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retargeting-strategy重定向策略

Agent Skill

retargeting-strategy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

654

周安装

27

GitHub Stars

66

下载量

214
CodexClaudeCursorGemini CLI

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

unknown

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:retargeting-strategy(重定向策略)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/retargeting-strategy
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill retargeting-strategy
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill retargeting-strategy

简介

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位结果。

  • 适用于需要从多来源线索中提取有效信息的场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 建议确认权限范围和维护状态,避免触发联网或文件读写操作。
  • retargeting-strategy 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

/dm:retargeting-strategy

Purpose

Design a cross-platform retargeting strategy with audience segmentation by funnel stage and behavior, creative sequencing, frequency management, and budget allocation. Produces a complete retargeting playbook ready for implementation across advertising platforms.

Input Required

The user must provide (or will be prompted for):

  • Website traffic volume: Monthly unique visitors and page views (approximate is fine)
  • Conversion funnel stages: The key stages in the user journey (visit, product view, add to cart, checkout, purchase -- or equivalent for lead gen funnels)
  • Platforms in use: Which advertising platforms are active or available (Google Ads, Meta, LinkedIn, TikTok, programmatic DSPs, etc.)
  • Retargeting budget: Monthly budget allocated or available for retargeting campaigns
  • Product catalog: For dynamic retargeting -- whether a product feed exists and on which platforms it is configured
  • Average purchase cycle: Typical time from first visit to conversion (days, weeks, months)
  • Current retargeting setup: Any existing retargeting campaigns, pixel/tag status, audience definitions already in place, and current performance
  • Pixel and tracking status: Which pixels/tags are installed and firing correctly (Meta Pixel, Google Tag, LinkedIn Insight Tag, TikTok Pixel, etc.)

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply voice, compliance, industry context. Check guidelines/_manifest.json for restrictions, messaging, channel styles, voice-and-tone rules, and templates. If a template matching this command exists in ~/.claude-marketing/brands/{slug}/templates/, apply its format. If no brand exists, prompt for /dm:brand-setup or proceed with defaults.
  2. Check campaign history: Run python campaign-tracker.py --brand {slug} --action list-campaigns to review existing retargeting campaign performance and identify what has already been tested.
  3. Audit tracking infrastructure: Verify pixel and tag installation status across platforms. Identify gaps in tracking that would prevent audience building or conversion attribution before designing the strategy.
  4. Define retargeting audience segments: Create segments based on funnel stage (awareness visitors, product viewers, cart abandoners, past purchasers, lapsed customers), behavior signals (pages visited, time on site, visit frequency, content consumed), and recency windows (1-3 days, 4-7 days, 8-14 days, 15-30 days, 31-90 days). Size each segment based on traffic volume.
  5. Design creative sequence per segment: Map a messaging sequence for each audience segment that progresses the user toward conversion -- awareness segments get educational and value-prop messaging, consideration segments get social proof and differentiation, cart abandoners get urgency and incentive, past purchasers get upsell and cross-sell, and lapsed customers get re-engagement offers.
  6. Set frequency caps per platform: Define impression frequency limits per user per day and per week for each platform. Balance visibility against ad fatigue -- typically 3-5 impressions per day for display, 1-2 per day for social feed placements, and 15-20 per week maximum across all placements combined.
  7. Plan cross-platform coordination: Orchestrate retargeting across platforms so users see a coherent journey rather than redundant messages. Assign primary and secondary roles per platform (e.g., Meta for awareness retargeting, Google Display for mid-funnel, search remarketing for high-intent, LinkedIn for B2B decision-makers).
  8. Design exclusion lists: Define converter exclusion windows (exclude purchasers for 7-30 days post-conversion), cross-segment exclusions (prevent users from seeing both awareness and cart abandonment ads simultaneously), and negative audience rules to prevent waste and brand fatigue.
  9. Set budget allocation per segment: Distribute the retargeting budget across segments based on audience size, proximity to conversion, and expected ROAS. Bottom-funnel segments (cart abandoners) typically receive the highest per-user spend despite smaller audience sizes.
  10. Configure dynamic retargeting: If a product catalog is available, specify dynamic ad setup -- feed requirements, template design, product recommendation logic (viewed items, complementary products, best sellers), and fallback creatives for users without product-level data.
  11. Define KPIs and optimization triggers: Set success metrics per segment and platform (ROAS, CPA, view-through conversions, frequency, CTR). Define optimization triggers -- when to refresh creative, adjust bids, reallocate budget, or expand/contract audience windows.
  12. Create UTM structure for tracking: Build a UTM naming convention that enables granular tracking of retargeting performance by segment, platform, creative variant, and funnel stage in analytics.

Output

A structured retargeting strategy document containing:

  • Audience segment definitions with sizing estimates, recency windows, and behavioral criteria
  • Creative brief per segment with messaging themes, ad formats, and sequencing logic
  • Frequency cap recommendations per platform with rationale for each limit
  • Cross-platform coordination plan showing which platform serves which funnel role
  • Exclusion list definitions with converter suppression windows and cross-segment rules
  • Budget allocation table by segment and platform with expected ROAS targets
  • Dynamic retargeting setup guide with feed requirements and product recommendation logic
  • KPI framework with targets per segment, optimization triggers, and review cadence
  • UTM structure and naming conventions for retargeting campaign tracking
  • 30/60/90-day optimization roadmap with milestone checkpoints and scaling criteria
  • Privacy and compliance considerations (cookie consent, GDPR/CCPA audience restrictions, platform-specific privacy limitations)
  • Tracking infrastructure checklist with pixel/tag verification requirements per platform

Agents Used

  • media-buyer -- Audience segmentation, platform-specific retargeting setup, frequency management, budget allocation, bid strategy, dynamic retargeting configuration, and campaign structure design
  • marketing-strategist -- Creative sequencing strategy, cross-platform coordination, funnel-stage messaging architecture, and optimization roadmap planning

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

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

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

Codex

32.89%
按下载量换算70

Claude

30.8%
按下载量换算66

Cursor

17.14%
按下载量换算37

Gemini CLI

10.17%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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