In digital marketing there are many analytical reports that can be and are used to determine how well a campaign is working and what digital initiatives should be addressed moving forward to increase the response from a message or digital tactic. Search engine results page (SERP) analysis is one of those and one of my favorite analytical exercises. Being analytical by nature, I like SERP analysis because it is very objective, it involves several different metrics that play off each other, and while the interpretation is difficult at first, once you get the hang of it, it is quite fun to teach others about.
Without further ado, I give you the steps for a SERP analysis:
Step 1 – Running the Analysis
You input keywords of your choice into a program or the program provides the keywords to itself. I recommend WebPosition and/or SEMRush. The program then scans the search engine results pages to find listings for those keywords. The program will scan whatever number of search results you designate—I recommend either the top 20 or 30. Once the listings in the top 20 or 30 are found, the position in the search results of each listing is noted.
Step 2 – Interpreting the Results
Following the above process, the metrics that I focus on are the total number of listings, the total number of keywords that produced these listings and the average top position of the listings in the search results. One important note here is that the real power and insight comes when these three metrics are trended over time.
Let’s wrap up with an example. Let’s say for the list of keywords we analyzed there were 15 listings for 10 keywords in the top 30 search results and the average top position of those listings in the search results was 6.2. For the next 3 months we trend these data points and at the end of this time we are now up to 30 listings for 20 keywords and an average top position of 8.2. Three more months go by and we are now up to 35 listings for 23 keywords and an average top position of 4.3.
The goal is to have a high number of listings and keywords in the top 30 search results and a low average top position. In our example above, this is what we experienced. Over a 6 month period, our listings and keywords increased while our average top position decreased. If you noticed that the average top position increased at the 3 month mark, give yourself a pat on the back. The reason for this is that often times when you see a rapid increase in the number of listings in a short time frame, the average top position may bump up temporarily, but over time, the goal is for it to come back down. This is search engine results page (SERP) analysis in a nutshell. You will notice if you check out WebPosition and/or SEMRush that there are some additional relevant metrics that we did not discuss here that I encourage you explore.
[Contributed by Ben Hill]