Facebook Ads AI Performance Analyzer

What This Agent Does

This powerful workflow automates your Facebook Ads performance analysis and reporting by combining real-time ad data with AI-powered insights. The agent pulls your latest Facebook Ads metrics, analyzes performance against industry benchmarks, generates strategic recommendations from a Senior Media Buyer perspective, and automatically populates a Google Sheet with actionable insights—all triggered with a single click.

Key benefits and time savings:

• Eliminate manual reporting: Automatically fetch and analyze ad performance without copy-pasting data
• AI-powered insights: Leverage advanced AI analysis to identify optimization opportunities instantly
• Benchmark comparison: Understand how your ads perform against industry standards
• Centralized reporting: All insights flow directly into your Google Sheet for easy sharing and tracking
• Save 2-3 hours weekly: Reduce time spent on ad analysis and reporting tasks

Target use cases:

• Digital marketing agencies managing multiple client ad accounts
• E-commerce businesses optimizing ad spend across campaigns
• Marketing teams conducting weekly performance reviews
• Performance marketers seeking data-driven optimization recommendations

Who Is It For

This workflow is ideal for marketing professionals and teams who:

• Run Facebook Ads campaigns and need regular performance analysis
• Want AI-powered recommendations without hiring additional analysts
• Prefer automated reporting over manual spreadsheet updates
• Need to justify ad spend with data-backed insights
• Manage multiple ad accounts and require consistent analysis

Whether you're a solo marketer, agency owner, or part of a larger marketing team, this agent streamlines your workflow and elevates your decision-making with intelligent analysis.

Required Integrations

Facebook Ads

Why it's needed: This integration connects TaskAGI to your Facebook Ads account, enabling the workflow to retrieve real-time performance metrics for all your active campaigns and ads.

Setup steps:

1. Navigate to the Integrations section in TaskAGI
2. Search for and select Facebook Ads
3. Click Connect or Authenticate
4. You'll be redirected to Meta's login page—sign in with your Facebook account
5. Review and approve the requested permissions (access to ad accounts and insights)
6. Confirm the integration is active by seeing a green checkmark

How to obtain API keys/credentials:

• TaskAGI uses OAuth 2.0 authentication, so you don't need manual API keys
• Ensure your Facebook account has Admin or Analyst access to the ad account you want to analyze
• If you manage multiple ad accounts, you can select which account to pull data from during workflow configuration

Configuration in TaskAGI:

• After authentication, select your Ad Account ID from the dropdown menu
• Choose your preferred date range for data retrieval (last 7 days, 30 days, custom range)
• Select metrics to retrieve such as: Impressions, Clicks, Spend, Conversions, ROAS, CPC, CTR
• Test the connection by clicking Verify Connection

Google Gemini

Why it's needed: Google Gemini (powered by Gemini 2.5 Flash) provides the AI analysis engine that transforms raw ad data into strategic, actionable recommendations using advanced language models.

Setup steps:

1. Go to Integrations in TaskAGI and search for Google Gemini
2. Click Connect or Add Integration
3. Sign in with your Google account (use the account associated with Google Cloud)
4. Grant TaskAGI permission to access Google Gemini API
5. Verify the integration shows as Active

How to obtain API keys/credentials:

• Visit Google Cloud Console
• Create a new project or select an existing one
• Enable the Gemini API in your project
• Generate an API key from the Credentials section
• Copy the API key and paste it into TaskAGI's integration settings
• Alternatively, use OAuth authentication (recommended for security)

Configuration in TaskAGI:

• Select Model: gemini-2.5-flash (already pre-configured in this workflow)
• Set Temperature: 0.7 (balances creativity with consistency)
• Set Max tokens: 2000 (sufficient for detailed analysis)
• The AI prompt is pre-configured with a Senior Media Buyer persona—you can customize it if needed

Google Sheets

Why it's needed: Google Sheets serves as your centralized repository for all AI-generated insights, creating a permanent record of analysis and recommendations that your team can access, share, and reference.

Setup steps:

1. Open Integrations in TaskAGI and find Google Sheets
2. Click Connect or Authenticate
3. Sign in with your Google account
4. Authorize TaskAGI to create, read, and modify spreadsheets
5. Confirm the integration is active

How to obtain API keys/credentials:

• Google Sheets uses OAuth authentication (no manual API keys needed)
• Ensure your Google account has Editor access to the spreadsheet you'll use
• If sharing with team members, grant them Editor permissions on the Google Sheet

Configuration in TaskAGI:

• Create a new Google Sheet or use an existing one
• Copy the Sheet URL from your browser's address bar
• In the workflow node "Update Sheet with AI Insights," paste the Sheet URL in the sheet_url parameter
• Define column headers in your Sheet: Ad Name, Campaign, Spend, ROAS, AI Insights, Recommendations, Date
• Test by running a workflow execution and verifying data appears in your Sheet

Configuration Steps

Node-by-Node Configuration Guidance

1. Overview Node (core.workflow_note)

• This is a documentation node—no configuration needed
• It displays workflow purpose and instructions to users
• Update the note with your team's specific goals or guidelines

2. Manual Trigger (trigger.manual)

• Configuration: No setup required
• How it works: Click the "Run Workflow" button to execute the entire analysis
• Tip: Schedule regular runs (e.g., every Monday morning) using TaskAGI's scheduling feature

