Columbus, Ohio SEO Expert | Jacob Stoops

Click Distribution & Percentages by SERP Rank

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Ever wonder what an organic click might really be worth? For that matter, ever wonder what is the number of clicks you might gain by moving from position #5 to position #1 in the search results?

What if I told you that there was information out there that might be able to help you predict just how many organic clicks you may stand to gain by moving up in search engine rankings? Well, it’s your lucky day.

The Click Distribution Data

There are 3 data sets & studies currently in existence to help us understand traffic distribution by SERP position:

  • AOL’s 2006 Data Leak – In 2006, AOL accidentally leaked over 30 million search queries from over 600,000 AOL search users. This has been discussed many times since then. See Richard Hearne and Bob Hodgson.
  • Cornell University Eye-Tracking Study – In 2004, Laura A. Granka, Thorsten Joachims and Geri Cay conducted a user-behavoir study focused around search behavoir specifically on Google. They used an eye-tracking study of a sample of undergraduate students to determine clicks and attention distribution.
  • Study – New software recently developed by BrandSoftech allowed them to track and create statistics based on over 63 gambling sites, which received 5,357,519 clicks from 29,327 different key phrases typed into Google. The ingenious software looked up a site’s position for a key phrase the moment it received a click from Google.
The 2006 AOL Leaked Data:

2006 AOL Leaked Click Distribution Data

The Cornell University Eye-Tracking Study Data:

Cornell University Eye-Tracking Study Data

The Click Distribution Study Data: Click Distribution Study Data

By looking at each individual study, you can easily see that there is a great disparity in terms of the number of clicks the #1 result receives versus #6 or #10. This is to be expected. AOL’s data also showed that 89% of people clicked somewhere on page one, while Cornell’s users click page one results 98%, and BrandSoftech’s users click page one results 99% of the time.

By my reasoning, I believe that none of the 3 data sets referenced above is 100% accurate. In fact, each data set has it’s share of flaws. However, I believe that the real click distribution percentage for clean SERP pages (you’ll see muddy SERP pages referenced below) likely falls somewhere in between all three studies.

So, I took the liberty of average all 3 percentages together to come up with a new mark:

  • Position #1: 45.46% of all clicks
  • Position #2: 15.69% of all clicks
  • Position #3: 10.09% of all clicks
  • Position #4: 5.49% of all clicks
  • Position #5: 5.00% of all clicks
  • Position #6: 3.94% of all clicks
  • Position #7: 2.51% of all clicks
  • Position #8: 2.94% of all clicks
  • Position #9: 1.97% of all clicks
  • Position #10: 2.71% of all clicks
  • Total: 95.91% of all clicks occur on Page #1 of SERPs

Please keep in mind, that this is NOT an exact science. This is only a way of attempting to estimate the percentage of click volume you may receive based upon SERP position.

What You Can Do With Click Distribution Data

The idea here is that you can utilize both your rankings data and keyword search volume data to determine:

  • How many clicks you might receive my achieving Top 10 positioning for a particular keyword.
  • How many clicks you can expect to gain/lose by moving position in the SERPs.

An Example

Okay, let’s show an example. For keyword research, I recommend using the Google Adwords Keyword Tool. I sometimes question the accuracy of this tool, but it’s free and easy to use – and also allows you to export data via excel. This data can show you monthly search volume trends on a keyword level.

Google Adwords Traffic Estimate

So in our example, I chose the word “shopping.” According to the tool, the keyword “shopping” had:

  • 24,900,000 Global Monthly Searches
  • 5,000,000 Local Monthly Searches (i.e. In Your Country (United States is mine))

Lets go ahead an just knock off about 20% right now due to the click volume that will probably go to Pay-Per-Click ads. That leaves us with approximately:

  • 19,920,000 Global Monthly Searches
  • 4,000,000 Local Monthly Searches (i.e. In Your Country (United States is mine))

