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customer-lifetime-value-optimizer客户终生价值优化器

Agent Skill

customer-lifetime-value-optimizer 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,724

周安装

117

GitHub Stars

公开资料未说明

下载量

955
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:customer-lifetime-value-optimizer(客户终生价值优化器)
来源仓库:https://github.com/harrylabsj/customer-lifetime-value-optimizer
安装命令:
openclaw skills install customer-lifetime-value-optimizer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install customer-lifetime-value-optimizer

简介

customer-lifetime-value-optimizer 基于消费行为细分客户并估算终生价值潜力。

  • 适用于 OpenClaw 中设计会员体系、优惠券投放与忠诚度计划策略。
  • 输出包含 RFM 模型标签、CLV 区间分布与推荐营销动作优先级排序。
  • 订单历史数据质量直接影响估值精度,缺失值需通过插补或排除处理。
  • 促销策略应平衡短期转化与长期利润,避免损害品牌价值的行为激励。

SKILL.md

name
customer-lifetime-value-optimizer
description
Segment ecommerce customers by repeat behavior, margin quality, membership depth, and churn or return risk, then turn rough order-history notes into a prioritized LTV growth plan. Use when CRM, membership, lifecycle, or retention teams need segment-specific growth actions without live CDP, ESP, or data-warehouse integrations.

Customer Lifetime Value Optimizer

Overview

Use this skill to convert customer-segment notes, order-history summaries, gross-margin signals, and retention context into a practical LTV action plan. It is built for operators who need fast prioritization across new-customer nurture, repeat purchase growth, margin protection, and winback strategy.

This MVP is heuristic. It does not connect to live CRM, CDP, ESP, loyalty, or analytics systems. It relies on the user's segment notes, exported summaries, and lifecycle context.

Trigger

Use this skill when the user wants to:

  • identify which customer segments deserve the most retention investment
  • design different lifecycle moves for high-value, price-sensitive, dormant, or return-risk customers
  • rank LTV levers such as repeat rate, AOV, margin mix, or churn reduction
  • turn rough order-history notes into a CRM or membership action brief
  • separate revenue growth ideas from margin-quality and retention-quality risks

Example prompts

  • "Which segments should we prioritize to improve LTV this quarter?"
  • "Create a retention plan for VIP, new, and dormant customers"
  • "How can we grow LTV without overusing discounts?"
  • "Turn these order and membership notes into an LTV roadmap"

Workflow

  1. Capture the customer segments, order behavior, and whether the main tension is repeat rate, AOV, churn, or margin quality.
  2. Normalize the likely LTV signals: order history, repurchase cycle, segment mix, return behavior, and offer sensitivity.
  3. Separate customer groups into different action lanes instead of giving one generic lifecycle answer.
  4. Rank the highest-value LTV levers and attach practical plays, owners, and success metrics.
  5. Return a markdown plan with segment diagnosis, lever ranking, and action packages.

Inputs

The user can provide any mix of:

  • customer segments or membership tiers
  • order history and repeat-cycle notes
  • AOV, gross margin, bundle rate, or attach-rate context
  • churn, dormancy, or lapsed-customer notes
  • refund or return-risk observations
  • lifecycle messaging constraints and incentive constraints

Outputs

Return a markdown plan with:

  • a segment diagnosis table
  • ranked LTV levers
  • action packages by segment
  • short, medium, and longer-horizon priorities
  • measurement notes, assumptions, and limits

Safety

  • Do not claim access to live CRM, ESP, loyalty, or analytics systems.
  • Do not auto-send discounts, coupons, or lifecycle messages.
  • Keep revenue lift and margin impact separate in the recommendations.
  • Downgrade certainty when user-level order history is incomplete.
  • Treat financial LTV models and operator-facing lifecycle plans as related but not identical.

Best-fit Scenarios

  • CRM and membership planning for ecommerce teams
  • repeat-purchase and lifecycle improvement reviews
  • retention strategy design when data is partial but usable
  • operator-led businesses that need an action plan before building a deeper model

Not Ideal For

  • formal finance-grade LTV forecasting
  • automatic customer scoring or trigger orchestration
  • businesses with no segment or order-history visibility at all
  • scenarios that require privacy-reviewed activation logic

Acceptance Criteria

  • Return markdown text.
  • Include segment diagnosis, lever ranking, action packages, and limits.
  • Show at least one short-term, one medium-term, and one longer-term move.
  • Keep the plan practical for CRM, lifecycle, and retention operators.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

97.05%
按下载量换算927

安全审计

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通过

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权限和风险

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安装前确认

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来源信息

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