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meta-ads-lead-gen-analysis元广告潜在客户发掘分析

Agent Skill

meta-ads-lead-gen-analysis 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。

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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:meta-ads-lead-gen-analysis(元广告潜在客户发掘分析)
来源仓库:https://github.com/elias-didoo/meta-ads-lead-gen-analysis
安装命令:
openclaw skills install meta-ads-lead-gen-analysis
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 meta-ads-lead-gen-analysis

简介

专门用于元潜在客户开发活动的深度分析报告模块。

  • 当 CPL 升高或导联质量模糊不清时启用诊断。
  • 聚焦线索来源、表单设计与落地页转化瓶颈分析。meta-ads-lead-gen-analysis 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 要求具备访问 Lead Ads 详细日志的权限。
  • 建议配合原始案例理解典型问题与优化方向对应关系。

SKILL.md

name
meta-ads-lead-gen-analysis
description
[Didoo AI] Specialized analysis module for Meta lead generation campaigns. Use when CPL is elevated, lead quality is unclear, or you need to diagnose why leads aren't converting downstream. For general campaign analysis, use meta-ads-analysis.
homepage
https://didoo.ai/blog
metadata

Required Credentials

CredentialWhere to GetUsed ForOAuth Scope
META_ACCESS_TOKENMeta Developer Console → Graph API Explorer → Generate TokenFetching campaign and form integration dataads_read (read-only)
META_AD_ACCOUNT_IDAds Manager URL: adsmanager.facebook.com/act_XXXXXXXXXIdentifying which account to query

When to Use

When running lead generation campaigns and standard e-commerce analysis logic doesn't apply. Specifically for:

  • CPL is higher than expected or target
  • Lead volume is healthy but conversion rate to closed deals is low (quality problem)
  • LPV rate looks fine but form submit rate is unknown
  • CAPI may not be sending offline lead data back to Meta
  • Not sure if the problem is the ad, the audience, or the form itself

Lead gen has fundamentally different metrics than e-commerce — standard CVR and LPV benchmarks don't apply. Use this skill instead of applying e-commerce logic to lead gen campaigns.


Key Differences from E-commerce Analysis

MetricE-commerce BenchmarkLead Gen BenchmarkWhy It Differs
LPV Rate> 70% is healthy> 50% is healthyMany leads browse without intent to submit
Form Submit RateN/A> 20% is healthyForm friction is the primary drop-off point
CPLVaries by industryThe primary metricWhat you're actually paying for
CVR (post-click)Purchase rateLead-to-qualified rateMeta can't see what happens after form submit
Attribution1-day or 7-day click7-day click usuallyLonger window for consideration

Step 1: Gather Lead Gen Specific Data

Pull these metrics at the campaign and adset level:

  • Spend, impressions, CTR
  • LPV Rate (Landing Page View rate = landing page views / link clicks)
  • Form Submit Rate (if available — requires CAPI or form integration)
  • CPL (cost per lead)
  • Frequency
  • Lead volume vs. prior period

Also ask the user:

  • What does a "good lead" look like for their business?
  • What's their lead-to-close rate historically?
  • Are they using CAPI to send offline lead data back to Meta?

Step 2: CAPI Verification — Critical for Lead Gen

Without CAPI sending offline lead data back to Meta:

  • Meta is optimizing for form submissions, not qualified leads
  • CPL shown may be "form submit cost" not "actual lead cost"
  • The algorithm can't learn which leads actually convert

How to verify CAPI is connected:

  1. Go to Meta Events Manager → select your pixel
  2. Check "About CAPI" — status should be green/active
  3. Ask: are offline leads (calls, CRM-qualified leads) being sent back via CAPI?

If CAPI is NOT connected for offline leads:

  • This is a priority fix — it will lower CPL over 2–3 weeks
  • Recommend a CRM integration or Zapier/Make workflow
  • Or use Meta's Lead Forms (form submission = conversion automatically tracked)

Step 3: Audience Targeting Analysis for Lead Gen

Cold Audiences (Interest-Based Targeting)

  • Interest targeting works for cold audiences
  • Frequency builds fast — limit budget to avoid rapid fatigue
  • Test narrower interest layers (2–3 stacked interests, not broad categories)

Custom Audiences (Retargeting and Lookalikes)

  • Website visitors (pixel): typically highest conversion rate
  • Email lists (matched audiences): strong for existing customer re-engagement
  • Lookalikes (LAL): based on converter audiences, quality depends on seed list quality
  • Test LAL layers 1–3% first — wider LAL = lower quality but more volume

Step 4: Format Output

Lead Gen Health Summary:

  • Spend / CPL / Lead Volume
  • LPV Rate vs. benchmark (> 50% healthy for lead gen)
  • Form Submit Rate (if available)
  • CAPI Status (connected / not connected)

SECTION 1: CAPI Gap (if applicable)

State whether offline lead data is being sent to Meta. Impact: algorithm is optimizing for quantity, not quality.

SECTION 2: Audience Diagnosis

Diagnose targeting based on frequency and CPL — is the audience too broad or well-matched?

SECTION 3: Funnel Stage

Identify the CPL bottleneck stage:

  • LPV < 50% → Ad-to-Form disconnect
  • LPV ≥ 50% but low leads → Form friction (check form fields)
  • LPV and CVR OK but CPL high → Audience mismatch or CAPI not connected
LP Landing Page diagnosis: The full LP disconnect diagnostic (Step 4a–4d) lives in meta-ads-recommendation → Step 4. This skill identifies the funnel stage; recommendation prescribes the fix.

Session Context — What This Skill Writes

After completing analysis, store the following in session context:

KeyDescriptionExample
lp_diagnosisFunnel stage causing the CPL problem"Form friction — submit rate 12%, below 20% benchmark"
capi_statusWhether offline leads are being sent to Meta"Not connected — offline lead data not flowing"
cpl_breakdownWhich stage is the bottleneck"LPV 65% OK; Form submit 11% is the bottleneck"
recommended_fix_priorityRanked fix order"1. CAPI 2. Form fields 3. Audience"
meta-ads-recommendation reads these keys to produce the lead gen action plan.

Key Collision Resolution

⚠️ Key priority: meta-ads-analysis writes lp_diagnosis_general; this skill writes lp_diagnosis (the lead-gen-specific version). meta-ads-recommendation is configured to prefer lp_diagnosis when available — so running both skills in sequence does NOT cause overwriting. The two keys coexist.

Rules

  • Apply lead gen benchmarks, not e-commerce benchmarks
  • Always verify CAPI status before diagnosing CPL issues — missing CAPI is the most common cause of misleading CPL data
  • Do not recommend creative changes if form friction is the bottleneck
  • Do not recommend audience changes if LPV rate indicates a page problem
  • This is analysis only — recommendations route to meta-ads-recommendation

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能力 5

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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。

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