meta-ads-analyzer

# Meta Ads Analyzer Most "Meta Ads analysis" stops at "this CPA is high, pause it." That's wrong more often than it's right. Meta's delivery system optimizes for **marginal efficiency** — the cost of the *next* conversion — not average efficiency across a snapshot. A segment with a higher average CPA is often the one keeping your overall campaign cheap. Pausing it makes things worse. This skill diagnoses Meta campaigns the way a senior media buyer would: at the right evaluation level, accounting for learning state, separating noise from signal, and explaining *why* the system is making the decisions it's making before recommending any change. **Core principle:** Holistic first, then drill down. Marginal over average. Dynamic over static. Every recommendation is a testable hypothesis with expected impact, not a directive. ## When to Use - "Analyze my Meta Ads campaign performance" - "Why is the system spending more on the higher-CPA placement?" - "Diagnose what's wrong with this ad set" - "Should I pause this audience / placement / ad?" - "My CPA jumped — is this normal or a real problem?" - "Audit this campaign before I scale budget" - "I exported my Meta data — what does it actually mean?" ## Phase 0: Intake 1. **Campaign data** — One of: - CSV export from Meta Ads Manager (Campaign / Ad Set / Ad level + breakdowns) - Pasted performance table - Screenshots (we'll extract the metrics) - Live data via your existing Meta Marketing API connection 2. **Campaign setup**: - Objective (Awareness / Traffic / Engagement / Lead Gen / Conversions / Sales / App Installs) - Budget type (Advantage+ Campaign Budget = CBO, or Ad Set Budget = ABO) - Placements (Automatic vs. manual) - Number of ad sets and ads 3. **Time period** — Date range covered, with any known events (creative refresh, budget change, audience edit, account issue) 4. **Target metrics** — CPA target, ROAS target, or "no target — benchmark me" 5. **Funnel context** (if relevant) — On-platform conversion vs. website event vs. downstream qualification rate 6. **What's making you ask?** — Specific concern ("CPA up 40%"), routine review, or pre-scale audit ## Phase 1: Identify the Correct Evaluation Level This is the most important step. **Evaluating at the wrong level is the #1 source of wrong recommendations.** | Campaign Setup | Correct Evaluation Level | Why | |---|---|---| | Advantage+ Campaign Budget (CBO) | **Campaign level** | System pools budget across ad sets — only campaign totals reflect reality | | Automatic placements (no CBO) | **Ad Set level** | System pools budget across placements within the ad set | | Multiple ads in 1 ad set | **Ad Set level** | System pools delivery across ads | | Manual placements + ABO | Placement / Ad Set level | Each is independent | **Output for this phase:** State the evaluation level explicitly and explain why before any metric is interpreted. > If asked "is this Meta placement underperforming?" on a CBO campaign, the answer is "wrong question — at CBO the placement-level CPA is misleading. Here's the campaign total..." ## Phase 2: Check Learning Phase Status Before judging anything, check delivery state per ad set. **Learning state checklist:** - Status is `Learning` (delivery less stable, CPA typically higher, results not predictive) - Exits after ~50 optimization events within 7 days of last significant edit - Shops ads exception: 17 website purchases + 5 Meta purchases - Status `Learning Limited` = can't get enough events → flag as a structural issue, not a performance issue **Significant edits that reset learning:** - Targeting changes - Optimization event change - Creative changes (large) - Bid strategy / amount changes - Budget changes >20% **Output for this phase:** Per ad set, mark `Active` / `Learning` / `Learning Limited`. Caveat all conclusions for anything in learning. **Do not recommend pausing a Learning ad set based on CPA alone.