{"id":25598,"date":"2026-09-05T02:46:14","date_gmt":"2026-09-04T23:46:14","guid":{"rendered":"https:\/\/alienroad.com\/google-bilgi-bankasi\/improving-seo-with-a-search-console-bubble-chart\/"},"modified":"2026-09-05T02:46:14","modified_gmt":"2026-09-04T23:46:14","slug":"improving-seo-with-a-search-console-bubble-chart","status":"publish","type":"ar_kb","link":"https:\/\/alienroad.com\/google-bilgi-bankasi\/improving-seo-with-a-search-console-bubble-chart\/","title":{"rendered":"Improving SEO with a Search Console bubble chart"},"content":{"rendered":"

\n Analyzing Search performance data is always a challenge, but even more so when you have plenty of
\n long-tail queries, which are harder to visualize and understand. A
\n bubble chart<\/a>
\n can help you understand which queries are performing well for your site, and which could be improved.\n<\/p>\n

\n If you’d like to test the techniques discussed here, you can
\n connect your data to Looker Studio<\/a> and play with the chart settings.\n<\/p>\n

\n<\/div>\n

\n If you haven’t read connecting Search Console to Looker Studio<\/a> and
\n monitoring Search traffic with Looker Studio<\/a>,
\n consider checking them out to understand more about what you can do with Search Console in Looker
\n Studio.\n<\/p>\n

Understanding the chart<\/h2>\n

\n A bubble chart is a great visualization when you have multiple metrics and dimensions because it
\n lets you to see relationships and patterns in your
\n data more effectively. In the example shown here, you can see
\n click-through rate<\/a>
\n (CTR), average position, and clicks for the query and device dimensions in one view.\n<\/p>\n

\"Elements<\/p>\n

\n This section goes into detail on some of the chart elements to clarify what the chart shows, and what it doesn’t.\n<\/p>\n

Data source<\/h3>\n

\n The bubble chart shown in this page uses the Site Impression table available through the
\n Search Console data source<\/a>,
\n which includes Search performance data<\/a>
\n aggregated by site and queries.\n<\/p>\n

Filters and data controls<\/h3>\n

\n There are five customization options in the chart to help you control your data effectively:\n<\/p>\n

    \n
  1. Data control<\/a><\/b>:
    \n Choose the Search Console property you’d like to analyze.<\/li>\n
  2. Date range<\/b>: Choose the date range you’d like to see in the report; by default you’ll see
    \n the last 28 days.<\/li>\n
  3. Query<\/b>: Include or exclude queries to focus on. You can filter your data<\/a>
    \n similar to how you do it in Search Console.<\/li>\n
  4. Country<\/b>: Include or exclude countries.<\/li>\n
  5. Device<\/b>: Include or exclude device categories.<\/li>\n<\/ol>\n

    Axes<\/h3>\n

    \n The axes in the chart are average position (y-axis) and site CTR (x-axis). There are three
    \n significant transformations in the axes:\n<\/p>\n

      \n
    1. Reverse y-axis direction<\/b>: Since the y-axis shows average position,
      \n inverting it means that 1 is at the top.
      \n For most charts, the best position is in the top right corner, so it is more intuitive to invert
      \n the y-axis when using it to display average position.<\/li>\n
    2. Log scale<\/b>: Using a logarithmic scale<\/a>
      \n for both axes lets you to have a better understanding of queries that are in the extremities of
      \n the chart (very low CTR, average position, or both).<\/li>\n
    3. Reference lines<\/a><\/b>:
      \n The reference line is very helpful to highlight values that are above or below a certain threshold.
      \n Looking at the average, median, or a certain percentile can call attention to deviations from the
      \n pattern.<\/li>\n<\/ol>\n

      Bubbles<\/h3>\n

      \n Each bubble in the chart represents a single query, with the following
      \n       style properties<\/a>:\n<\/p>\n