Based on the click distribution percentages above, you might expect approximately the number of clicks displayed below if you rank in the Top 10 SERPs for the keyword “shopping”:

Applied to Global Search Volume

  • Position #1: 9,075,552 clicks (45.46% of all clicks)
  • Position #2: 3,126,112 clicks (15.69% of all clicks)
  • Position #3: 2,009,264 clicks (10.09% of all clicks)
  • Position #4: 1,094,272 clicks (5.49% of all clicks)
  • Position #5: 996,000 clicks (5.00% of all clicks)
  • Position #6: 785,512 clicks (3.94% of all clicks)
  • Position #7: 500,656 clicks (2.51% of all clicks)
  • Position #8: 584,984 clicks (2.94% of all clicks)
  • Position #9: 392,424 clicks (1.97% of all clicks)
  • Position #10: 539,832 clicks (2.71% of all clicks)

Applied to Local Search Volume

  • Position #1: 1,822,400 clicks (45.46% of all clicks)
  • Position #2: 627,733 clicks (15.69% of all clicks)
  • Position #3: 403,467 clicks (10.09% of all clicks)
  • Position #4: 219,733 clicks (5.49% of all clicks)
  • Position #5: 200,000 clicks (5.00% of all clicks)
  • Position #6: 157,733 clicks (3.94% of all clicks)
  • Position #7: 100,533 clicks (2.51% of all clicks)
  • Position #8: 117,467 clicks (2.94% of all clicks)
  • Position #9: 78,000 clicks (1.97% of all clicks)
  • Position #10: 108,400 clicks (2.71% of all clicks)

Personally, I recommend using the Local Search Volume as your primary area of focus unless you’re a very well-known worldwide brand. So if we go by the above logic using the Local Search Volume numbers, you can expect that if your site moves from the #5 organic position (which receives 200,000 clicks monthly) to the #2 organic position, you should get a monthly increase in organic traffic of around 427,733 clicks.

What Is a Click Worth To You

Lets use the above example, and really roll with it into conversions. Let’s say your website’s conversation rate is 2%, and you’re currently ranking #5 for shopping which we think pulls 200,000 local clicks monthly. Each conversion for your company is worth $200.

At the #5 ranking, your site should be generating 4000 conversions per month which equates into $800,000 monthly.

A move from #5 to #2 increases your organic traffic, which increases your number of conversions (if your conversion rate holds) from 4000 to 12,555 conversions. At $200 per conversion, this new revenue number becomes $2,511,00 – a difference of $1,711,00!

Please, before you get excited I want you to keep in mind, all of this is approximate. This logic does not occur in a vacuum, and will most likely happen on a MUCH MUCH smaller scale for most examples. But in the end, this should serve as a good starting point from which to begin to understand how apply the data points that we are aware of to understand how shifts in your organic ranking may affect your organic traffic.

The Flaw in the Logic

As I said above, there are several flaws in the logic I stated above.

Different Types of Searches

Different types of search classifications is discussed in detail by Aaron Wall over at SEOBook. These types are Navigational, Transactional, and Informational.

  • In general, for navigational searches people click the top result more often than they would on an informational search.
  • In general, for informational searches people tend to click throughout the full set of search results at a more even distribution than they would for navigational or transactional searches.
  • The only solid recently-shared publicly data on those breakdowns is from Dogpile [PDF], a meta search engine. But given how polluted meta search services tend to be (with ads mixed in their search results) those numbers were quite a bit off from what one might expect. And once more, they are aggregate numbers.

Different search contexts certainly impact the patterns in which people click around the SERPs, which in turn may affect the click distribution percentages.

Muddy SERPs

The concepts discussed above occur in the vacuum of a clean search results page. However, we know different. SERPs are muddied with local listings, inject with news feeds, social media, pictures, media, etc, not to mention the 10-20% slice the pay-per-click ads take right off the top.

You can see how different types of listings are injected into the natural SERPs

This means that there aren’t always 10 static listings in the SERP, which in turn means that each listings click distribution gets watered down. In addition, you must consider the effect of personalized search results which may display different listings for different users – making the click distribution percentages even less reliable.

