Google Organic Click Through Rate (CTR)

As many SEO’s will already be aware of Google added additional functionality to their webmaster tools console by extending the information on top search queries. http://googlewebmastercentral.blogspot.com/2010/05/top-search-queries-is-now-search.html.

This has been widely disputed about the accuracy of the data, but nevertheless it can be used to get some good information. My thoughts were about Organic Click through rate for Google. It now gives you some data based on search position so I thought I would really like to know what an average Organic Click through rate for Google was based on position, particularly for the first page as this can allow you to predict what traffic you might get to the site using CTR data and keyword volume data from keyword Search tools such as: https://adwords.google.co.uk/select/KeywordToolExternal.

A little Background
Firstly I wanted to get some information about Click through rate, who clicks on Organic adverts compared to paid listings and I found out some useful information. Below shows an image of how many SEO’s perceived the relationship between organic and ppc ads on Google.

References:

I then carried out some further digging and found a post on Search Views about the affect CTR had on Paid advertising when Google moved the ads further towards the left from being way over on the right of the screen. This gave a 14% increase in clicks on paid ads.

We can now assume that CTR distribution from Organic to Paid adverts is now around 65% Organic to 35% Paid.
(Assume makes an ass and out of you and me:) )

I carried out further research on organic Click through rate and I came across Aaron Wall’s blog on SEOBook, this showed information about an eye tracking study from 2004 and the details in 2006 when AOL leaked its search records and some SEO’s detailed the organic Click through rate.

Webmaster tools and Click Through rate
So I took all the information above on board and thought if Google webmaster tools now gives click through rate by position and at Just Search we have a large client base I thought I’d go through the long winded task of downloading this information across around 100 clients to see what it detailed.

In total I compiled a list of 2710 keywords ranked in positions 1-10 in Google and added the details to an excel sheet, showing:

  • Query
  • Impressions
  • Clicks
  • CTR
  • Avg. position

I then used a pivot table to be able to extract what the average click through rate on Google was based on search Position. This gives some quite useful data, it’s not 100% accurate and will only give an incite into organic CTR as the figures are from broad from a number of clients and the click through rate is based on Google’s export of average position.

The Data

The first thing you may notice is that the figures add up to more than 100%, this simply as this is an aggregate of averages for 2710 keywords, but it does show some corresponding data to the eye tracking study and AOL leaked data in terms of what positions people are more likely to click on.

Getting crafty

The above data was good to see but I also decided to look at if the click through rate changed based on Query length. I used the excel formula of:

=IF(LEN(TRIM(A2))=0,0,LEN(TRIM(A2))-LEN(SUBSTITUTE(A2,” “,””))+1)

I simply added a column to my table which looked at the keyword (Query) and counted how many words formed the query and then provided the result. Again I could add this to my pivot table and then display the CTR for No.1 position based on Query length.

Conclusion

After going through the data from all sources I came up with a conservative guess of an average click through rate for position 2-10 would be 4.85%.

If you then think that I stated before:

We can assume that CTR distribution from Organic to Paid adverts is now about 65% Organic 35% Paid.

We can do the following:

  • Find out the Search volume of a keyword via Adwords tool
  • Multiply this by 0.65 (65%) for Organic CTR
  • Multiply this by 0.485 (4.85%) for being ranked position 2-10

This will give you a prediction of how many visitors you can receive from ranking the first page under a given keyword.

What’s Next?

Look out for my next post about the seminar I did at Internet World this year, this takes the above data then looks at website conversion rate, average order values and how to put a business case for how much money a keyword could make for you and creating a Profit and loss and other financials for this.

I also talk about custom reporting using Google Analytic s and e-commerce tracking, you can actually see how much revenue a keyword makes you, and to put the final piece of the puzzle together comparing the above ways to predict with actual data, look out for my next post 🙂

77 thoughts on “Google Organic Click Through Rate (CTR)”

  1. Wait, wut?

    48.5% or 4.85%?

    So 65% of total search volume goes to organic.