3. Get Facebook Ads Insights (facebookads.getInsightsAdvanced)

• Parameters to configure:
  • ad_account_id: Select from authenticated Facebook account dropdown
  • date_range: Choose last_7_days, last_30_days, or specify custom dates
  • metrics: Select all relevant metrics (Impressions, Clicks, Spend, Conversions, ROAS, CPC, CTR)
  • breakdown_by: Set to ad to get individual ad performance
• Example output: JSON array containing all ads with their performance metrics
• Data passed to next node: Raw ad performance data

4. Process Ad Data (core.function)

• Purpose: Cleans and structures raw Facebook data for analysis
• Configuration:
  • Input: Raw insights from Facebook Ads node
  • Function: Filters out underperforming ads (optional threshold)
  • Output: Structured array of ad objects with standardized fields
• Example transformation: Converts spend from cents to dollars, rounds metrics to 2 decimals

5. Calculate Benchmarks (core.function)

• Purpose: Computes industry benchmarks and performance ratios
• Configuration:
  • Input: Processed ad data
  • Calculations: Average ROAS, median CPC, CTR benchmarks by industry
  • Output: Benchmark object with comparative metrics
• Example: If your average ROAS is 3.2, this node identifies it as "above average" (benchmark: 2.5)

6. AI Media Buyer Analysis (googlegemini.generateContent)

• Pre-configured prompt: Senior Facebook Ads Media Buyer persona
• Input data: Processed ads + calculated benchmarks
• Configuration:
  • Model: gemini-2.5-flash
  • Temperature: 0.7
  • Max tokens: 2000
• Prompt includes: Performance analysis, optimization recommendations, budget allocation suggestions
• Output: Detailed AI analysis as text

7. Parse AI Response (core.parse_output)

• Purpose: Extracts structured insights from AI's text response
• Configuration:
  • Input: Raw AI analysis text
  • Parsing rules: Extract recommendations, insights, and action items
  • Output: Structured JSON with categorized insights
• Example output: { "strengths": [...], "improvements": [...], "actions": [...] }

8. Prepare Raw Data for Sheets (core.function)

• Purpose: Formats all data for Google Sheets insertion
• Configuration:
  • Input: Processed ads + AI insights
  • Formatting: Creates rows matching your Sheet structure
  • Output: Array of row objects ready for Sheets

9. Loop Through AI Analysis (core.loop)

• Purpose: Iterates through each ad to update the Sheet individually
• Configuration:
  • Loop over: Prepared data rows
  • Iteration variable: current_ad
  • Loop path: Connects to "Find Row for Ad" node

10. Find Row for Ad (core.function)

• Purpose: Locates the correct row in Google Sheets for each ad
• Configuration:
  • Input: Current ad from loop
  • Search criteria: Match ad name or ID
  • Output: Row number in Sheet

11. Update Sheet with AI Insights (googlesheets.appendRowFromUrl)

• Critical configuration:
  • sheet_url: Paste your Google Sheet URL (currently null—must be configured)
  • sheet_name: Name of the worksheet (e.g., "Ad Analysis")
  • values: Array of data to insert (ad name, metrics, AI insights)
  • append_mode: Set to true to add new rows without overwriting
• Example Sheet URL: https://docs.google.com/spreadsheets/d/1a2b3c4d5e6f7g8h9i0j/edit

Testing Your Agent

Step 1: Pre-Execution Checklist

Before running your workflow, verify:

• ✅ Facebook Ads integration is authenticated and shows active
• ✅ Google Gemini integration is connected
• ✅ Google Sheets integration is authorized
• ✅ Sheet URL is entered in the "Update Sheet with AI Insights" node
• ✅ Your Google Sheet has proper column headers
• ✅ You have at least 3-5 active ads in your Facebook account

Step 2: Run Test Execution

1. Click the Run Workflow button in TaskAGI
2. Monitor the execution in real-time using the Execution Log
3. Watch for green checkmarks indicating successful node completion

Step 3: Verify at Each Step

After "Get Facebook Ads Insights":

• Check the output contains your ad data
• Verify metrics are populated (spend, impressions, clicks)
• Confirm date range matches your selection

After "Calculate Benchmarks":

• Review benchmark values are reasonable
• Verify ROAS and CPC calculations are correct
• Check that comparisons show "above/below average" status

After "AI Media Buyer Analysis":

• Read the AI-generated insights in the execution log
• Verify recommendations are specific and actionable
• Ensure the analysis mentions actual ad names and metrics

After "Update Sheet with AI Insights":

• Open your Google Sheet
• Verify new rows have been added with all data
• Check that AI insights are properly formatted and readable

Step 4: Expected Results and Success Indicators

Successful execution shows:

• ✅ All 11 nodes complete without errors (red indicators)
• ✅ Execution time: 30-60 seconds (depending on ad account size)
• ✅ New rows appear in your Google Sheet within 2 minutes
• ✅ AI insights are detailed, specific, and reference actual ad performance
• ✅ No duplicate rows (if running multiple times)

Common issues and solutions:

• "Sheet URL is null" error: Paste your Google Sheet URL in the final node
• No data appears: Verify Facebook Ads account has active campaigns
• Duplicate rows: Enable deduplication in the Sheets node
• AI insights are generic: Check that benchmark data is being passed correctly

Next steps after successful test:

1. Review the AI insights and verify they're actionable
2. Customize the AI prompt if needed for your industry
3. Set up a schedule to run this workflow weekly or daily
4. Share the Google Sheet with your team for collaborative review

Congratulations! Your Facebook Ads analysis agent is now live and ready to transform your ad performance data into strategic insights.