** ## Phase 3: Diagnose with Meta-Specific Lenses Run the diagnosis through these five lenses. Each one explains a different class of "weird" behavior. ### 3A: Marginal Efficiency Analysis (Breakdown Effect) The Breakdown Effect: the system shifts budget toward segments where the *next* conversion is cheapest, not where the *average* conversion is cheapest. A segment can have a high average CPA in a breakdown report and still be the right place for budget. **How to spot it:** - Time-series the segment's CPA. If marginal CPA is rising sharply, expect the system to shift budget out — even if average looks fine. - A breakdown row with high average CPA + high spend usually means the system found cheap marginal conversions there earlier in the period. **Mandatory framing in the report:** Never recommend pausing a segment based solely on higher average CPA/CPM in a breakdown report. Removing it will often *raise* total cost. Frame any cut as a hypothesis to test with a holdout, not an instruction. ### 3B: Ad Relevance Diagnostics For each ad with sufficient impressions (~500+), check the three rankings: | Ranking | Below Average → | Action | |---|---|---| | **Quality Ranking** | Creative is the problem | Test new creative formats / hooks | | **Engagement Rate Ranking** | Hook isn't pulling | Test new opener / first 3 seconds | | **Conversion Rate Ranking** | Post-click is leaking | Audit landing page (use `ad-to-landing-page-auditor`) | Two below average + one average = creative refresh. All three below average = scrap and rebuild. ### 3C: Auction Overlap Check Symptoms: ad sets in the same campaign chronically `Learning Limited`, underspending budget, or showing erratic delivery. **Causes:** Overlapping audiences within the same ad account / Page mean only one of your ads enters each auction (Meta picks the highest-value one; the others are excluded — you don't bid against yourself, but the suppressed ad sets can't learn). **Action:** - Run Account Overview → Opportunity Score for explicit overlap flags - Combine similar ad sets (consolidate learning) or pause the weaker overlapping ones ### 3D: Pacing Analysis Pacing = the system smoothing budget across the day/period to capture the best opportunities. Daily snapshots will look uneven *by design*. **How to read it:** - Evaluate spend over the full campaign window, not single days - If the system is consistently underspending budget, that's a pacing/learning issue, not a "good thrift" — usually points to overlap, narrow audience, or bid-strategy mismatch - Ignore "$X budget unspent today" alarms unless sustained over 3+ days ### 3E: Performance Fluctuation Assessment Distinguish noise from trend before recommending anything. | Signal | Verdict | |---|---| | Day-to-day CPA swing within 20–30% | Normal — ignore | | Weekend vs. weekday delta | Normal — control for it | | Gradual change over weeks | Trend — investigate | | Sudden ≥50% cost increase sustained 3+ days | Real problem — diagnose | | Delivery near zero | Account/asset/policy issue — check first | | Conv rate dropping while spend rises | Creative fatigue or LP regression | Always check sample size. A 1-conversion difference at low volume is meaningless. ## Phase 4: Synthesize Through the Breakdown Effect Lens Before writing the report, restate every finding from Phase 3 in terms of *what the system is trying to do*: > "Placement A shows $10 average CPA vs Placement B's $15. Time-series shows A's CPA rising. The system is correctly shifting toward B because B's marginal CPA is now lower. Recommendation: do nothing on placements; test new creative in A to lower its marginal CPA." If a finding can't be restated in marginal/system-mechanics terms, it's probably noise — drop it. ## Phase 5: Generate the Report Use this exact structure. No deviation. ``` 1. EXECUTIVE SUMMARY - 2–3 sentences on overall health - Top 1 thing to do, top 1 thing NOT to do 2. EVALUATION LEVEL - Stated explicitly with the reason 3. LEARNING STATUS - Per-ad-set table: Active / Learning / Learning Limited - Caveats applied to any in-learning analysis 4. PERFORMANCE OVERVIEW - Standardized metric naming (see table below) - Aggregate first, then drill-down - Compare to target where given, benchmarks otherwise 5. DIAGNOSIS - Findings from Phase 3, each tagged to its lens (Marginal / Relevance / Overlap / Pacing / Fluctuation) - Each finding cites specific data 6. RECOMMENDATIONS - Each = hypothesis + expected impact + how to test - Marked Critical / High / Medium / Low priority - Anything paused/scaled has a rollback plan 7. BREAKDOWN EFFECT NOTES - Explicit callouts where average ≠ marginal - "Do not do X" warnings if the data tempts a wrong move ``` ## Output Standards (Mandatory) These are not style suggestions. Violating them produces wrong analysis. - **Never recommend pausing or reducing budget on a segment based solely on higher average CPA/CPM in a breakdown report.** Removing it often raises total cost. State this explicitly when the data tempts a wrong move. - **Every recommendation includes:** evidence cited from the data + the system mechanic that explains it + expected impact + a rollback plan if it doesn't work. - **Every recommendation is a hypothesis,** not a directive. Use "test", "try", "hypothesize" — not "do this". - **Disambiguate clicks.