Hangworkshop
step 4 · verde cantina · lapsed

Review the output, then ship

See exactly what one guest receives, then push the file to your email platform and schedule per-guest sends.

What one guest receivesexample output
Subject
Marcus, your $5 off your next $20+ order is waiting at Verde Cantina
Send
Tue, Jun 9, 2026 · 5:00 PM (local)

Hi Marcus,

Taco Tuesday hasn’t been the same without you and the crew — so here’s $5 off your next $20+ order at Verde Cantina, this week only.

[ Order now → ]

Your reward is already loaded in the Verde Rewards app. See you soon.

— The Verde Cantina Team

Offer valid through Sunday. Minimum $20 subtotal. One redemption per member.

Why this message

Tuesday tickets run 3–4 taco plates in a single order — clearly feeding a group. The hook leans on that standing Tuesday taco run, not the discount.

Why this send time

Those Tuesday orders land ~6:30 PM, so 5:00 PM reaches them while the group is still deciding where dinner’s coming from.

Every row carries both rationales, citing the guest’s actual orders — so any send is auditable, never a black box. Skim a handful before you ship.

Ship it in your email platform

The upload CSV drops into any customer-engagement / email platform — Klaviyo, Braze, and the like. The steps are the same everywhere:

  1. 01

    Import & map

    Create a list or segment, upload the CSV, and map the columns: email and first_name to their standard fields, and personalized_message_part, send_date, send_time (plus the rationales) to custom profile properties.

  2. 02

    Wire the message with a fallback

    Drop the personalized field into the email body with a safe default, so anyone missing a value still gets a clean line.

  3. 03

    Schedule per-guest sends

    Send each guest at their own send time. Best: a flow / Canvas that waits until each profile’s send_datetime_local, then sends. If your platform doesn’t support that, segment by send slot and schedule a send for each.

You just turned one offer into twenty-five thoughtful, on-brand messages — each timed to the guest, each drawn from their real ordering history — while only ever approving the rules, not every message. Do it continuously, across every channel and every guest, and that’s the whole idea behind a CDP + AI.

Presented at
Restaurant Marketing Workshop