Post-purchase & winback
Cross-sells, review requests, and re-engagement after the first purchase.
The Lifecycle Agent is available on the Enterprise plan.
Post-purchase follow-up
After a buyer completes a purchase, the Lifecycle Agent handles follow-up conversations:
- Cross-sells: Recommends complementary products based on what they bought. Timing is per-buyer, not a fixed “7 days after purchase” rule.
- Review requests: Asks for reviews after the buyer has had time to use the product. Janine knows what they ordered and references it specifically.
- Reorder reminders: For consumable products, Janine tracks estimated usage and follows up when it’s time to reorder.
Example
A buyer purchases a running shoe. Ten days later (enough time for delivery and a few runs), Janine follows up:
“How are the Trail Runner Pros working out? If you’re happy with them, a quick review helps other runners find the right fit. And if you need insoles or extra laces, I can help with that too.”
A batch email tool would send the same cross-sell to every buyer on the same schedule. The Lifecycle Agent adjusts timing based on delivery estimates, product category, and the buyer’s past behavior.
Winback
When a buyer stops engaging, the Lifecycle Agent spots it per person rather than applying a blanket “inactive for 90 days” rule.
How it works
The agent tracks each buyer’s engagement cadence. If someone who usually opens emails weekly goes silent for two weeks, that’s early disengagement. It doesn’t wait 90 days to notice.
Once it identifies disengagement, it re-engages with the minimum effective offer. Not everyone needs 20% off. Some buyers just need a reminder. Some need to see a new product. The agent tests different approaches per individual.
The point is to avoid giving away margin when you don’t have to. Some buyers come back with a reminder. Some need to see a new arrival. Some actually do need a discount. The agent figures out which is which instead of blasting 20% off to your entire list.
Continuous optimization
The Lifecycle Agent tests every interaction on its own. It varies timing, tone, channel, and offer across buyers and learns what works for each person. No manual A/B test setup, no waiting weeks for statistical significance.
