For those who are familiar with my last post on Organic CTR will know that the post had some great pick up and is some real nice data.
After getting a number of requests on twitter (@theukseo) people have asked for more analysis from the data, so that’s what I have done.
Background
In my original study on Organic CTR I took a total of 2849 keywords which were analyzed the from the data I exported from webmaster tools.
I then created a table in Excel featuring:
- Query
- Impressions
- Clicks
- CTR
- Avg. Position
- Query Length
- Whole Number position
- Count
The results as per my last post were:
I then decided to go through the 2849 keywords and label them with a “keyword type” i.e.
- Brand
- Specific Product
- General
- Location
Brand
I labeled keywords as “brand” if they were Company names, company name derivatives, brand related searches.
Specific Product
These keywords were labeled as I consider them to be specific product searches, some keywords were very niche and other more generic but they would all be what I consider to be keywords at the end of a search journey.
General
This does account for a large percentage of the keywords analyzed as simply if I wasn’t connived that a keyword was niche, brand or localized then I have identified it as a “General” query.
location
I have labeled all localized keywords as “location”, this includes product and service searches by location.
The Initial Data
It was a very time consuming job to go through 2849 keywords so I hope this post is worth it, but below shows the overview of data assigned to each keyword type.
As you can see the greatest data is assigned to general keywords, however we do have at least 250 keywords analyzed in the other segments which can still give a reasonable picture.
So what Does the data show?
Below shows the overall graph of CTR based on keyword type. We can see that they all follow a similar pattern. However i will expand on the data in more detail.
The pivot table
Segmented Analysis of Organic SEO CTR
The next part of the post takes a look at each individual keyword type, firstly lets look at:
Brand:
The first things to notice is that the CTR rate in top position is much higher than the general CTR I displayed across all keywords i.e.
This would indicate to me that people are generally finding the brand related website in the top 2 results, however on branded product searches they are still likely to click onto the other results.
Specific Product Searches
You can see from the table below that the data does shows a slightly higher CTR on Position 1 for specific product searches, but in general the data is very similar to the overall average CTR’s based on position.
It is important to note that a Specific product search doesn’t have to be a longer query string. In my last post I detailed CTR based on Query length, although a specific product search would be suggested as a longer query this is often not the case.
Location based searches
This segment I think was the most interesting as it shows a higher CTR on all positions.
Remember this is simply the out put from webmaster tools and so I’m not saying this is 100% accurate but I think it does give a good idea of CTR by keyword types. Bearing mind that Google will often display a map insert on location based searches:
My conclusion on the location based keywords is that users are more likely to click on a lot more results when looking for something which is location specific.
General
Finally the biggest segment of data was for general keyword searches. By segmenting this data away from the average we can see that Click through rate is generally lower across the board, but the data is very similar to the general average.
Conclusion
The overall conclusion of this post is it show that Organic CTR does change based on keyword search type, however in general they do all follow a similar pattern. I think as an SEO I will particular take focus on location based searches and focus on Google local business centre to increase the retail space on the first page by displaying result in Organic, Local business and Paid listings, therefore maximizing the potential Click through rate to a website from a search query.
Hi Neil, nice post, your last CTR post also inspired me to look at a similar approach, using brand, intent and research style keyphrases, and got similar results to where we overlap i.e. brand search CTR.
I’d be interested if your own data give similar results if you segment your general search phrases in a similar manner, I sadly didn’t have much location specific data to work with.
Hi Mark, I’ll go through the data, may take me a bit of time, but I’ll give you an update when I’m done looking at Brand, Intent and research style keywords, cheers Neil
Interesting results. We over at SEO Effect tools use the SEO KPI ‘traffic share’ to monitor keywords. We only segment ‘traffic share’ by brand (brand and productnames) and non brand keywords. To be conservative we use a 50% max CTR’s for nr 1 position for branded and a 20% CTR’s for non-branded keywords. You find a full explanation of ‘traffic share’ in this blog post. Interesting to consider segmenting by places too, although the CTR’s do not differ that much to predict other maximum SEO visitors. Do you have segmented data of CTR for listings with or without Adwords/text advertisements? This will also influence the organic CTR’s.