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    noon ads optimizer

    1

    Analyze Noon Ad Manager Excel exports to identify wasted spend and generate manual bid adjustment checklists.

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    noon ads optimizer

    noon ads optimizer

    Example session with this skill installed

    Analyze the attached 'noon_campaign_july.xlsx' with a target ROAS of 8.0 and generate a manual action plan for bid adjustments.

    • Read your context and instructions
    • Compiled the noon ads optimizer
    • Generated the data export

    I have analyzed noon_campaign_july.xlsx. The audit covered 142 targets across 3 campaigns. Total spend reconciled within 0.2% of sheet totals. I have identified 12 high-waste targets and 4 scaling opportunities.

    Noon Ads Analysis: July Campaign Export

    CategoryCountTotal Spend (SAR)Total Revenue (SAR)Avg. ROAS
    High Waste (ROAS < 2.0)8450.5045.000.10
    Scaling (ROAS > 12.0)4120.001,850.0015.42
    Under-performing15890.004,200.004.72
    Total Audited1424,560.2532,450.007.12

    Recommended Manual Actions

    
### 1. High Confidence Bid Reductions (Action: PAUSE or REDUCE)
- SKU: B07NCW - Spend: 155.20 | Orders: 0 | Action: PAUSE
- Query: "iphone case" - Spend: 88.40 | ROAS: 0.4 | Action: REDUCE BID 30%
- Target: Electronics_Auto_Campaign_1 - Spend: 210.00 | ROAS: 1.2 | Action: REDUCE BID 50%

### 2. Scaling Opportunities (Action: INCREASE)
- SKU: B08XX1 - Spend: 45.00 | ROAS: 18.2 | Orders: 12 | Action: INCREASE BID 15%
- Query: "wireless charger fast" - Spend: 32.00 | ROAS: 22.0 | Action: PROMOTE TO EXACT

### 3. Data Warnings
- Discrepancy: Campaign 'Summer_Sale' summary shows SAR 1,200 spend, but SKU total is 1,195. Verify missing SKUs.

    Next steps

    1. Download the generated manual_actions.csv for the full list of 27 recommended changes.
    2. Open Noon Ad Manager and apply the 'High Confidence' reductions first to stop immediate budget bleed.
    3. Verify if the 'wireless charger' query exists as a standalone target before increasing the bid.

    noon_campaign_july.xlsx

    CSV · data export

    Generated

    Example file from a real run - the skill writes it into your workspace.

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

    About this skill

    Noon Ad Manager provides limited automation, often forcing sellers to waste hours manually parsing Excel exports. This skill automates the heavy lifting of auditing Noon Ads .xlsx workbooks to find wasted spend and scaling opportunities. It processes raw report data to identify non-converting search terms, zero-order SKU targets, and budget bleed without the risk of blind automation.

    What it does

    • Data Reconciliation verifies that campaign summary totals match granular SKU and placement data to catch reporting discrepancies.
    • Waste Identification flags high-spend, low-conversion targets and search queries that drain budget without generating orders.
    • Bid Optimization generates structured manual action plans for bid reductions or increases based on a target ROAS benchmark.
    • Batch Processing consolidates multiple campaign exports into a single account-wide performance report with SHA-256 deduplication.
    • Actionable Reporting produces formatted Markdown summaries and CSV checklists ready for manual execution in the Noon dashboard.

    How it works

    1. Load Export by providing one or more Noon Ad Manager .xlsx workbooks for analysis.
    2. Set Benchmarks by defining target ROAS and order thresholds to separate statistical noise from real performance trends.
    3. Review Diagnostics via the generated summary reports to identify data quality issues or cross-campaign overlaps.
    4. Execute Plan using the manual_actions.csv checklist to update bids and status directly in the Noon Ad Manager UI.

    Frameworks & tools

    Built for Python 3.8+ environments using openpyxl for deterministic Excel parsing. It focuses on local data processing and does not require external API access.

    Why this beats prompting it yourself

    Generic LLM prompts struggle with large Excel files and often hallucinate math across thousands of rows. This skill uses programmatic verification to ensure every recommended bid change is grounded in actual sheet totals and pre-defined statistical thresholds.

    Use cases

    • Auditing monthly Noon Ads performance to cut non-performing search queries.
    • Scaling high-ROAS SKUs that meet minimum order volume requirements.
    • Reconciling fragmented campaign reports into a single account-level view.
    • Generating client-ready executive summaries for ad agency reporting.

    Known limitations

    This tool does not support direct API mutation as Noon lacks a public ads API. It requires product margins and COGS input from the user to calculate true net profitability.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Python

    Listed11 days ago

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