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Meta Ads Analysis

[Didoo AI] 深入分析 Meta Ads 广告系列表现——包括指标、漏斗、趋势和异常。当用户想要了解广告系列的运行情况时使用。

person作者: elias-didoohubclawhub

Required Credentials

| Credential | Where to Get | Used For | OAuth Scope | |-----------|-------------|---------|-------------| | META_ACCESS_TOKEN | Meta Developer Console → Graph API Explorer → Generate Token | All Meta Marketing API calls | ads_read (read-only, least-privilege) | | META_AD_ACCOUNT_ID | Ads Manager URL: adsmanager.facebook.com/act_XXXXXXXXX | Identifying which account to query | — |

When to Use

Loaded when user wants to understand how their Meta Ads campaign is performing — either a specific aspect (audience, creative, overall) or a full diagnostic. Can run standalone or as prerequisite for meta-ads-recommendation.


Step 0: Understand the Campaign

Before pulling any data, get context on what this campaign is trying to do. Ask 1–2 quick questions if not already clear from conversation:

  • "Is this an always-on campaign, or tied to a specific promotion?"
  • "Are you testing new things, or trying to scale what's already working?"

Keep it conversational. If META_ACCESS_TOKEN or META_AD_ACCOUNT_ID is not available, tell the user exactly what is needed and do not proceed with API calls.


Step 1: Gather Campaign Structure

Ask the user for their Meta Ads account access. Use the Meta Marketing API to fetch:

Campaign level

  • Campaign name, ID, status (is it ACTIVE?)
  • Objective (what counts as a "result" — leads, purchases, clicks?)
  • Budget type (CBO = campaign-level budget optimization, or ABO = adset-level)
  • Bid strategy, daily budget, start date

Adset level

  • Adset name, ID, status
  • Optimization goal (this determines what "results" means for this adset)
  • Targeting countries, budget, bid amount

Ad level

  • Ad name, ID, status
  • Which adset it belongs to

Store this as campaign_context. Reuse across the session — don't re-fetch.


Step 2: Confirm Time Range and Attribution Window

Always confirm the time period and attribution window before pulling performance data:

  1. Time range: "What time period would you like to analyze? (e.g., last 7 days, last 30 days, or a specific date range)"
  2. Attribution window: "What attribution window are you using? Default in Meta is 7-day click. For e-commerce, 1-day click often gives a clearer signal. For lead gen, 7-day click is usually better."

| Campaign type | Recommended attribution window | |--------------|--------------------------------| | E-commerce / purchase | 1-day click | | Lead generation | 7-day click | | App installs | 7-day click | | Brand awareness | 28-day view |

Convert to YYYY-MM-DD,YYYY-MM-DD format. Default granularity:

  • ≤14 days → daily
  • 15–60 days → weekly

Step 3: Route the Analysis

| User is asking about | What to analyze | |----------------------|-----------------| | Overall / general health | Campaign-level metrics, no breakdown | | Audience / country / platform / age / gender | Adset or ad level with breakdowns | | Creative / which ad is better | Ad-level metrics | | Everything / full diagnostic | All three in sequence | | Follow-up on existing data | Use data already in session — don't re-fetch |


Step 4: Pull and Interpret Performance Data

Use the Meta Marketing API to fetch metrics for the relevant level and time range.

Key Metrics to Collect

At campaign or adset level:

  • Spend, impressions, frequency
  • CPM (cost per 1,000 impressions)
  • CPC (cost per link click)
  • CTR (link click rate)
  • LPV rate (landing page view rate = landing page views / link clicks)
  • Results, cost per result
  • Conversion rate (results / landing page views)

At ad level, add:

  • Individual ad performance
  • Creative elements if identifiable

What Each Metric Tells You

| Metric | Declining = | Growing = | |--------|-------------|-----------| | CPM | Cheaper reach | Competition up | | CPC / cost_per_result | More efficient | Less efficient | | CTR / LPV rate / conversion_rate | Problem | Healthy | | Results volume | Dropping | Growing | | Frequency | — | Fatigue risk if > 3 |

Understanding "Results"

The meaning of "results" depends on the optimization goal:

  • LEAD_GENERATION → results = leads
  • LINK_CLICKS → results = link clicks
  • LANDING_PAGE_VIEWS → results = landing page views
  • PURCHASE / CONVERSIONS → results = purchases

Always clarify what "results" means when discussing cost_per_result.

