> ## Documentation Index
> Fetch the complete documentation index at: https://docs.markifact.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Get Pixel Stats

> Get statistics for a Meta Ads pixel with various aggregation types and optional date filtering

The **Get Pixel Stats** node retrieves detailed analytics and performance statistics for your Meta Ads pixel, offering various aggregation methods and filtering options to analyze tracking data.

***

## When to Use It

* Analyze pixel performance and data quality
* Monitor event tracking and conversion patterns
* Identify technical issues with pixel implementation
* Assess data collection across different devices and browsers
* Review custom data field usage and effectiveness
* Optimize pixel configuration based on usage patterns
* Generate reports for stakeholders and compliance
* Debug tracking issues and data gaps

***

## Inputs

| Field                   | Type       | Required | Description                                                 |
| ----------------------- | ---------- | -------- | ----------------------------------------------------------- |
| **Account**             | Select     | Yes      | Select the Meta Ads account containing the pixel            |
| **Pixel**               | Select     | Yes      | Select the specific pixel to get statistics for             |
| **Aggregation**         | Select     | No       | How to group the statistics (default: event\_total\_counts) |
| **Date Range**          | Date Range | No       | Time period for statistics (default: last 28 days)          |
| **Time Grouping**       | Select     | No       | Group by timestamp or date (default: time)                  |
| **Event Source Filter** | Select     | No       | Filter by web/server events (default: all)                  |

### Aggregation Options

| Option                   | Description                           | Use Case                           |
| ------------------------ | ------------------------------------- | ---------------------------------- |
| **event\_total\_counts** | Total event counts by type            | Overall pixel performance overview |
| **event**                | Detailed event data with filters      | Specific event analysis            |
| **event\_source**        | Events grouped by source (web/server) | Compare web vs CAPI performance    |
| **pixel\_fire**          | Pixel firing statistics               | Technical monitoring               |
| **host**                 | Events grouped by website domain      | Multi-site tracking analysis       |
| **url**                  | Events grouped by specific URLs       | Page-level performance             |
| **browser\_type**        | Events by browser type                | Browser compatibility analysis     |
| **device\_os**           | Events by operating system            | Device targeting insights          |
| **device\_type**         | Events by device category             | Mobile vs desktop analysis         |
| **match\_keys**          | Data matching quality stats           | Attribution accuracy assessment    |

***

## Output

Returns statistics based on your selected aggregation method:

### Event Total Counts Example:

```json theme={"dark"}
[
  {
    "event_name": "PageView",
    "count": 15420,
    "timestamp": "2024-10-16T00:00:00Z"
  },
  {
    "event_name": "Purchase",
    "count": 342,
    "timestamp": "2024-10-16T00:00:00Z"
  }
]
```

### Event Source Example:

```json theme={"dark"}
[
  {
    "event_name": "Purchase",
    "source": "web",
    "count": 180,
    "percentage": 52.6
  },
  {
    "event_name": "Purchase", 
    "source": "server",
    "count": 162,
    "percentage": 47.4
  }
]
```

### Device Type Example:

```json theme={"dark"}
[
  {
    "device_type": "desktop",
    "event_count": 8234,
    "percentage": 53.4
  },
  {
    "device_type": "mobile",
    "event_count": 7186,
    "percentage": 46.6
  }
]
```

***

## Credit Cost

* **Cost per run**: 1 credit

***

## FAQs

<Accordion title="Which aggregation method should I use for different analysis needs?">
  **For Overall Performance Monitoring:**

  * **event\_total\_counts**: Best starting point - shows all event volumes
  * **event**: Detailed breakdown with filtering options

  **For Technical Analysis:**

  * **event\_source**: Compare web pixel vs Conversions API performance
  * **pixel\_fire**: Monitor pixel installation and firing issues
  * **browser\_type/device\_os**: Identify compatibility issues

  **For Business Intelligence:**

  * **host**: Analyze performance across different websites
  * **url**: Identify high/low performing pages
  * **device\_type**: Understand user behavior patterns

  **For Data Quality Assessment:**

  * **match\_keys**: Review data matching and attribution quality
  * **custom\_data\_field**: Analyze custom parameter usage

