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    Ad Performance Decision Engine

    1

    A decision-support engine for advertisers to diagnose funnel leaks and determine when to scale, optimize, or pause ads.

    $9.99

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    Ad Performance Decision Engine

    Ad Performance Decision Engine

    Example session with this skill installed

    Analyze this Meta ecommerce ad. Spend: $1,200. CTR: 2.1%. Landing Page Conv: 3%. Purchases:
    12. CPA: $100. Target CPA: $60. Trend: CPA was $80 last week. objective: Purchases. Funnel: Bottom.

    • Read your context and instructions
    • Compiled the ad performance decision

    The provided data indicates a significant efficiency gap between current performance and the business target, with costs trending in the wrong direction despite healthy top-of-funnel engagement.

    Ad Performance Decision Snapshot

    Decision: OPTIMIZE

    • Confidence: High

    Primary Reason: CPA is 66% above target and deteriorating despite a strong CTR, indicating a mid-to-bottom funnel breakdown.

    Main Evidence: CTR (2.1%) is above average, but Landing Page Conversion (3%) is insufficient to sustain the $60 CPA target at the current CPC.

    Main Risk: Continued spend will lead to further margin erosion if the conversion rate bottleneck is not addressed.

    • Recommended Next Action: Audit the landing page for message-match and mobile friction.

    Funnel Health Check

    StageMetricCurrentTrendAssessment
    AttentionCTR2.1%StableStrong; ad is winning the click.
    LandingCVR3.0%WeakBottleneck; traffic is not converting.
    BusinessCPA$100DeterioratingCritical; exceeds $60 target.

    Optimization Plan

    Bottleneck → Evidence → Likely Cause → Optimization → Metric to Watch
    *

    Conversion Rate → 3% CVR vs $100 CPA → High friction or offer mismatch → Simplify checkout/match ad copy to LP → CVR and CPA.

    Next steps

    • Review the landing page specifically for mobile loading speed and offer clarity.
    • Verify if the $1,200 spend has reached audience saturation (check frequency if available).
    • If CVR does not improve within the next $200 of spend, move to PAUSE.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Advertisers often struggle to interpret raw performance data, leading to emotional decisions, premature budget cuts, or wasted spend on failing creatives. Without a structured diagnostic framework, it is difficult to isolate whether a performance drop is caused by the ad creative, the landing page, or the bidding strategy.

    What it does

    • Analyzes multi-platform ad data (Meta, Google, TikTok, LinkedIn) to classify creatives into actionable categories: Scale, Optimize, Test, Hold, or Pause.
    • Diagnoses funnel leaks by mapping metrics across impression, click, landing page, and conversion stages.
    • Evaluates creative performance against business economics like target CPA, break-even ROAS, and contribution margins.
    • Identifies specific bottlenecks such as weak hooks, high friction offers, or audience saturation.
    • Generates structured test hypotheses for underperforming assets to isolate variables before full resets.

    Why this beats prompting it yourself

    This skill enforces a rigorous DATA to DECISION workflow that prevents common AI hallucinations regarding statistical significance. It uses specific diagnostic modes for different business objectives like Awareness, Leads, or Ecommerce, ensuring recommendations align with actual financial goals rather than just surface-level engagement metrics.

    Use cases

    • Auditing a weekly Meta Ads report to identify which high-spend creatives are actually driving profitable sales.
    • Troubleshooting a high-CTR campaign that is failing to convert on the landing page.
    • Determining if a new TikTok creative has sufficient data to be declared a winner or if it needs more budget.
    • Prioritizing optimization tasks across a multi-ad account based on confidence levels and trend stability.

    Known limitations

    Does not execute API calls to ad platforms or make live budget changes. Performance outcomes are never guaranteed.

    Ad Performance Decision Engine helps advertisers make better decisions about ads that are already running. It does not focus on generating ad copy. Instead, it analyzes campaign evidence and determines the most appropriate next action: 📈 SCALE — when performance and economics support continued investment 🔧 OPTIMIZE — when a specific bottleneck can be improved 🧪 TEST — when more controlled experimentation is needed 👀 HOLD — when performance is still developing ⏸️ PAUSE — when evidence shows persistent unacceptable performance 📊 GATHER MORE DATA — when the available evidence is insufficient It evaluates the complete funnel rather than blindly optimizing one metric. Core Workflow DATA → CONTEXT → DIAGNOSE → CLASSIFY → DECIDE → EXPLAIN → NEXT ACTION

    Requires manual input of ad performance data. Does not connect directly to ad platform APIs. Cannot verify the accuracy of user-provided tracking or attribution data.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This engine uses a structured diagnostic framework to analyze your funnel metrics, helping you distinguish whether a performance drop is due to creative fatigue, landing page friction, or bidding strategy, thereby removing emotional bias from your budget decisions.

    The skill works with data exported from any major platform, including Meta, Google, TikTok, and LinkedIn, as long as you provide the relevant impression, click, and conversion metrics for analysis.

    Unlike generic prompts, this skill uses a specialized 'Data-to-Decision' workflow that accounts for statistical significance and specific business objectives (like Lead Gen vs. Ecom) to prevent the AI from hallucinating conclusions based on surface-level metrics.

    You will receive the proprietary logic and structured workflow required to run the Ad Performance Decision Engine on your preferred AI agent platform, along with documentation on how to input your data for the most accurate results.

    No, this is a diagnostic tool designed to provide strategic recommendations; it does not have the authority to make live budget changes or API calls to your ad accounts, ensuring you maintain full control over your spend.

    To get the most out of the engine, you should provide standard performance data including spend, impressions, CTR, CPC, conversion rate, and your specific financial targets like target CPA or break-even ROAS.

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