Google Organic Click-Through Rates in 2014

Posted by Philip_Petrescu

We’ve all been there. Trying to improve our organic rankings so we can get more traffic from the search engines. And every time we do that, we are left with some big questions in our minds:

  • How much traffic would I actually get if I rank on the first page?
  • Is it worth my time trying to rank above the fold?
  • How much more traffic will I get if I rank first in the organic results?

I’ve been there, too. I felt overwhelmed and frustrated every time I had finally reached a number one organic ranking in Google only to find out that the traffic coming from the search engine was not making the big difference I was expecting.

So I started searching for a way to find out how much organic traffic I could get for ranking on the top positions in Google.

But I faced a big challenge. These days, with “not provided” being almost 100%, it’s very hard to measure how many people reach your website searching for a certain keyword.

So I turned to the best source that I could get this data from, Google Webmaster Tools, which allowed me to see how many people click on my website when searching for the keywords I am interested in. This saved me a lot of time and allowed me to make better choices in the future with the keywords I was targeting.

Sounds like something you would be interested in?

Read on to find out more about how my initial findings turned out into a full fledged organic CTR study and how you can use this data to make better and more informed decisions in the future.


TL;DR:
 This will be a long post, so for those of you who are anxious to see the results of this study, scroll down to the CTR Study section below. Alternatively, you can download the complete study in PDF format or check out the free Google CTR History tool we have built to aid with this study.

Previous CTR studies

This is not the first study of its kind. There have been a number of studies in the past that have tried to find out the CTR for organic results. It all started when
AOL released more than 20 million search queries made by more than a half-million users in 2006.

A number of studies
followed after that, including those from Enquiro (now Mediative) in 2007 and later by Chitika and Optify in 2010. More recent studies have been performed by Slingshot in 2011 and then Chitika and Catalyst in 2013 respectively.

Here is a comparison of the Click Through Rate for each study:
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It’s important to emphasize the major differences in the methodologies applied for each study, as they are the main ingredients responsible for the dissimilarity of the results:

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It’s worth noting that the studies conducted by Mediative (former Enquiro) and Chitika, have been executed through unique methods that cannot be truly compared to any of the other studies. Mediative’s study relies on survey data and eye-tracking research, while Chitika’s studies are based on ad impressions served within their network.

Also relevant for a comparison is how CTR is defined for the other three studies previously conducted:

  • Optify defines CTR as “the percentage of users that clicked on each position, given that a user clicks on a top 20 organic ranking.” Their study makes the assumption that all searches result in a top 20 organic click.
  • In the Slingshot SEO study, CTR is calculated as “total visits (via Google Analytics) divided by total searches (via Google AdWords Keyword Tool) for a given keyword over a stable period.”
  • For the Catalyst study, CTR is defined as “the percentage of impressions that resulted in a click for a website (via Google Webmaster Tools).”

Our study retrieves the CTR data from 
Google Webmaster Tools so comparing it with the Catalyst study would be the most accurate.

So why a new study?

First of all, the Google search results have evolved significantly since these studies were performed. Besides having a fresh set of data, we also wanted to make this study unique.

  • Unique
    This study is unique because we have segmented the queries to be able to see how the CTR is affected by different types of searches. For example, we have segmented the keywords by category (industry), search intent, number of words (long tail) and whether the keywords are part of a branded search or not.

    Another important section of this study is trying to find out what impact some features that appear in the SERP (such as ads) have on the organic results CTR. 

  • Accurate
    To make sure that we get relevant and accurate results, this study is based on search data coming from Google Webmaster Tools for 465.000 keywords and 5.000 websites.
  • Transparent
    This study was intended to be as transparent as possible. Thus, we have included our step-by-step process below so you can see how we arrived at our results. 

    More than that, we also decided to give away the entire set of data so you can do your own research. To protect our clients, the actual keywords have been anonymized in the data set. 

  • Up to date
    As we have seen with previous studies, the organic CTR changes in time due to various factors. It can be affected by the holiday season, or by more features that are constantly being added in the SERPs.

    This is why we decided to transform the initial study into a free tool that anyone can use to segment the data and watch how the CTR changes in time.

Read on to see how different types of search results influence users’ behavior and what role the user intent has in determining the distribution of clicks.

Our methodology

Here’s how we obtained this data in case you want to do a similar analysis for your own websites:

  1. Download average search query data from GWT

    The initial data was obtained from Google Webmaster Tools (GWT) with the default filter: Web. This includes only traffic coming from non mobile devices. Our data set includes only keywords that have at least 50 impressions per month.

    We then changed this filter to Mobile and downloaded the table again to get CTR data for mobile devices.

    The Avg. position column from GWT displays an average of all ranking positions that this keyword has appeared in. This data was used to build the section of the charts.

