Retention isn't a calendar.
It's a decision.

Retention marketing is the discipline of growing revenue from customers you already have, through repeat purchases, cross-sell, winback, and lifecycle engagement. Acquiring a new customer costs roughly 5× more than retaining one, and even a 5% lift in retention can drive 25–95% more profit. Modern retention marketing has shifted from calendar-based flows to AI-orchestrated decisions made for each customer individually.

Traditional lifecycle marketing runs on rules you define in advance: “send X to segment Y on day 30.” AI retention runs on a continuously learning decision engine that decides, for each customer, every day, whether to act, on which channel, with which message, at which exact moment. It's the difference between a thermostat (set once) and a control system that adapts continuously to real behavior.

Replenit separates churn into the two motions it actually has: brand churn (the customer is leaving you entirely) and product churn (the customer is still buying with you but has gone silent on a specific SKU or category). Both are detected the moment cadence breaks against the customer's own pattern, not against an arbitrary 180-day cliff. The same Churn agent runs both motions, scoring five distinct patterns: product-level, category exit, competitor switch, frequency decay, and basket shrink.

Start with Repeat Purchase Rate and Net Revenue Retention as your headline KPIs. Layer in CLV to budget intelligently, and Predictive Churn Probability to act before customers lapse. But the single most important measurement discipline is incrementality testing: running continuous holdout groups so you can prove what retention revenue would not have happened without your program. Without holdouts, last-click attribution will overstate retention impact by 30–60%.

Five strategies consistently outperform: (1) AI-powered replenishment timing for consumables; (2) predictive churn intervention before customers lapse, product- and brand-level; (3) lifecycle-aware cross-sell that respects onboarding moments; (4) autonomous winback that picks who to reactivate profitably; (5) margin-protecting promotion logic that prices offers to each customer's elasticity. All five share the same underlying capability: a decision engine that reasons about individual customers, not segments.

No. Replenit is an intelligence layer. It sits alongside your existing stack and decides what should happen next. Your ESP (Klaviyo, Braze, Salesforce, Iterable, Insider, Bloomreach, etc.) still owns delivery. Your CDP still owns the unified customer profile. We connect via API in roughly one day and push decisions natively into your activation tools. There's no rip-and-replace.

Most Replenit customers see measurable incremental revenue within 2–3 weeks. Day 1 is integration. Days 2–7 are AI calibration on your historical data. Days 8–14 are autonomous orchestration beginning, with holdouts already running. Documented case studies range from a 12× conversion lift at Farmex within weeks to a 42× ROI at Mumzworld within the POC window.

Typically the opposite. Because Replenit only acts when there's a high-confidence reason to, brands usually see fewer total sends with higher per-send revenue, and substantially better list health. The decision engine optimizes for incremental revenue per customer, not for volume, which protects deliverability and reduces unsubscribe pressure.