How to Chart Organic Search CTR Curve Using Google Webmaster Tools


A few months back the team published our goals for 2014. These goals included personal as well as company growth ideals that we as a group and individuals wanted to strive to achieve.

Among many of our goals for this year, one of them stood out to amongst the rest:

Live a day in your co-workers shoes

That being said, I decided to live a day in the shoes of our Search Engine Marketing (SEM) expert, Christian Bullock

My Mission: Chart CTR by Organic Search Position

Search engine marketers really care a lot about keyword rankings; better rankings tend to lead to more traffic, conversions and revenue.

Folks at Catalyst and Slingshot SEO have released CTR curves by organic search position, but these were always based upon their own analytics data. See an example below:

ctr curve organic search slingshot seo catalyst seo

But can you actually quantify the value of keyword improvements from position #5 to position #2 for your own brand?

Short answer: YES!

Using Google Webmaster Tools, you can calculate the traffic and monetary value of increasing the position on a specific keyword.

Step 0: Setting Up Methodology

This concept first came to me after reading an article on iPullRank titled Google Webmaster Tools Killed the CTR Study , which was inspired by a tweet from Moz's Cyrus Sheppard (see below):

With these two search marketing thought leaders showing the way, I decided to set up the following parameters for our CTR curve study example:

  1. What We Want to Achieve: I wanted to understand the amount of drop off from the first few organic search positions -- is it as drastic as Slingshot and Catalyst CTR research had originally suggested?
  2. Statistical Significance: Mike King's CTR research was based off a few hundred impressions and clicks. To build on his results, we wanted to look at hundred's of thousands of impressions and clicks to create a higher confidence in the results. Additionally, we only looked at search queries with 10+ impressions to weed out super long tail keywords.
  3. Vertical: I decided to white label one of our e-commerce client's data, as they have a relatively deep website and have been around for 20+ years
  4. Time Frame: We pulled this data for Q1 of this calendar year, 2014

So what are we waiting for? Let's get going!

Step 1: Pulling CTR data for organic search

To protect our client's data, we've shown all screenshots on MKG Media Group's Google Webmaster Tool profile.</p>

The first step of this process is to log in to Google Webmaster Tools and visit the 'Search Traffic' section of the user interface. Search traffic Google Webmaster Tools

As the drop down options expand, click on search queries.

search queries google webmaster tools

This will drop you onto a page titled 'Search Queries'. You can clearly see the keyword queries that are generating impressions, clicks and avg. position on Google's search engine.

You'll want to select the correct dates (upper right corner) and then click on 'Download this table' option.

Google Webmaster Tools Search Queries Download this data

Step 2: Chart CTR Curve Data In Excel

Now that you've pulled down the data, you'll need create a small table and perform a SUMIF function to pull down impressions and clicks by ad position.

Take a look at the SUMIF table we created below (first 10 positions only):

ctr by organic search position 1 - 10

Next up, make a simple line graph and you'll have CTR performance by organic search position for your brand!

See below for our e-commerce client's performance by search position:

CTR Chart by Search Position

At a high level, we can clearly see that positions #1 and #2 are the most valuable places for this e-commerce client to appear. Additionally, doing an in-depth analysis across long tail keywords would help us uncover the value of those keywords to our brand.

More importantly, this graph is telling us that we should target keywords ranked #3 or worse to try to capture a #2 or #1 ranking. The biggest and most attainable gains are those rank #3 keywords and turning them into a #2 or #1 ranking.

Step 3: Analyze CTR performance data

This simple chart should give analyst / measurement team everything they need to understand where your most profitable keyword positions live for both first page search engine results page (SERP) rankings as well as for long tail keywords.

In Conclusion: What I Learned By Playing Search Marketer for a Day

I learned a few things (in no particular order) by working a day in Christian's shoes:

  • Google Webmaster Tools (GWT) has a ton of valuable features and search marketers should take advantage of the capabilities it provides. Along with the CTR curve analysis, GWT also provides keyword data for impression, click and average position -- something that Google Analytics now pipes in as (not provided) traffic.
  • Looking at a CTR curve holistically is valuable, but breaking down CTR curve by branded versus non-branded keywords could help brands uncover potential big wins or insights based on how users are searching for their products on the web.
  • Give back to the search marketing community! This study was inspired by Mike King's CTR curve article, and he was originally inspired by Cyrus Sheppard's tweet. While Mike's data was (admittedly) inconclusive, we took it to the next level to apply a higher level of confidence in CTR curve data. So who will be next to build on our research and give back to the community?

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