Meta Ads Analysis

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.

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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.

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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.

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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

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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

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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.

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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.

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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.

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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

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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

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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.

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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"

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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

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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.