Customize SEO Metrics in Looker Studio

Customizing Dimensions and Metrics for SEO

When using tools like Google Search Console, BigQuery, and Looker Studio for SEO analysis, you can customize dimensions and metrics to gain deeper insights tailored to your specific goals. Customizing SEO dimensions and metrics enables you to focus on what matters most, from tracking specific keywords to measuring the performance of different content types.

1. Why Customize SEO Dimensions and Metrics?

Standard dimensions and metrics, such as clicks, impressions, and position, are useful but may not cover all the insights you need. Customizing allows you to:

• Measure performance according to your unique business needs, like analyzing by product category, user intent, or page type.
• Focus on specific segments, such as branded vs. non-branded keywords or mobile vs. desktop traffic.
• Tailor reports for stakeholders by emphasizing metrics aligned with company goals.

Custom dimensions and metrics add flexibility, letting you analyze SEO data in ways that standard reports don’t support.

2. Setting Up Custom Dimensions and Metrics in BigQuery

To begin with SEO metrics customization, you’ll use SQL in BigQuery to define new dimensions and metrics based on existing data.

• Step 1: Define Custom Dimensions in BigQuery

  • Dimensions describe the characteristics of your data, such as query type or country. Define new dimensions by creating custom fields using SQL. For instance, create a dimension that separates branded from non-branded queries:

    SELECT
      query,
      country,
      clicks,
      impressions,
      CASE
        WHEN query LIKE '%brand%' THEN 'Branded'
        ELSE 'Non-Branded'
      END AS brand_type
    FROM
      `your_project.your_dataset.search_data`;

  • This query adds a new “brand_type” dimension that labels each query as either “Branded” or “Non-Branded.”

• Step 2: Define Custom Metrics in BigQuery

  • Metrics measure performance, such as click-through rate or conversion rate. To create a custom metric, calculate it based on existing fields. For example, define a custom metric for click-through rate (CTR):

    SELECT
      query,
      clicks,
      impressions,
      (clicks / impressions) * 100 AS ctr_percentage
    FROM
      `your_project.your_dataset.search_data`;

  • This metric calculates CTR as a percentage, giving you a better understanding of how often users click on your content after seeing it in search results.

• Step 3: Combine Custom Dimensions and Metrics for Specific Analysis

  • By combining custom dimensions and metrics, you can create targeted insights. For example, calculate the CTR for branded keywords in the U.S.:

    SELECT
      query,
      clicks,
      impressions,
      (clicks / impressions) * 100 AS ctr_percentage,
      country,
      CASE
        WHEN query LIKE '%brand%' THEN 'Branded'
        ELSE 'Non-Branded'
      END AS brand_type
    FROM
      `your_project.your_dataset.search_data`
    WHERE
      country = 'US'
    AND brand_type = 'Branded';

  • This query provides the CTR for branded queries in the U.S., helping you assess engagement with brand-related searches in this region.

3. Using Custom Dimensions and Metrics in Looker Studio

Once you’ve created custom dimensions and metrics in BigQuery, connect them to Looker Studio for clear, visual reporting.

• Step 1: Connect BigQuery Data with Custom Fields to Looker Studio

  • Add BigQuery as a data source in Looker Studio and include the custom fields you’ve created.

• Step 2: Visualize Custom Dimensions and Metrics

  • Set up charts, tables, or graphs to display these custom dimensions and metrics. For instance:
    • A pie chart for “Branded” vs. “Non-Branded” clicks helps you see the distribution of traffic across these segments.
    • A bar chart for CTR by country highlights performance differences across regions.

• Step 3: Use Filters and Segments for Deeper Analysis

  • Apply filters to refine your analysis based on specific custom fields. For example, filter by “Branded” keywords or by country, allowing you to focus on segments that align with your goals.

Example: A bar chart showing CTR by country for branded keywords offers a clear view of engagement across regions, highlighting areas where your brand presence may need improvement.

4. Practical Applications of Custom Dimensions and Metrics for SEO

Custom dimensions and metrics empower you to tailor your SEO analysis in ways that support your strategic goals:

• Analyze Keyword Intent: Segment keywords by user intent (informational, navigational, transactional) to better understand which type of content drives engagement.
• Focus on High-Impact Areas: Use custom dimensions like content type or region to identify high-performing sections of your site and areas for improvement.
• Track Specific SEO Goals: With custom metrics, such as conversion rates, you can assess how effectively SEO efforts translate into business outcomes, giving you more strategic insights.

Summary

By customizing SEO dimensions and metrics in BigQuery and visualizing them in Looker Studio, you gain control over how data is segmented and analyzed. This tailored approach enables you to focus on specific areas like branded keywords, user intent, or regional performance, leading to more targeted and impactful SEO strategies.