    Being first get's an average of 50.15% of those? Being somewhere else on the front page gets 4.85% on average? Being page 2 or 3 (or more) gets you the remainder?

    So Keyword XYZ gets 10,000 visits a month.

    I'm ranked 1st I get 3269 visits?

    Being 2nd – 10th gets me 315 visits?

    Now that Google has added the left column into results will organic percentage go up again, do you think?

    Do you think the verticals take away some of the normal organic clicks too?

    • Hi StalkerB, fixed the submit URL section on the blog if you noticed 🙂 Regarding your questions what the data says is that if we take the information from the eye tracking study, AOL data and the GWT info I have put together we can assume (Taking the no. 1 position out) that as an average figure 4.85% is the CTR for being on the first page. The example in reality would be more like:

      10,000 Search Volume (impressions)

      No.1 Position Gets – 46.37% = 4,637 visits
      No.2 Position Gets – 29.43% = 2,943 visits
      No.3 etc…
      No.4 etc…

      If we make an estimate that being on the first page the average CTR is 4.85% then from 10,000 Search Volume (impressions) you would expect to get 485 visits.

      Hope that makes sense.

      • For anyone else who may have been struggling to understand this (as I was), the key here is that when you average positions 2 – 10 together the total DECREASES. That’s the nature of averaging numbers – the lower numbers pull the higher numbers down and the higher numbers pull the lower numbers up until you reach the middle. Of course if you were to rank at #2 then you would be above the average, same as if you ranked 3, 4, or 5 or till whatever position happens to be at or close to the median point.

        If we based this on just the averaged numbers that Neil obtained via the data he pulled from his cross section of 100 clients then that average works out to be 14.93%. As Neil pointed out the total here is greater than 100% (180.71% actually) because each of those percentages correlating to each position (2 – 10) are derived via the aggregation of the averages for each of the keywords (who knows how he actually worked through that mathematically, but I’ll take his word for it).

        Anyway, I hope that helps someone who was struggling to put the pieces together on this as I was.

  2. Great analysis there Neil. I would ne very interested to see how CTRs change across niches. Do tech people and stay at home moms have similar distributions ?

    Looking forward to the CRO bit!

    Paul

    • Hi John, i’m just going through the excel sheet 2710 lines identifying brand, product etc. I will update you with another post when this is done.

  3. Interesting thought’s presented here, however if i try to calculate / predict visitors with your formula, i have found that for some markets your prediction is too high. I did a quick check and found that for a local market like Austria the formula should read:

    * Find out the Search volume of a keyword via Adwords tool
    * Multiply this by 0.65 (65%) for Organic CTR
    * Multiply this by 0.485 (4.85%) for being ranked position 2-10
    * Multiply this by 0.10 to compensate for reality..

    with this formula and some selected keywords your predicition is very good, so i asume that the keyword tool from google is not giving us correct data all the time. would be nice to get some feedback from other users too..

    • Hi Jörg, I found that with the formula the prediction is generally over but quite close, I like you adaptation though, thanks for the feedback.

    • Hi Andy, Google’s moto is to get people of it’s search engine as quickly as possible, I think the brand new layout is to obviously try and help do this, I’d love to see data to see if the 3 column layout increases PPC CTR or not.

    • Hi Andy, Good spot, your right it should 0.0485 for (4.85%) I.e. 1000 impressions at a CTR of 0.0485 for (4.85%) would give 48.5 potential visitors.

  4. Neil,

    Nice post, but you may want to get into the data that comes back from the Google AdWords Keyword volume tool compared to the total impression volume presented in the WebMaster reports. When using the keyword tool, the way you look at the organic traffic was supposed to be done by setting the “Exact” match. But when you start looking at numbers from both sources, you’ll notice that the keyword volume from AdWords is very far off from the WebMaster reports. So if you’re trying to look at the paid impressions compared to organic, they won’t add up and your percentage paid/organic will be off.

  5. I followed you perfectly until the 4.85% CTR figure was introduced.

    How are you calculating that? Are you using weighting the 2004 eye tracking and 2006 AOL data heavily? It seems like the CTR shown via GWT is substantially higher in the pivot table graph.

