, and leaves without buying, the Lifecycle Agent remembers what they looked at. If they come back, Janine has context. If they don’t, she follows up.

This is different from a welcome drip. A welcome drip sends the same 5 emails to every subscriber regardless of what they did on your site. The Lifecycle Agent sends messages based on actual browsing behavior.

Example

A visitor spends 4 minutes on a specific product page, adds it to their cart, then leaves. Two days later, Janine follows up:

“Hey — I noticed you were looking at the Trail Runner Pros the other day. Still thinking about them? Happy to answer any questions about sizing or fit.”

Compare that to a generic welcome email that says “Thanks for signing up! Here’s 10% off your first order.”

How it decides when to follow up

The Lifecycle Agent tracks engagement signals: time on page, products viewed, cart additions, return visits. It uses these signals to decide:

  • Whether to follow up at all (a 3-second bounce isn’t worth a message)
  • When to follow up (same day, next day, a week later)
  • What to say (mention the specific products they looked at)
  • Which channel to use

Why it works

People respond to messages about things they actually looked at. A follow-up that references the specific product someone spent time on gets opened. A generic “Thanks for signing up, here’s 10% off” gets ignored. The difference is context.