** Never use bare "clicks". Use **Clicks (all)** for total interactions or **Link Clicks** for offsite clicks. - **Audience size language.** Use "Accounts Center accounts" or a bare number. Never "people". If quoting a specific count, use "person" as the noun (e.g., "17,000 person"). - **Check `get_recommendations` first** if you have live API access. If your recommendation diverges from Meta's, explicitly explain why. ## Metric Naming Standard Always rename raw metric names to these standardized display names in any output: | Raw | Display | |---|---| | `impressions` | Impressions | | `reach` | Reach (Accounts Center accounts) | | `frequency` | Frequency | | `spend` | Amount Spent | | `cpm` | CPM | | `clicks` | Clicks (all) | | `cpc` | CPC (all) | | `ctr` | CTR (all) | | `cost_per_action_type:link_click` | CPC (Link Click) | | `outbound_clicks_ctr` | Outbound CTR | | `actions:purchase` | Purchases | | `action_values:purchase` | Purchase Value | | `cost_per_action_type:purchase` | Cost per Purchase | | `purchase_roas` | Purchase ROAS (return on ad spend) | | `video_thruplay_watched_actions` | ThruPlays | ## Reference: Domain Concepts ### The Breakdown Effect The misinterpretation that Meta's system shifts budget into "underperforming" segments. In reality the system maximizes total results by optimizing for **marginal efficiency**. A breakdown report sliced by placement, demographic, or device shows averages — but the system optimizes for the next dollar, not the average. A segment with high average CPA may be protecting overall campaign efficiency by preventing even higher marginal cost elsewhere. ### Learning Phase Delivery state where the system is exploring how to deliver a new or significantly edited ad set. Performance is less stable, CPA is typically higher, and results are not predictive of long-term performance. Exits after ~50 optimization events within 7 days of the last significant edit. **Don't edit during learning** (resets the clock). **Don't fragment** with too many ad sets (each needs its own 50 events). Use **realistic budgets** — too small or too large gives bad signal. ### Auction Overlap When ad sets share overlapping audiences within the same ad account, only the highest-value ad from your portfolio enters each auction. The others are excluded. Symptoms: chronic `Learning Limited`, underspending, erratic delivery. Fix: consolidate ad sets, or pause the lower-performing overlapping ones to free up auction entries. ### Pacing The system spreads spend across the day/period to capture best opportunities. Daily under/overspend is by design — only sustained underspend (3+ days) is a real signal. ### Creative Fatigue Effectiveness decreases as the same audience sees the same creative repeatedly. Watch frequency (>3–4 in a 7-day window for prospecting) and conversion-rate decline while spend stays flat. Refresh creative on a rotation rather than waiting for fatigue to show in CPA. ### Performance Fluctuations Day-to-day CPA variation within 20–30% is normal. Weekend/weekday differences are normal. Sudden ≥50% sustained cost increases over 3+ days, near-zero delivery, or conv-rate drops while spend rises are the only patterns worth diagnosing as "problems." ## What This Skill Will Not Do - **Will not write to your ad account.** Pure analysis. Use Meta Ads Manager or whatever write tool the calling agent has available for execution. - **Will not generate creative.** Use `messaging-ab-tester` for variants and `ad-angle-miner` for source material. - **Will not analyze landing pages.** Use `ad-to-landing-page-auditor` — and use it whenever Conversion Rate Ranking is below average. - **Will not multi-platform compare.** Use `ad-campaign-analyzer` for cross-channel budget reallocation. ## Related Skills - **`ad-campaign-analyzer`** — Multi-platform performance review and budget reallocation. Run this first if you have multiple channels; run `meta-ads-analyzer` after for the Meta-specific deep dive. - **`ad-to-landing-page-auditor`** — Always pair with this when Conversion Rate Ranking is below average. - **`messaging-ab-tester`** — Generate variants when creative fatigue is the diagnosis. - **`meta-ads-campaign-builder`** — Architect a new campaign when the diagnosis points to "rebuild, don't fix". ## Credit Meta system-mechanics framing (Breakdown Effect, Learning Phase, Auction Overlap reference content) adapted from an MIT-licensed Meta ads analyzer project by Mathias Chu.