Click-through rate (CTR) from search results to your site is one of the most critical metrics for understanding your website's performance.
However, a troubling trend in recent years is the decline in clicks from search results, even when search volumes remain constant. This often suggests that features within search results are diverting clicks away from your site.
Why CTR Matters
CTR reflects how effectively your search result engages users, but external factors like SERP features (e.g., answer boxes, carousels, and ads) may be reducing your share of clicks.
AWR offers a fantastic dataset on CTR trends (check it out here), but to gain the most actionable insights, you need a custom CTR curve tailored to your site.
Creating this custom curve is straightforward, and to save you time, I’ve prepared a Looker Studio template and a Google Sheet that handle the heavy lifting.
Step-by-Step Guide to Create Your Custom CTR Curve
Here’s how you can set it up:
1) Connect to Looker Studio - In Looker Studio, link the Google Search Console property for your website.
2) Select a Date Range - Choose a time period for your analysis—typically one month or less if you have substantial data.
3) Export Your Data - From the table in Looker Studio, click the three dots in the top-right corner and export the data as a CSV.
4) Prepare the Google Sheet - Copy and paste the data from the CSV into my pre-built Google Sheet. Remember to make a copy of the sheet before you begin.
5) Set Up the REGEX Field - On the "Instructions" tab, input your brand name or related terms in the REGEX field. This step filters data into brand and non-brand queries.
If you don't change the brand REGEX (above), you will notice the second and third pivot tables are not accurate.
What You'll Get
After following these steps, the pivot tables in the sheet will update automatically.
You’ll see:
CTR at different ranking positions
Query and search term counts (helpful for understanding the reliability of each CTR value)
Split tables for brand and non-brand terms
a completed custom CTR visualised for my own blog:
Tips for Better Insights
Validate Query Counts: If a CTR value is calculated from fewer than 100 queries, it might be less reliable.
Filter Noise: If CTRs seem off, filter out terms with fewer than 100 impressions or 10 clicks.
Brand Strength Matters: For strong brands (70%+ branded searches), the brand/non-brand split is essential for accurate insights.
Why This Matters
This approach is quick, free, and accessible for anyone, providing a clear understanding of how your CTR changes over time. While advanced methods can yield more precision, this method offers a practical starting point for better understanding your site’s evolving relationship with search results.
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