    And would you have to adjust the GWT Organic CTR based on the 65% assumption since it's showing clicks versus impressions, which would include potential paid clicks.

    I'm impressed with the process but want to understand that last part of your analysis.

  6. great analysis neil!

    so it means for being No.1=Imp x 0.65 x 0.9515

    right?

    and you said

    shouldn’t it be 10,000 x 0.65 x 0.0485 = 315 visits?

    correct me if i am wrong

  7. Very helpful post. I saw a stat recently that said about 70% of searchers skipped the paid adverts but there was no cite. It can be a very powerful stat to use when approaching a certain segment of new business. Having some support data that I can link to is great!

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  9. Hi Neil

    This is great research and work and has answered a few questions but at the same time raised others for me (murphys law).

    The primary question i have is regarding the keywords. My gut feel (which i never trust) is that a brand key phrase with more relevant results would have a higher click through. How many of the key phrases are brand phrases? Also the more competitive the phrase the greater the “noise” how many of the phrases have a full compliment of PPC adverts.

    This is obviously the start but i am sure will facilitate discussion.

  10. A very good synthesis of available information combined with -real customer data-. The latter is what makes this so credible. The CTR vs Query Length also informative. Thanks. On to your next article….

  11. Great information. It really helps to calculate ROI. I was interested in the chart element: Grand Total = 20%. What does that refer to?

    Also, you mention that being on the first page was worth an average of 4.85% of total CTR. How did you get that number? It seems that the lowest position is around 7%

    Thanks again for the information.

  12. Hi Neil

    I very much appreciate the time and effort you have put into the collation of this data. Its now April 2011 and the same data is fed to me through various sources. A credit to you for your efforts.

    I too am an SEO Internet Marketing specialist and no consideration has gone into the dynamics of the visual look of the returned search. For example does a listing fully populated with characters have more or less appeal to the eye? What causes the eye to stretch across the page and settle on something appealing.

    Figures for position 1 ,2 and possibly 3 can demonstrate one piece of reasoning but it fails to take into account that the eye responds to the site of the order on the page. It gets drawn to the irregular, distracting the order of the mind. I think we now need to take advantage of the display text to capture the eye’s weak tendency too.

    A thoroughly good read, I was brought to you from Mark R in Warrior Forum

    We are in interesting times for Web Traffic Generation.

    Thank you once again

    Tim

  13. Hey Neil

    Thanks for putting a considerable amount of time into this post! It was fascinating to read.

    I am often discussing the number of clicks throughs a website will receive for their position on page 1 with clients starting new businesses or beginning an SEO strategy.

    Cheers

    Mark

  14. Great analysis. The one thing I think not being considered are the additional results that often compete for clicks on the page i.e. news results, local results, shopping results. In my tests I have found that an assumption of 60% of the clicks going to organic results (one through ten) is more accurate.

  15. These figures seem to tally with my experience. At position 2 in google I was getting a CTR of 9.5%. After much boring SEO I finally got to postion 1 and didn’t think the diffrence would be that different. I was staggered to see the CTR go up to 47%. Which made all the hard work finally pay off.

    If you’re in the same position as I was, just struggling to make that final move to the top ( always the hardest !), just persevere, it will be worth it.

  16. quite interesting though, does anyone know an estimate or average of the top 3 rankings using adwords or ppc?

    ive tried to find some info – but i am assuming that well that if it may be true that the paid ads receive between .25 – .30 average CTR

    this would be helpful in order to estimate a simple cost – relation of being indexed @ 1 SERP

    even better with the average you commented about the 4% decrease per ranking number, would give you a more or less idea on how much you are saving either for yourself or a client, @ least to some degree of course between minimums and maximums

    …….

    by the way cool post ! Neil

  17. Wow, that’s some useful information for CTR.
    Something I find interesting is the large number of impressions a keyword can get without influencing the CTR – in my experience CTR increases the higher the ranking – I guess that’s obvious really but, it does backup the graph shown from Aaron Wall’s blog post.

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