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  2. Download exact search query data from GWT

    In GWT, when you click on a keyword in the Search Queries table, you will be sent to a report called Query Details. This report provides the CTR for each exact ranking position for that keyword.

    For example we can see here that every time this keyword was ranked first in the search results, the CTR was 56%. That’s because 2,947 people searched for it (Impressions) but only 1,644 people actually clicked on it (Clicks).
    xdgGKSBCzA2OiYtKWcVZ597s-1ucSXMg22dNMU_o 

  3. Exclude from exact data the queries with less than 500 impressions per month

    This was done to ensure that we get accurate CTR results. A filter was also applied to include only the keywords that had at least 10 impressions per month for each exact position they appeared in.

     

  4. Categorise queries based on brand, search intent and number of words

    We wanted to see how the CTR changes for searches that contain branded keywords. Most brands rank first for their brand keywords and it is believed that people tend to click on that first result.

    For this study we have defined brand searches as searches that contain the entire domain name of the website in the query.

    The same thing happens when people include a search intent in their query. It is believed that people act differently when they are interested to buy something as opposed to looking for information about something or when comparing different things.

    How can we figure this out? We look for certain words in the search queries, trying to guess what the intent was for that search.

    There are three types of search intents that were included in this study:

    Informational
    This includes searches that contain words like: what, when, where, how, who, restaurant, hotel, flight, definition, define, review, news, weather, time, phone.

    Commercial
    This includes searches that contain words like: buy, purchase, order, shop, coupon, cheap, cheapest, expensive, pricing.

    Location
    This includes searches that contain words like: near, nearby, from, directions, how long to, how far away from, how fast, train station, airport, ferry, route, highway, toll, plane tickets, flights, maps, driving directions.We have also tracked long tail queries (more than one word) separately to see how they affect the CTR.

      

  5. Find out if the SERP contains ads

    We matched the entire set of keywords from Google Webmaster Tools with the ones we track for each client in AWR Cloud. This way we were able to get more information about the features included in the SERP, such as the number of ads and their position and if any Universal features were included in the search results.

     

  6. Create graphs for easier data analysis

    We first used Excel to display this data in charts but in the end we ended up creating an in house tool because we realized that it would be interesting to see how the CTR changes over time.

Assumptions and limitations

The sample data set that was extracted from GWT belongs to our clients. Their businesses, although variate, may belong to certain industries that are different than the industry you are in. Therefore the results may not be the same for every business.

This study measures the CTR that was observed for a special time frame (within the month of July 2014). That means we cannot predict how the CTR changes for keywords that have higher volumes in different periods of the year.

In this study, we also made the assumption that the data collected from GWT with the above methodology is accurate.

The CTR study

This is the reference chart for the click-through rate (CTR) of organic desktop searches in Google for July, 2014.

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It is important to mention that these numbers reflect the CTR across all the searches included in this study. They do not account for the user intent, the features that appear in the SERP, or whether the keywords used in the search included a brand name. These will be addressed later in the study when we segment the data.

On average, 71.33% of searches result in a page one organic click. Page two and three get only 5.59% of the clicks. On the first page alone, the first 5 results account for 67.60% of all the clicks and the results from 6 to 10 account for only 3.73%.

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“These numbers serve as a useful reminder of the importance of organic rankings, and reconfirms the importance of the top few positions on Google. Although the first spot is still the most valuable for CTR, it seems to have become less so. I’d guess that part of the reason is that the increased use of ads, universal search results and Google’s own comparison and shopping results have reduced the prominence of top slot.”  
Graham Charlton - Econsultancy

In case you wonder where the other 23.08% of the clicks are, here are some possible scenarios:

  • Some people may find the ads displayed above the organic results more relevant.
  • Some people may not find what they are looking for in the first 10 results so they click on results from the second or third page instead.
  • Others may not find what they are looking for at all so they refine the search adding more words to the query to be more explicit.
  • With Google providing more and more instant answers people may very well find the answer to what they are looking for in the displayed search results so there is no need for them to click on any of the results.

Mobile

Mobile traffic is getting bigger and bigger day by day. Here we can see the CTR for searches coming from mobile devices compared with the searches from desktop devices.

Given the fact that you can see fewer ranking results above the fold on mobile, people have assumed that the CTR would be higher for the first results on mobile devices. Let’s see if that is the case:

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Not only is the CTR slightly lower on the first page, but the CTR for mobile searches actually rises on the 2nd and 3rd page, which is opposite to what we would expect and see from mobile searches.

“I would’ve expected mobile to drop off much, much faster than desktop. These rates seem to imply that the first positions on a mobile results page are less significant than we thought. Does that mean people are scrolling more?”  
Ian Lurie Portent

Branded vs. unbranded

One might assume that when users are making generic searches on Google, they end up making a brand selection from the results retrieved. They choose from the handful of options received, the source of information or provider to trust in for satisfying their need.