In the example above, there were actually more than 15 listings of one type or another on the search result page.

What To Do?

Probably the best bet is to take whatever numbers you come up with utilizing the math above and knock about 20-30% off of them due to the invariable flaws and differences in search results pages, search types, and the volume of clicks taken by PPC.

Also, set your expectation as such so that you’re not recreating these experiments in a vacuum and then coming to me later if they’re not exactly right. Remember, this isn’t an exact science, simply something that is meant to guide you along the path of understanding how search rankings impact traffic and potentially revenue.

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Click Distribution & Percentages by SERP Rank, 4.8 out of 5 based on 6 ratings

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Jacob Stoops

About the Author

is an SEO professional living in Columbus, Ohio and working for Rosetta Marketing. He's been working in the SEO industry since 2006, and has been blogging since 2009. Learn more about , a Columbus, Ohio SEO Expert.

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  • lingoway

    The #1 ranking in SERPs matters the most. The click difference between #1 and #2 ranking is drastic. That why people want to get #1 ranking In SERPs.

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  • Amelia

    This is great info… The number of times my customers have asked for this information and I’ve been unable to give even an approximation of an accurate response… This goes some way to achieving this.

    I also look at the Click Trough Data in Webmaster Tools and conversions analytics, but for new client pitches this information isn’t always available.

    I err on the side of caution and always give conservative estimations so that my customers expectations aren’t over optimistic about the results that are possible. One of the biggest problems I have encountered is client trust in the ‘product’ of SEO – many of my clients had been ‘burnt’ in the past by unscrupulous companies promising them more than can be delivered.

    Something else worth considering is that some keywords offer better conversion rates than others. Brand names tend to be higher, niche keywords that are exact matches to the product or service offered are also quite high, but with high-search-volume slightly ambiguous keywords, the conversion rate will be relatively low. I tend to work out which keywords will offer the best conversion for my clients and concentrate my efforts there, rather than chasing the vanity keywords straight away. Again, the figures for this are largely guesstimations, but the in terms of relative numbers of conversions when compared against one another – it’s usually fairly accurate. It gives me a focus and target (I love targets – sad but true!) and the customer also gets an understanding of what can realistically be achieved by the keywords chosen.

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    • Jacob Stoops

      I agree. It’s best to be very conservative when giving any click estimates. There are many other things that go into it, including muddy search results, personalized search, and the many different types of searches.

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  • kevin

    wow… nice. thanks for the analysis

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  • David Thatcher

    Thank-you Jacob, I really enjoyed the article and your observations and deductions.

    I am finding that Google is changing so fast with on-page (and mid-page) SERP “innovations” that the new googly gadget things i.e. persons location, news, places, images, that they are blurring the clarity of the datasets and percentages that you have mentioned (as you have rightly pointed out).

    But that doesn’t really matter as the percentages mentioned (and the calclulated % average, thank-you, saved me the time!) are reasonably clear for the time and the place and the methods on which they are based.

    “Click distribution percentages” or “clickthrough rates v SERP ranks” are obviously very important and finding them somewhat surprisingly skewed towards really only the very top ranks … makes the job of SEO and keeping the SEO customer satisfied much more difficult wouldn’t you say? If there was a more gradual distribution we would have an easier job I feel.

    After 12 years doing web design and SEO I have made my decision to move more into SEM than SEO next year, I am beginning to believe that SEO is not really the best dollar value spend for the customer (re: dollars spent on my time), especially with 3 BIG PINK sponsored links at the top of the average SERP that are grabbing much more traffic than they used to I am guessing.

    Google will be happy though as I making the perfect move as far as they are concerned, reselling their paid product rather than trying to improve customer’s unpaid SERP listings.
    I wonder if there has been some Google-thought towards making SEO’s like me do exactly what I am doing by making SEO gradually worth less? (than SEM?)

