meta-ads-analyzer

# Meta Ads Analysis & Diagnosis Skill ## When to Use This Skill Use this skill when you need to **analyze and diagnose Meta Ads campaign performance**, including: - Interpreting campaign, ad set, or ad-level performance data - Identifying root causes of performance issues - Generating actionable optimization recommendations - Understanding why Meta's system makes certain budget allocation decisions ## Result Recommendations (MANDATORY for Final Reports) > **IMPORTANT:** The following rules are **MANDATORY** and **MUST be strictly followed** when writing the final analysis report. These are not optional guidelines—they define the required standards for all deliverables. - **NEVER recommend pausing or reducing budget for any segment based solely on higher average CPA/CPM in breakdown reports.** Higher average cost does NOT mean poor performance—it often reflects the system capturing low *marginal* cost opportunities earlier. Removing segments may increase overall costs. Always frame changes as testable hypotheses, not directives. - **ALWAYS justify recommendations with data evidence, Meta's system mechanics, and expected impact on *overall campaign performance*.** - **EVERY insight must include data evidence and explanation.** Every recommendation must be actionable and verifiable. - **USE QUALIFIED LANGUAGE.** Say "Estimated Reach of ~1,000" not "You reached 1,000 people." All metrics are estimates. - **ALIGN WITH OFFICIAL RECOMMENDATIONS.** Check `get_recommendations` API first. If diverging, explicitly acknowledge and explain why. - **Disambiguate clicks.** Never use the term "clicks" alone. Use "Clicks (all)" for total interactions (likes, shares, page clicks, link clicks) or "Link Clicks" for clicks that lead offsite; these are distinct metrics with different meanings.** ## Core Principles - **Holistic First:** Evaluate at aggregate level before drilling down. The system optimizes for the whole, not the parts. - **Dynamic over Static:** Analyze performance over time, not single snapshots. - **Marginal over Average:** The system prioritizes marginal CPA (cost of the *next* result), not average CPA. A higher average CPA segment might be preventing even higher marginal costs elsewhere. ## Analysis Workflow **Reference Documents:** - `references/breakdown_effect.md` - The Breakdown Effect with examples (read this first) - `references/core_concepts.md` - Ad Auction, Pacing, Learning Phase overview - `references/learning_phase.md` - Learning phase mechanics - `references/ad_relevance_diagnostics.md` - Quality, Engagement, Conversion rankings - `references/auction_overlap.md` - Diagnosing auction overlap - `references/pacing.md` - Budget and bid pacing - `references/bid_strategies.md` - Spend-based, goal-based, manual bidding - `references/ad_auctions.md` - How auction winners are determined - `references/performance_fluctuations.md` - Normal vs. concerning fluctuations ### Step 1: Identify the Correct Evaluation Level This is the most critical step to avoid the Breakdown Effect. | Campaign Setup | Correct Evaluation Level | | :--- | :--- | | Advantage+ Campaign Budget (CBO) | **Campaign Level** | | Automatic Placements (without CBO) | **Ad Set Level** | | Multiple Ads within a single Ad Set | **Ad Set Level** | ### Step 2: Analyze with Meta-Specific Lens Focus on these Meta-specific analytical angles: 1. **Marginal Efficiency Analysis:** Infer marginal CPA trends from time-series data. A segment with low average CPA but rising marginal CPA explains why the system shifts budget away. 2. **Ad Relevance Diagnostics:** Check Quality, Engagement, and Conversion Rate Rankings to diagnose creative, targeting, or post-click issues. 3. **Learning Phase Status:** Determine if ad sets are still in learning phase (~50 results needed to exit). ### Step 3: Synthesize Findings Through Breakdown Effect Lens Interpret all findings through the **Breakdown Effect**. Explain *why* the system makes certain decisions. > **Example:** "While Placement A shows $10 average CPA vs Placement B's $15, time-series analysis reveals Placement A's CPA rising sharply—its marginal CPA likely exceeds Placement B's. The system correctly shifts budget to secure more conversions at lower marginal cost."