> For the complete documentation index, see [llms.txt](https://docs.peakcommerce.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.peakcommerce.com/guides/feature-guides/retain-and-manage/guide-win-back-reactivation-journey.md). # Building a Win-Back (Reactivation) Journey ### Overview A cancelled customer isn't gone — they're *paused indefinitely*. They already knew your product, already trusted you with a card once, and often left for a reason you've since addressed. A **win-back journey** invites a lapsed customer to re-subscribe in a couple of clicks, prefilled with the plan they had and sweetened with a comeback offer — and it gets smarter when you target it at *why* they left in the first place. This guide builds a reactivation flow and shows how to aim it using the cancellation reasons your retention journey captured. ### The example we'll build **Cadence, a fitness-app subscription,** emails customers who cancelled 60 days ago: *"We've missed you — come back for 30% off your first 3 months."* The link opens a journey already set to their old Premium plan, applies the comeback discount, takes payment, and reactivates them — no hunting for the right plan, no re-deciding everything. ### Before you begin * A **comeback offer** (a discount) configured in your offers / pricing setup, so the journey can apply it within policy. * The plans you want lapsed customers to return to. * Ideally, cancellation **reasons** captured by your retention journey (see the multi-branch retention journey guide) — they make win-back far sharper. ### 1. Create the reactivation journey 1. Go to **Content → Journeys** and click **+ New Journey**. 2. Choose the **Type** for your audience: **E-Commerce** if the link is public (anyone with the email can use it), or **Customer Self-Service** if you require the lapsed customer to sign in first. Name it (for example *Win-Back — Premium*). 3. Build a short, low-friction flow: **Welcome-back offer → Billing → Confirmation** Keep it shorter than a cold checkout — they've bought before; don't make them reconsider every choice. ### 2. Prefill the plan from the link The win-back email should drop the customer straight onto *their* plan, not a generic catalog: * Use a **plan-based URL prefill** so the link sets the base plan (by id), currency, and starting step. The customer lands on the welcome-back step with Premium already selected — they just confirm and pay. * Optionally point a **branded host** at the journey's entry step with a subdomain mapping, so the comeback link lives on your own domain. ### 3. Apply the comeback offer On the welcome-back step, present and apply the discount: * The offer resolves from your **offers / pricing** configuration, so the journey can only extend a comeback discount your business has approved — the policy engine is the ceiling. * A `create_order` action then **re-subscribes** the customer to the plan (a new subscription), with the comeback discount applied. ### 4. Target win-back by why they left This is where win-back gets powerful. The cancellation **reason** your retention journey stamped to the CRM (for example `CancellationReason__c = missing_feature`) tells you *how* to win each cohort back: * **"Missing a feature"** that you've since shipped → "The thing you wanted is here" win-back, no discount needed. * **"Too expensive"** → lead with the discount or a cheaper plan. * **"Switching tools"** → a comparison + comeback incentive. * **"Not using it enough"** → re-onboarding help, not just a price cut. Use **profile assignments** (and your email segmentation) so each cohort gets the win-back journey tuned to their reason, rather than one generic "come back" for everyone. ### 5. Preview, publish, measure * **Preview** with a prefill link to confirm the right plan and offer load, then **Publish**. * Reactivations show up in your **Analytics** alongside new business; watch reactivation volume and the revenue recovered, and compare win-back cohorts by reason to learn which offers actually bring people back. ### Get creative * **Anniversary win-back.** Trigger the email at a meaningful interval (60/90/180 days lapsed) and escalate the offer the longer they've been gone. * **"What's new since you left."** Branch the welcome-back step to highlight features shipped after their cancellation date — especially for feature-driven leavers. * **Reactivate to a free tier.** For price-sensitive leavers, offer a free/cheaper tier as the re-entry point and expand them later. * **Loyalty for returners.** Grant a returning customer a small perk (extra seats, a credit) to make coming back feel rewarded, not just transactional. ### Tips * **Prefill everything you can.** The whole advantage of win-back is that you already know them — set the plan, currency, and step from the link so they barely have to choose. * **Tie the offer to the reason.** A discount answers "too expensive," but a shipped feature answers "missing a feature" better than money. * **Keep offers within policy.** Comeback discounts resolve from your offers engine, so set the ceiling centrally and let the journey honor it. ### FAQ **Public link or signed-in?** Either. An **E-Commerce** journey lets anyone with the email reactivate; a **Customer Self-Service** journey requires sign-in first. Choose based on how tightly you want to bind the offer to the original customer. **How do I aim win-back at the right people?** Use the cancellation **reason** captured by your retention journey (stamped to the CRM) to segment your email and your journey cohorts, so each group gets the offer most likely to bring *them* back. See the multi-branch retention journey guide for capturing those reasons. **Does win-back create a new subscription or resume the old one?** It re-subscribes the customer — a `create_order` places a fresh subscription on the chosen plan with the comeback offer applied. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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