PPCPPC Click-Through Rate by Position: Does Rank Matter? [Data]

PPC Click-Through Rate by Position: Does Rank Matter? [Data]

What is the "right" position is for a given keyword? A data set of more than 12,000 data points was analyzed to find out what the click-through rate (CTR) would be at various average positions. Here are three insights from the data.

I find myself in discussions about the rank of given keywords far more frequently than I think I should. The general conversation is based around what the “right” position is for a given keyword.

There are so many sub-level discussions to this debate because the real “right” answer is based on that individual interaction. The value of that specific customer to the business.

However, those discussions often happen at the position level. So we discuss it at length, especially since it is so tied to budget and cost. I understand the debate.

Click-Through Rate by Position

To better understand this discussion, I pulled some data across our client set over the last 30 days and put it into a scatter plot in Excel. I used click-through rate (CTR) as the y-axis and Average Position as the x-axis.

I removed any keywords with less than 25 clicks to try to remove some of the noise in the data. Then I pulled out my algebra skills and had Excel show the equation of the line.

The line’s equation allows you to input values for either X or Y to solve for the other. In this case I wanted to find out what the CTR would be at various average positions. So I input the data that is below in the table:

Click-Through Rate by Position

CTR by Position Data

This type of analysis is awesome for understand the relationship between any two points of data. I use this approach for the relationship between daily ad spend and daily conversions, CPC and position, conversion rate by position, etc. Any two values can be compared in this way.

This data set was made up of more than 12,000 data points, allowing for a better range. Certainly this data will differ by client, vertical, seasonality, time of day, and many other factors. However, it’s a solid directional guide:

3 Insights About Rank & CTR

Here are three insights you can gather from this data:

  • The drop off between the top three positions in terms of CTR is significant. The difference between Position 1 and even Position 1.5 is ~3X. That can be a huge factor in the amount of traffic that comes to your site, but also a big step potentially in cost to hold down that number one spot.
  • After Position 3 there is very little traffic to be acquired. This is something that I think is slightly overstated in the data. There is still plenty of traffic that is acquired at these positions and lower, but you have to be cautious and understand the impact as you get further to the right rail.
  • You’ve got to test it out for yourself, across device, across category. This is really a guide, a way to think about how to use your data to show insights to your clients or for your own brand. The amount of data that is created in any given digital media campaign can be overwhelming, but there is a treasure trove of data that is available. You just have to know where and how to look.


Hopefully you found this data interesting, not only a way to understand the relationship between CTR and position, but also as a framework for understanding your specific data.

The data is there to optimize and maintain a winning program. Happy treasure hunting!


Semrush Keyword Difficulty

whitepaper | Analytics Semrush Keyword Difficulty

Searchmetrics Core Web Vitals Study

whitepaper | Analytics Searchmetrics Core Web Vitals Study

The Ultimate Guide to Forum Link Building in 2020

whitepaper | Analytics The Ultimate Guide to Forum Link Building in 2020

Top 5 SEO Mistakes

whitepaper | Analytics Top 5 SEO Mistakes