Campaign Structure Matters

  • CBO (campaign-level budget): Evaluate at campaign level first
  • ABO (adset-level budget): Evaluate at adset level
  • Multiple ads in one adset: Evaluate at adset level, not individual ads
  • Active but less than 7 days old + less than 50 results since last significant edit: Treat as still in learning phase — data is unstable
  • Breakdown Effect: Meta optimizes for marginal CPA (cost of the next result), not average CPA. A segment showing higher average CPA may be protecting overall campaign efficiency. Do not judge system decisions by average CPA in breakdown reports alone.

Step 4b: Lead Generation Campaigns

Use meta-ads-lead-gen-analysis instead — it has dedicated LPV benchmarks for lead gen, form friction analysis, CAPI verification, and lead quality diagnosis.


Step 4c: Landing Page Diagnostic

This section has moved to meta-ads-recommendation → Step 4. Landing page diagnosis is now part of the recommendation workflow for better action alignment.


Step 5: Check Ad Relevance Diagnostics

When an ad's cost_per_result is elevated and basic metrics (CTR, LPV rate) don't fully explain it, check the Ad Relevance Diagnostics in Meta Ads Manager.

| Diagnostic | What it measures | Low ranking suggests | |-------------|-------------------|-----------------------| | Quality Ranking | Perceived ad quality vs. competitors | Improve creative | | Engagement Rate Ranking | Expected engagement vs. competitors | Test new angles, improve hook | | Conversion Rate Ranking | Expected conversion vs. competitors with same optimization goal | Check landing page or audience-offer fit |

Usage rules:

  • Requires 500+ impressions to be available — below that, diagnostics are not meaningful
  • These are diagnostic tools only, not auction inputs
  • When all three rankings are low simultaneously → strong audience-creative mismatch

Step 6: Assess for Problems

Flag these when you see them:

  • Frequency > 3 → Audience fatigue risk
  • CTR less than 1% → Weak creative hook or audience mismatch
  • LPV rate less than 70% → Ad-to-landing-page disconnect
  • cost_per_result rising → Efficiency problem
  • Status is not ACTIVE → Explain impact
  • Learning / Learning Limited → Warn: data not yet stable
  • Spend less than 50% of budget → Delivery problem — audience may be too narrow or bid too low
  • One segment vastly outperforming others → System is correctly finding winners

Step 7: Structure Your Output

  • Campaign Context: one sentence covering objective, budget type, and status.
  • Summary: Spend, impressions, results, cost per result, CTR, CPM.
  • Funnel: Impressions → Link Clicks → Landing Page Views → Results, with rates at each stage.
  • Trend Analysis: Key metrics with direction and what it means for the business.
  • Key Issues: Specific problems and why they matter.
  • Data Notes: Any caveats — learning phase, insufficient data, zero-spend entities excluded.

Tone and Language

  • Match the language the user speaks (English or Chinese)
  • Speak as a professional growth partner — translate numbers into business insights
  • Every judgment must cite specific data. Never say "performance is bad" without a number
  • When data is insufficient, say so: "2 days isn't enough for reliable trends — let's revisit in a week"

Restrictions

  • Analysis only — never output recommendations in this skill
  • Do not recalculate metrics already computed by Meta (CTR, CPM, CPC are already calculated)
  • Never conclude an ad or adset is "underperforming" based on CPA alone without comparing to its own historical baseline and the account average

Session Context — What This Skill Writes

After completing analysis, store the following in session context:

| Key | Description | Example | |-----|-------------|---------| | funnel_weak_points | Where the biggest funnel drop-off occurs | "LPV rate 58%, well below 70% benchmark" | | trend_signals | Direction of key metrics | "CPM up 18% WoW; CTR down 0.4pp" | | anomalies | Anything unusual or unexpected | "Frequency 4.2 with CPL still at target" | | data_quality | Whether there's enough data to act | "Only 2 days — too early to judge" | | lp_diagnosis_general | Is the problem ad-side or landing page-side? | "Ad side — CTR declining, frequency stable" |

Routing: If the campaign is Lead Gen, route to meta-ads-lead-gen-analysis and preserve these keys. meta-ads-recommendation reads these keys to produce the action plan.