  **Pro tip**: Start with event\_total\_counts for overview, then drill down with specific aggregations.
</Accordion>

<Accordion title="How do I interpret event source data (web vs server)?">
  **Event Source Types:**

  **Web Events (Browser Pixel):**

  * Tracked directly from user's browser
  * Real-time user interactions
  * Subject to ad blockers and privacy settings
  * May miss some conversions due to technical issues

  **Server Events (Conversions API):**

  * Sent from your server to Meta
  * More reliable and comprehensive
  * Not affected by ad blockers
  * Better for sensitive data and offline events

  **Healthy Distribution:**

  * **50/50 split**: Excellent - both sources working well
  * **70% web / 30% server**: Good - strong browser tracking
  * **30% web / 70% server**: Good - strong server integration
  * **90%+ from one source**: Check the other source setup

  **Optimization Goals:**

  * Aim for both sources active for redundancy
  * Server events improve data quality and match rates
  * Use server events for sensitive data (purchases, leads)
  * Web events good for engagement tracking
</Accordion>

<Accordion title="What insights can I get from device and browser data?">
  **Device Type Analysis:**

  * **Mobile dominance**: Optimize for mobile experience and ads
  * **Desktop preference**: Focus on desktop-optimized content
  * **Balanced usage**: Ensure responsive design and cross-device tracking

  **Browser Type Insights:**

  * **Chrome/Safari/Firefox distribution**: Check compatibility
  * **Unusual patterns**: May indicate bot traffic or technical issues
  * **Privacy-focused browsers**: Expect lower tracking rates

  **Operating System Data:**

  * **iOS vs Android**: Mobile app and campaign optimization
  * **Windows/Mac distribution**: Desktop experience optimization
  * **Version information**: Compatibility and feature support

  **Business Applications:**

  * **Ad creative optimization**: Design for dominant platforms
  * **User experience improvements**: Focus development efforts
  * **Targeting strategy**: Adjust campaigns based on user preferences
  * **Technical troubleshooting**: Identify platform-specific issues

  **Red Flags:**

  * Sudden shifts in device/browser distribution
  * Extremely low counts from major browsers/devices
  * Inconsistent patterns compared to industry benchmarks
</Accordion>

<Accordion title="How can I use URL and host data for optimization?">
  **URL-Level Analysis:**

  * **High-converting pages**: Identify your best-performing content
  * **Drop-off points**: Find where users leave your funnel
  * **Event distribution**: See which pages drive specific actions
  * **A/B testing insights**: Compare performance across page variants

  **Host-Level Analysis:**

  * **Multi-domain tracking**: Compare performance across properties
  * **Subdomain optimization**: Identify strong/weak areas
  * **Campaign landing pages**: Analyze dedicated campaign sites
  * **Partner integrations**: Track third-party domain performance

  **Optimization Strategies:**

  * **Improve low-performing pages**: Focus UX improvements
  * **Replicate success**: Apply high-performing page elements elsewhere
  * **Adjust traffic allocation**: Send more traffic to converting pages
  * **Fix technical issues**: Address pages with tracking problems

  **Common Patterns:**

  * **Homepage dominance**: May indicate navigation issues
  * **Checkout abandonment**: Focus on conversion optimization
  * **Blog engagement**: Content marketing effectiveness
  * **Product page variations**: Compare product performance

  **Pro tip**: Use this data to inform content strategy and user experience improvements.
</Accordion>

<Accordion title="What do match keys statistics tell me about data quality?">
  **Match Keys Explained:**
  Match keys are data points used to connect pixel events with Meta user profiles:

  * **Email addresses**
  * **Phone numbers**
  * **External IDs**
  * **Facebook user IDs**

  **Key Metrics:**

  * **Match rate**: Percentage of events with successful user matching
  * **Coverage**: How many events include each type of match key
  * **Quality scores**: Accuracy and reliability of matches

  **Quality Indicators:**

  * **High email match rates**: Good customer data collection
  * **Strong phone number coverage**: Comprehensive contact information
  * **External ID usage**: Effective CRM integration
  * **Low match rates**: Data quality or collection issues

