Full User Lifecycle Operations System Setup

From Vague Segmentation to Actionable Stage-based Operations

A common pain point for private domain operators is the gap between having user segments (e.g., via RFM) and knowing "what stage of the lifecycle is this user in?" and "what strategy should we deploy next to guide them?" Generic, one-size-fits-all actions (like blanket re-engagement campaigns for all dormant users) or strategies misaligned with user stages lead to wasted resources and disjointed user experiences.

This skill provides a structured framework from a temporal dimension. It transforms vague user states (e.g., "new user," "active," "dormant") into a quantifiable five-stage, three-zone lifecycle model (Introduction, Growth, Maturity, Atrophy, Loss) and generates a tightly coupled operational strategy action matrix.

Core Capabilities & Workflow

The skill follows a standardized process to directly output an executable "three-piece set":

1. Stage Definition with Quantifiable Conversion Conditions: It anchors stage thresholds to business category (e.g., high-frequency F&B, cyclical retail) and uses the "Four Methods for Thresholds" (mean, quintile, Pareto, fixed anchor) to set explicit entry/exit conditions for each stage. For example, the condition to move from Growth to Maturity might be defined as "completing [N] repurchases within [Purchase Cycle] days."
2. Lifecycle Journey Map Generation: A visual representation of user flow between stages, incorporating the seven journey map elements to diagnose experience friction points. This map answers "why is the journey designed this way?"
3. Stage-wise Operational Strategy Table Compilation: This is the core deliverable. It aligns each stage with specific objectives, actions, touchpoints, content, benefits, and key performance indicators (KPIs). For instance, strategies for the "Maturity" stage would prioritize benefits/services over deep discounts and track KPIs like "Customer Lifetime Value (LTV)" and "Average Order Value."

Key Principles:
- Orthogonal to RFM: The skill does not re-calculate RFM. It references RFM results as a "value axis" and crosses it with the "stage axis" (lifecycle) to create a "Stage × Value" matrix (e.g., "Maturity × High Value"), enabling dual-dimensional operations.
- Anti-pattern Prevention: All outputs are enforced to be quantifiable, rejecting vague terms like "after activity declines" or "relatively good." Loss thresholds must be explicit (e.g., for FMCG: no purchase for ≥ [Purchase Cycle] days) and calibrated by category.

Scope and Important Considerations

• Not for Value-Only Segmentation: If your need is solely "RFM Value Segmentation + Outreach Strategies," use the parent skill 【Private Domain User Operations】. This skill specifically addresses the temporal path: "where are they, and where to guide them?"
• Cold-Start Friendly: You can start with category-based experience thresholds even without detailed data, clearly marking them as [Hypothesis—needs data validation] for subsequent calibration with real data.
• Enforced Closures: The output includes a recalculation cadence (to prevent stale segments) and a re-engagement ROI decision rule (investing in reactivation only for historically high-value dormant users to avoid waste).
• Final Delivery: The skill outputs a complete Markdown report (the "three-piece set") and submits it to a server for registration as a side-effect. A local script is also available to generate a companion Excel template.