Optimizing website performance using a Search Console bubble chart

April 6, 2022

Wednesday, April 06, 2022

In this post, we'll provide tips to help you uncover opportunities to optimize your site's Google Search performance. If you haven't read our recent posts on connecting Search Console to Data Studio and monitoring Search traffic with Data Studio, consider checking them out to understand more about what you can do with Search Console in Data Studio.

Today we'll discuss a bubble chart that can help you understand which queries are performing well for your site, and which could be improved. We'll first explain the main elements in the chart, describing specific settings and how they influence the data. Then we'll provide some pointers on what to look for when analyzing the data.

The good news is that you don't need to build the chart from scratch - you can use this template and connect it to your data.

A bubble chart is a great way to visualize multiple metrics and dimensions at the same time, as it enables you to see relationships and patterns in your data more effectively. In the example shown here, you can see traffic attributes (click-through rate (CTR), average position) and volume (total clicks) for different dimensions (query, device) all at once.

This chart uses the "Site Impression" table from the Search Console data source, which includes aggregated search performance data by site and query. There are five customization options:

  1. Data control: Choose the Search Console property you'd like to analyze.
  2. Date range: Choose the date range you'd like to see in the report; by default you'll see the last 28 days.
  3. Query: Include or exclude queries to focus on. You can use regular expressions similar to the way you use them in Search Console.
  4. Country: Include or exclude countries.

The text discusses three ways to make a chart more insightful. These methods are reversing the y-axis direction, using a logarithmic scale, and adding reference lines.

Reversing the y-axis direction means that 1 is at the top. This is helpful for business charts because the best position is usually in the top right corner.

Using a logarithmic scale enables you to have a better understanding of queries that are in the extremities of the chart. This scale is "a way of displaying numerical data over a very wide range of values in a compact way."

Adding reference lines is helpful to highlight values that are above or below a certain threshold. This can help call attention to deviations from the pattern.

The following text discusses the use of bubbles in data visualization to help surface query optimization opportunities. The bubbles represent individual queries, with size representing the number of clicks and color representing device category.

Using the number of clicks as the bubble size helps you see in a glance which queries are driving the bulk of the traffic — the larger the bubble, the more traffic the query generates. Similarly, using the device category as the bubble color helps you understand performance differences between mobile and desktop searches. You can use any dimension as the color, but as the number of values increases, it becomes more difficult to recognize patterns.

This visualization can be helpful in identifying areas for further optimization. For example, if there is a large difference between average position and CTR, this may indicate that there is room for improvement in terms of ranking or relevance. Likewise, if there are many small bubbles with high CTRs, this could suggest that there is potential for increased traffic by expanding these keywords.

The red reference lines in the chart below show the average for each of the axes, which split the chart into quadrants, showing four types of query performance. Your quadrants are likely to look different than the one shared in this post; they'll depend on how your site queries are distributed.

chart showing four types of query performance

In general, the chart will show four groups you can analyze to help you decide where to invest your time when optimizing your query performance.

  1. Top position, high CTR: There's not much you need to do for those; you're doing a great job already.
  2. Low position, high CTR: Those queries seem relevant to users; they get a high CTR even when ranking lower than the average query on your website. They could represent a significant contribution if their position goes up — invest in optimizing them!
  3. Low position, low CTR: When looking at queries with low CTR (this and the next bullet), it's especially interesting to look at the bubble sizes to understand which queries have a low CTR but are still driving significant traffic. While the queries in this quadrant might seem unworthy of your effort, they can be divided into two main groups:

The following text discusses how to prioritize queries for SEO purposes. It divides queries into two categories - related and unrelated - and offers advice on how to deal with each.

Related queries are those that are already appearing in search results. These should be given priority over queries that are not appearing at all, as they will be easier to optimize.

Unrelated queries are those that are not currently appearing in search results. If these queries are important to you, it may be a good opportunity to fine-tune your content to focus on them.

The text also offers advice on what to do if you find yourself in the top position for a low-CTR query. This may be due to competitors having structured data markup, or because you are ranking for a query that users are not interested in relation to your site. In either case, consider enabling search result features for your site.

If you want to rank higher in search results, it's important to optimize your website performance. The SEO starter guide can help with tips like making sure your title elements, description meta tags, and alt attributes are descriptive and accurate. You can also use heading elements to create a hierarchical structure for your content, making it easier to navigate. Adding structured data markup can help describe your content to search engines so it's eligible to be displayed in useful ways in search results. And finally, thinking about the words that a user might search for to find your content can help you rank higher. The Keyword Planner provided by Google Ads can help discover new keyword variations and approximate search volume. You can also use Google Trends to find ideas from rising topics and queries related to your website.

The Google Search Central team has announced a new series of blog posts on the Google Search Console and Data Studio. The first post in the series covers feedback from the search community.

The team asks that any questions be posted in the Google Search Central Community or the Data Studio Community. They also remind everyone to follow them on Twitter for announcements of future posts in the series.

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