The author’s views below are entirely his or her own and may not reflect the views of Moz.
Bluerank specialists have been analyzing web search to provide the best service to our clients. Web search is based on users, and to achieve the best results we have to understand users’ actions.
I was interested in click through rates in Google search engine result pages. It is obvious that the position in search engine result pages is vital. However, it is just as important that there are three main types of keywords, and these keywords might have different click through rates. To find out if that thesis is true, I conducted a study.
I built a database of 14,507 queries, their CTRs, and average positions. Data was gathered from Google Webmaster Tools from different types of websites (including e-commerce, institution website, company website and classifieds websites). The collected database includes various queries, which gives some broader perspective.
Each query was analyzed and marked as brand if it contained the domain name. Queries were checked and marked as “Product queries” if they contained product names. If the query was neither brand nor product, it was marked as “General.”
You can find expanded methodology at the bottom of the post.
The main conclusion of this analysis is that, depending on the type of queries a user chooses, their actions in web search differ. While preparing the plan for long-term SEO projects, we can assume priorities for different types of keywords. The last conclusion concerns the issue of long tail phrases that can’t be ignored. Websites have to be prepared properly so that they are ready to serve good landing pages for long tail queries.
It is obvious that reaching high positions is important. But if you want to prioritize queries and plan to reach the highest positions first with most important queries, it would be best to start with product queries, then with general queries, and after that with brand queries.
Average CTR of all queries
As you can see on the graph above, top1 is most popular (52%) for all the queries (nothing new). More importantly, the total of average CTRs for top 10 queries amounts to 208%. This means that users click more than twice on the first result page. It is obvious that top 5 queries bring huge traffic to the website, but users often go deeper in Google results, and visibility of a website on further positions might also be profitable.
Average CTR of brand queries
My study concluded that if users search using brand queries, the position in SERP remains less important than on average, for all queries in the study. Although it is important, the total of average CTRs in top 10 queries amounts to 306%, which means that users click more than three times on the first result page. It could be the result of the fact that users don’t care about the positions for such phrases, or they are trying to find what they are looking for on various kind of sources: company websites, blogs, online stores, social profiles, and so on.
Average CTR of product queries
It is clear that when users search for products, the first result is most important for them (average CTR for top1 is 53%). The total of average CTRs is 208%, so we can affirm that users click on more than two results. This might result from comparing offers on different pages. If users don’t find products they search for on the first result page, they will keep looking further in SERPs. (More information about CTRs on further result pages have been presented in the end of this study.)
Average CTR of general queries
For general queries (non branded, and non product) the average CTR graph looks very natural.
Below you can find summarizing graph for all tested queries, including brand, product, and general queries CTRs.
As you can see on the graph, the average CTRs for all product and general queries are quite similar. Brand queries’ average CTRs seems unnatural, but we can be sure that users care less about position in SERPs while using brand queries.
Long tail queries
Below you can see the average CTRs for long tail queries, containing 3, 4, and 5 words.
It is clear that when users make their queries more and more precise, the results are getting more accurate. For queries built with 4 and 5 words, visibility on the highest positions becomes increasingly important.
Let’s take a look on the average CTRs for positions 1 to 10, for long tail phrases built with 3, 4, and 5 words.
As it can be seen on the graph above, the more precise query, the more important it is to reach higher positions in SERPs. Long tail queries are very important because of the huge quality of traffic they generate. The surprising conclusion is that when users use longer queries, they open more websites from search engine result pages. The total of average CTRs in top 10 results for long tail queries (3 words) is 227%, for long tail queries (4 words) is 233%, and for long tail queries (5 words) it is 249%. We can only presume that this phenomenon occurs because search engine result pages meet the needs of users and it encourages the users to visit more than one website.
Additional data for further result pages
During my analysis, I also gathered the average CTR data for further result pages (positions 11-20, 21-30 and 31-40). We must remember that Google Webmaster Tools provide data for further positions, but denominator used for the CTR calculation is different for result page number 1, 2, 3, and so on. This occurs because it is based on the number of page views, not the number of searches. CTR on further result pages might be also distorted by the universal search, leading me to believe that data for further result pages might be less accurate than for the first one.
Below you can see the average CTRs for further result pages for the following queries:
In the first part of study, I built the database of queries, their CTRs, and their average positions. All data was gathered from Google Webmaster Tools from different types of websites.
I took the data from:
- Clothes e-commerce websites
- Drugstore e-commerce websites
- Health and beauty e-commerce websites
- Higher education institutions websites
- Jewelry company websites
- Websites providing song lyrics
- Two classifieds websites on pets and animals
- Websites with heavy machinery classifieds
The collected database includes various queries, which gives us some broader perspective. All the queries were collected from Polish websites, although I’m sure that the conclusions would prove right for all languages. The database includes 14507 queries. Having collected all the keywords, I rounded up the average positions.
Finally, each query was analyzed and marked in the appropriate category. The query was marked as a “Brand” if it contained the domain name, but was checked manually in case there were some entries to those websites from the incorrectly written domain names. It turned out that users made some mistakes quite often. For example, if the keyword was containing a small mistake, it was also marked as brand keyword. Queries were checked and marked as “Product” if they contained product names. If the query was neither Brand nor Product, it was marked as “General.”
After the analysis, I was left with:
- 14507 All queries
- 418 Brand queries
- 11684 Product queries
- 1795 General queries
- 3538 Long tail queries containing 3 words
- 1638 Long tail queries containing 4 words
- 809 Long tail queries containing 5 words
Depending on the type of queries users choose, their actions in web search differ. We have to remember this fact while planning long-term SEO projects. While scheduling our long-term work, we can prioritize queries and plan to reach the highest positions first with the most important product queries, then with general queries, and after that with brand queries. Putting huge emphasis on website optimization so that it will serve good landing pages for those queries is key.