Reach members when they're ready to buy — not when the calendar says so
Intent emerges in real time and expires fast. AI models each member's consumption rhythm and fires personalized outreach ahead of the most likely purchase moment, so the send matches the member instead of the planning cycle.
Campaigns run to the calendar, not the customer
Marketing cadence is set by planning calendars and promo windows, but customer readiness doesn't wait for the calendar — intent appears in real time and expires quickly. The average consumer belongs to 17 loyalty programs and engages with fewer than half. That silence usually isn't disinterest; it's communications arriving at the wrong moment for the member's current state, so a genuinely interested buyer gets a message a week after the window closed.
Model the rhythm, trigger the moment
AI agents learn each member's preferred consumption windows from their own behavior and trigger personalized outreach just ahead of the most probable purchase moment. The calendar stops driving the send: instead of one blast to everyone on Tuesday, each member is reached in their own window, with an offer matched to where they are in the lifecycle. Match the moment and the same audience buys more often.
How it works
The mechanics behind intent-triggered marketing.
Consumption-rhythm modeling
Agents model each member's individual dining or shopping rhythm — breakfast, lunch, dinner, late night; weekday vs. weekend; category cadence — from their transaction history rather than a segment average.
Highest-probability-moment trigger
Outreach fires ahead of the member's most likely next purchase, so the message lands while intent is live instead of after it has expired.
Per-member windows
Each member carries their own send windows and frequency caps, so the program reaches a whole base personally — one identity, one rhythm — without a single calendar broadcast.
McDonald's modeled individual dining rhythms (breakfast/lunch/dinner/late night) at 200M-member scale, lifting member GMV contribution to 85% and purchase frequency to 6.7 transactions/year.
Frequently asked
What data do we need before intent triggers work?
Transaction history and at least one digital channel to reach the member. From there the agents build per-member rhythm models — you don't need a separate data-science project, and the models sharpen as more behavior accumulates on the live member view.
How is this different from a scheduled drip or a birthday email?
A drip fires on a fixed clock for everyone; a birthday email fires on one known date. Intent-triggered marketing fires on each member's own predicted purchase window, which shifts as behavior changes — the trigger is the member's rhythm, not a shared calendar entry.
Does modeling 'rhythm' transfer outside Asian markets?
Yes — intent detection is a structural feature of data-driven growth, not a geography. The mechanic (model the individual window, trigger ahead of it) is the same in North America; channel fragmentation there actually raises the value of a unified per-member view.
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