Overview

Track how your schema quality evolves over time. Visualize daily validation counts, average scores, error rates, and improvement trends with interactive charts.

How It Works

1. Data is aggregated from validation history
2. Daily breakdowns show:
– Number of validations
– Average completeness score
– Error count trends
– Most common error types
3. Time range is configurable (7d, 30d, 90d, custom)
4. Data powers dashboard charts

Tier Availability

| Tier | Available |
|——|———–|
| Free | No |
| Pro | Yes |
| Agency | Yes |
| Enterprise | Yes |

Related Features

– Validation History: Raw data source for trends
– Site-Wide Score: Current snapshot vs temporal evolution

Mini-Tutorial

Step 1: Choose Your Time Range

Navigate to Analytics > Trends and select a period: 7 days, 30 days, or 90 days. Longer periods reveal seasonal patterns.

Step 2: Examine Daily Breakdown

The chart shows daily validation counts. Spikes may indicate content launches or bulk updates.

Step 3: Analyze Score Trends

Watch the blue line tracking average completeness score over time. An upward trend means improvements; declining trends indicate regression.

Step 4: Identify Error Patterns

The error section reveals common issues. If you see “missing aggregateRating” appearing consistently, it’s a priority fix across your site.

Step 5: Export for Stakeholders

Use the “Export Trend Data” button to download CSV for presentations or detailed analysis.

Technical Details

Request

GET /api/v1/trends?period=30d&project_id=abc123

Response Example

{
  "period": "30d",
  "summary": {
    "total_validations": 342,
    "valid": 324,
    "invalid": 18,
    "avg_score": 81.5
  },
  "daily_data": [
    {
      "date": "2025-02-22",
      "total": 10,
      "valid": 9,
      "invalid": 1,
      "avg_score": 79.2,
      "avg_errors": 1.1
    },
    {
      "date": "2025-02-23",
      "total": 15,
      "valid": 14,
      "invalid": 1,
      "avg_score": 82.0,
      "avg_errors": 0.9
    }
  ],
  "type_distribution": {
    "Article": 145,
    "Product": 98,
    "Organization": 62,
    "Review": 37
  },
  "top_errors": [
    {
      "error": "missing aggregateRating",
      "count": 23,
      "frequency": 0.067
    },
    {
      "error": "invalid url",
      "count": 8,
      "frequency": 0.023
    }
  ],
  "trend": {
    "improvement": true,
    "score_change": 4.2,
    "error_improvement": 0.15
  }
}

Query Parameters

– period: 7d, 30d, 90d (required)
– project_id: Filter by project (optional)
– schema_type: Filter by schema type, e.g., “Article” (optional)

References

– Schema.org Full Hierarchy
– JSON-LD Context Specification
– Time Series Data Analysis Best Practices
– ValidGraph Trends API Documentation