Guide: build an abandoned-cart journey in WeZend, step by step
A concrete walkthrough using the real node types and the built-in cart-recovery template — not a conceptual overview.
This is a hands-on build, not a concept explainer. By the end you'll have a live journey that recovers abandoned carts across email and SMS.
1. Start from the built-in template
Journeys are graphs of nodes — you don't have to design one from a blank canvas. List the ready-made templates:
curl https://api.wezend.com/v1/journeys/templates \
-H "Authorization: Bearer $WEZEND_JWT"
The response includes cart_recovery: triggered on add_to_cart, with a 60-minute delay, a 50/50 A/B split between an email and an SMS reminder, and a purchase goal. That's your starting graph.
2. Fire the trigger event
The journey only starts once the platform sees the event it's listening for. From your storefront (server-side, or client-side via the public tracking endpoint):
curl -X POST https://api.wezend.com/v1/events/track \
-H "Content-Type: application/json" \
-d '{
"public_key": "pk_live_...",
"event": "add_to_cart",
"customer_ref": "cus_8823",
"properties": { "sku": "DK-1180", "qty": 1, "value": 499 }
}'
See Tracking events for the full field reference.
3. Customize the copy
The template's send nodes ship with placeholder copy ({{first_name}}-style merge fields) — edit the email subject/body and SMS body in the builder before activating. Nothing about the trigger, delay or split logic needs to change unless your funnel is unusual.
4. Test with one real profile
Before opening the gates, run .../test-enroll against a real (test) profile and confirm it lands in the email branch, the SMS branch, or exits via the goal — exactly as designed — with real merge-field data, not a preview stub.
5. Activate, then watch the goal rate
Turn the journey on. GET /v1/journeys/:id/stats reports how many profiles entered, how many hit the goal (purchase), and the split between branches — your actual cart-recovery lift, not an estimate.
Going further
Once this is live, the same pattern extends to a win-back journey for lapsed customers, or a churn-risk journey fed by a computed trait instead of a raw event — see Building a journey for the full node reference.