  **Improvement Strategies:**

  * **Collect better data**: Improve form fields and data capture
  * **Implement hashing**: Properly format customer data
  * **Use Conversions API**: Send server-side data for better matching
  * **Enable automatic matching**: Let Meta optimize connections

  **Business Impact:**

  * Better attribution accuracy
  * Improved ad targeting effectiveness
  * Higher conversion tracking reliability
  * Enhanced audience building capabilities
</Accordion>

<Accordion title="How should I set up date ranges for meaningful analysis?">
  **Recommended Date Ranges:**

  **Daily Monitoring (1-7 days):**

  * **Use case**: Real-time issue detection
  * **Time grouping**: By hour or timestamp
  * **Focus**: Technical problems, campaign launches

  **Weekly Analysis (7-14 days):**

  * **Use case**: Campaign performance review
  * **Time grouping**: By date
  * **Focus**: Trend identification, optimization opportunities

  **Monthly Reviews (28-90 days):**

  * **Use case**: Strategic analysis and reporting
  * **Time grouping**: By date or week
  * **Focus**: Long-term patterns, seasonal effects

  **Quarterly Audits (90+ days):**

  * **Use case**: Comprehensive pixel health assessment
  * **Time grouping**: By week or month
  * **Focus**: Infrastructure changes, business growth impact

  **Comparative Analysis:**

  * **Year-over-year**: Same period previous year
  * **Month-over-month**: Compare recent months
  * **Before/after**: Major website or campaign changes

  **Pro tips:**

  * Use consistent date ranges for trend analysis
  * Account for seasonality in your business
  * Include sufficient data for statistical significance
  * Consider external factors (holidays, market events)
</Accordion>

<Accordion title="What should I do if I see concerning patterns in my pixel stats?">
  **Common Issues and Solutions:**

  **Sudden Drop in Events:**

  * **Check**: Website changes, pixel code modifications
  * **Action**: Verify pixel installation, test with Pixel Helper
  * **Timeline**: Address immediately

  **Low Match Rates:**

  * **Check**: Customer data quality, CAPI implementation
  * **Action**: Improve data collection, implement server events
  * **Timeline**: Plan for gradual improvement

  **Unusual Device/Browser Patterns:**

  * **Check**: Bot traffic, technical restrictions
  * **Action**: Implement bot filtering, check compatibility
  * **Timeline**: Monitor and adjust over time

  **High Web vs Server Imbalance:**

  * **Check**: CAPI setup, server event configuration
  * **Action**: Implement or fix Conversions API
  * **Timeline**: Technical implementation project

  **URL/Host Issues:**

  * **Check**: Tracking code placement, page load issues
  * **Action**: Fix technical implementation, optimize pages
  * **Timeline**: Development sprint planning

  **Monitoring Best Practices:**

  * Set up automated alerts for significant changes
  * Regular weekly reviews of key metrics
  * Document known issues and planned fixes
  * Compare against industry benchmarks when available
</Accordion>

<Accordion title="Can I export this data for further analysis?">
  **Data Export Options:**

  **Direct Use:**

  * Copy JSON output for spreadsheet analysis
  * Use data in subsequent workflow nodes
  * Generate reports within Markifact

  **Integration Approaches:**

  * **Google Sheets**: Connect output to spreadsheet for team access
  * **BI Tools**: Feed data into business intelligence platforms
  * **Dashboards**: Create automated reporting workflows
  * **APIs**: Use data in custom applications

  **Analysis Recommendations:**

  * **Trend Analysis**: Track metrics over time
  * **Comparative Studies**: Compare across pixels or time periods
  * **Correlation Analysis**: Relate pixel performance to business metrics
  * **Forecasting**: Predict future performance based on trends

  **Reporting Best Practices:**

  * **Stakeholder-specific views**: Customize reports for different audiences
  * **Regular cadence**: Set up automated reporting schedules
  * **Context inclusion**: Add business context to raw data
  * **Action items**: Include recommendations with data insights

  **Pro tip**: Combine pixel stats with business data (sales, traffic, campaigns) for comprehensive analysis.
</Accordion>