But what happens when 
branded searches are made? If the users are clearly looking for information related to a specific brand, will they follow the same behavioural pattern as for generic searches?

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For branded searches the first result is almost always associated with the brand’s website, which makes it the obvious choice for most users and very hard to miss. This would justify the big CTR difference between the first position and the rest of the SERP.

This big difference in CTR may also be affected by the fact that brand searches usually display a pack of 6 site links just below the first result, making it more prominent in the search results.

“People will seek click on a brand in the first position for a search on that brand way out of proportion to all other positions.”  
Danny SullivanSearch Engine Land

“The CTR data coming straight from Google suggests that we should be even more conservative when estimating potential search traffic. Most of our keyword research is going to revolve around non-branded terms. If you study the data, you’ll see a dramatic difference between CTR for the #1 position of branded vs. non-branded search. Our views of how many clicks you will get with an average position of 1 may be skewed because of this. But now with this segmentation data, I know I will be viewing traffic potential even more conservatively based upon CTR of only non-branded keywords.”  
Dan ShureEvolving SEO

Search intent

Most of us have some sort of intent when we search for something. We may need to find the location of a restaurant or a better price for that big TV we always wanted to get in the living room.

It is believed that people who search for keywords with high commercial intent (“buy 4k LCD TV”) are more likely to click on the first results than people who perform basic informational searches (“where is the nearest thai restaurant”).

Let’s see if search intent does indeed affect how people click on the results.

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This chart reveals that people tend to click more on the first results when their search has a specific intent. So we wanted to dig deeper and see which of the search intents affect the CTR and how.

“Google uses a lot of
context cues beyond the keyword so if I type ‘restaurant’ the intent isn’t there, until you realise it is midday and I’m on the street searching on my iPhone. This might explain the significant uptick in clicks on positions 1-3 for searches with intent.”  Tom AnthonyDistilled

The “Specific Intent” in the chart above is the set of all keywords found in the Informational, Commercial and Location sections and the “Other Intent” means all the other keywords.

The following chart compares these three search intents and how they affect the CTR:

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Google is getting better and better at figuring out search intent. Nowadays, many of the search results contain instant answers so people no longer need to click on a website to find out what they’re looking for. The answer is already there.

Commercial intent searches usually trigger ads that have colorful pictures of the products we search. It’s usually a lot more tempting to click on these pictures than on the first organic results.

“Search results for commercial intent keywords usually contain more features (eg: pricing, ratings, shopping results) which might dilute the CTR across the page.” 
Richard BaxterBuiltvisible

“It’s interesting that commercial intent searches have a lower organic CTR than informational searches. We’ve seen the opposite hold true for paid CTRs. This may be because commercial intent KWs are more likely to trigger ads, which lower the organic CTR.”  
Mark IrvineWordStream

Estimating organic traffic based on CTR

Remember the initial goal of this study? To find out how many organic visits one could receive for ranking in the top results on Google. We are now closer to reaching our goal.

By knowing the CTR for each position in the organic search, we can now calculate the organic traffic potential of a website. Depending on the ranking of a keyword and how many people click on that website, we can easily calculate how many people would reach that website from organic search.

Theoretically, by taking into account all these factors, one could easily estimate the amount of organic traffic. The formula is quite simple:


Traffic = Search Volume * CTR

But things get a little complicated when taking into account that each keyword is different.

As this study showed, searches for branded keywords have a higher CTR. Search intent also affects organic CTR significantly and long tail keyword searches show higher CTRs for first page listings.

Let’s see an example for an unbranded keyword with a volume of 1,000 searches per month where you rank first in the organic results with no ads above you:


1,000 x 24.8 / 100 = 248 (visits per month)

where 24.8 is the CTR for the 1st position for unbranded keywords.

Applying this formula for each keyword, enables you to estimate the amount of organic search traffic for any website.

Where can you get this study from?

This post contains only parts of the actual study. To find out how ads affect the CTR of organic results and more, download the
complete Google Organic CTR Study in PDF format.

You will also get access to the entire data set that we used for this study if you want to do your own research.

Future developments of the study

We will be constantly adding new features to this study, such as more ways to segment the data or insights on how different features that may appear in the SERP affect the CTR. These new additions will be featured first in the
free Google Organic CTR History tool, so make sure you check it out.

The first thing we want to tackle next is how the features that appear in the Universal results (such as news, videos, places, etc.) affect the CTR. We will then dig deeper to see how the CTR is affected by carousels, answer boxes and other knowledge graph features that appear in the SERP.

Your turn

Is there something in particular you would like to see in further updates of this study?

Post your comments below and let’s find out how we can improve this tool to benefit the entire community.

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October 1, 2014  Tags: , , , ,   Posted in: SEO / Traffic / Marketing

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