    I hope not as I am a big fan of Google and the free tools they provide that I use daily such as; Analytics, webmaster tools and the keyword tool (for volume).

    I did see that with the recent revamp of the Google Places listings (or the map or pushpin listings) that the actual map (now in the right hand side column above the sponsored links) moves down as you scroll down, and that the actual map then obscures the paid listings. This would seem to be an SEO friendly thing to do (or SEM unfriendly) except when you consider that according to the data you have presented it is no great loss to Google because most people are not scrollling down before they make their decision to clickthrough onto a high ranked SERP listing.(statistically the #1 ranked sponsored link in all probability) but that is still a guess I admit.

    Thanks again JS, good luck to all people engaged in SEO!

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    • Jacob Stoops

      I agree, this can make many SEO customers unhappy – especially that for many of them it doesn’t happen on such a grand scale as the ‘shopping’ example I’ve used above. For many, it can be more of a slow trickle over time.

      I still think that from an agency perspective, it makes more sense to sign SEO contracts as PPC contracts can leave razor-thin margins for those who manage.

      From a client side, it really comes down to expectations. If they want quick results, then PPC is the way to go. They have to remember that this is only as good as their budget. When the budget goes away, so do the clicks. If they are patient, then SEO typically provides more gradual results over time – but these results are less likely to dry up as instantly as with PPC.

      In my opinion, it’s all relative and really more of a case-by-case type of thing.

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  • S. moraghan

    Wow, explains a lot about on how things works with Search Engine Results Pages & SEO rankings. I was familiar with the basics, but as of today I stand corrected. I am a newbie writer and author, who has just started out on the Internet in the hope to make money online in affiliate marketing. A couple of weeks ago, I had just finished writing 10 content articles concerning marriage breakups, Infidelity and Divorce for my website and submitted them to different article Directories and to my surprise, they ranked all 10 articles on the front page of google in their respective Title categories. WOW – I almost fell off my chair, Not sure what I did there, got to be a fluke or beginners luck. Anyway thanks for the insight and the post.

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    • Anonymous

      No problem. Thank you so much for taking the time to read it!

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  • Anonymous

    I recommend changing from broad match to exact match in the Google Adwords Tool for better estimations. Phrase match is good for taking into account the long tail; but broad match is hugely over estimated.n

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  • dancristo

    Thanks for the post. You probably mentioned it in the post somewhere, but I missed the date of the Brandsoftech report. nnThe fact that the AOL leaked data was from 2006 and Cornell study from 2004 raises some flags. Google’s interface has changed A LOT since then. You’re using a screen shot with Google’s 2010 interface, not AOL’s 2006 interface. And you’re also using a shopping query, not a gambling query like the Brandsoftech report. nnI know you’re using what’s available, but I’m not sure how accurate this data is these days.

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    • Anonymous

      You’re absolutely right, it could be incredibly inaccurate. I think that the search results have become incredibly muddy since then which is why I recommended just knocking 20% at least right off the top of whatever #’s you come up with. I used the “shopping” query for my example. It came from the Google Traffic Estimator. The BrandSoftTech study came from 2010.

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  • marketappeal

    Presumably at least 10-20% of people click on the PPC ads to the top and right of the listings, with a few also going for other links such as “Sign in”. As a result, I’d expect the first page organic CTRs to only add up to 95% frequently cited.

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    • Anonymous

      Agreed. I’ve tweaked my article a bit to reflect this point. PPC will take 10-20% of your clicks right off the top – not to mention the effects of Muddy SERPs. It’s safe to estimate 20-30% less overall clicks than what the raw click distribution formulas show as a final #.

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  • DJ

    I’d be interested in finding newer data regarding this study to see if people are getting lazier (ie clicking nearer the top result) or scrolling more.

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    • Anonymous

      Me too. I think the changes Google is making to the page (which I like to call “muddy SERPs”) are probably driving those percentages down and spreading them a bit thin – although I still believe most people still stay on the first page.

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