All use cases

Upsell & Cross-sell

Post-purchase upsell with holdout proof

The order just confirmed — the warmest moment to recommend what goes with it, and every dollar of lift is proven against a control group.

Close the loopNext best thingBehavioral triggerTime-based triggerChatEmailIn-appSMSE-commerce & Retail

What it does

The minutes after a purchase are the highest-intent window a brand ever gets, and most companies spend it on a transactional receipt. The agent uses that window to recommend complementary products and services — accessories in the receipt thread, a lesson pack to go with new gear, a contextual offer the day after a service visit. And because post-purchase upsell is usually a guess dressed up as a result, every eligible customer is randomly split against a holdout: the revenue you see is the lift the agent actually created, not the purchases that would have happened anyway.

How it works

  1. 1
    Trigger. an order_confirmed event arrives, or a time-based follow-up window opens (the day after delivery, after a service appointment).
  2. 2
    Decision. the agent picks the complementary product or service from the catalog, the order's contents, and the customer's memory — then a judge gates the message for relevance and policy. A slice of eligible customers is held out and receives nothing.
  3. 3
    Action. the recommendation lands in the receipt thread or as a follow-up on the customer's channel (chat, email, in-app, SMS) with a one-line reason tied to what they just bought; purchases run through the client's own secure checkout hand-off.
  4. 4
    Follow-through. accepted and declined offers are written back to memory; if the customer returns the order or opens a complaint, any queued upsell is cancelled. Lift is reported as the delta between treated and holdout groups.
Example
AgentOrder confirmed — your racket ships tomorrow. One thing new racket owners usually wish they'd added: a lesson pack to break it in properly. Want to see the options?
CustomerHow much is the starter pack?
AgentHere's the starter pack with current pricing on a secure checkout page — sessions are bookable whenever suits you, and your racket order isn't affected either way.

Configuration

How the agent is wired for this use case.

Triggerorder_confirmed event from the OMS, or a time-based follow-up window opening (day after delivery, after a service visit)
Tools & actions
  • OMS / commerce platform · read order contents; subscribe to delivery, service-visit, and return/complaint events
  • Product & service catalog · resolve the complement matched to the order
  • CRM / memory store · read customer memory and consent; assign holdout vs treated; write back accept/decline and report lift
  • Messaging channel · deliver the recommendation in the receipt thread or as a channel follow-up
  • Hosted checkout · hand off the purchase to the client's own secure payment page
Autonomymessage selection and send run unattended behind a relevance/policy judge with randomized holdout assignment; the purchase itself is money-moving and completes only through the client's hosted checkout on explicit customer action
Channelschat · email · in-app · sms
Escalationno automated handoff; a return, refund, or open support issue suppresses any queued upsell, which routes the customer back to the client's existing support path

What you need

The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.

Signals

order_confirmed, delivery and service-visit events, return/complaint events for cancellation

Data

order contents, product and service catalog with complement mappings, customer memory, channel consent state

Guardrails

judge gating on every unprompted message; randomized holdout assignment; frequency caps per customer; automatic suppression on returns, refunds, or open support issues

Metrics it moves

  • attach-rateup, by putting the right complement in front of the customer at peak intent
  • aovup, measured per order across treated customers
  • revenue-per-conversationup, and reported as holdout-proven incremental lift rather than gross attributed revenue

Related use cases

Upsell & Cross-sell

Second sale inside the support conversation

the same upsell muscle inside a support thread

Upsell & Cross-sell

Complete-the-kit cross-sell

closes the basket gap before the order instead of after

Prevent / Care

Post-resolution follow-up

the care-first version of the day-after touch

See it on your own customer journey

Bring one drop-off, one churn cliff, or one silent segment. We will show you what a proactive agent with memory and judgment does with it.

Book a demo