Average Internal Search Position Clicked
A few years ago, I wrote an extensive post describing how to track internal search position clicks to see which internal search positions visitors tend to click on. That post showed how to track impressions and clicks for internal search positions and how to view this by search phrase. Recently, however, I had a client ask for something tangentially related to this. This client was interested in seeing the overall average search position clicked when visitors search on their website and for each search term. While the preceding post provides a way to see the distribution of clicks on internal search spots, it didn’t provide a straightforward way to calculate the overall average. Therefore in this post, I will share a way to do this for those who want to see a trended view of how far down the search results list your visitors are going.
Calculating the Average Internal Search Position Clicked
The key difference in calculating the average internal search position clicked from what I described in my previous post, is that you need to switch from using a dimension (eVar) to using a metric (Success Event). To compute the average search position, the formula we eventually need is one that divides the summation of the position numbers clicked by the number of total internal searches. For example, if I conduct a search and click on the 10th result and then another search and click on the 5th result, I have clicked on an aggregate of 15 internal search positions (10+5) and had 2 search clicks. When I divide these two elements, I can see that my average search position clicked is 7.5 (15/2). Hence, if you apply the same approach for all of your visitors, you will be able to calculate the overall average internal search position.
From an implementation standpoint, this is relatively easy. If you have internal search on your site, you are probably already setting a metric (Success Event) on the search results page to determine how often searches are taking place. If you followed my advice in this post, you would also be setting a second metric when visitors click on a result in your search result list. Therefore, the only piece you are missing is a metric that quantifies the position number clicked. To do this in Adobe Analytics you would set a new Numeric (or Counter if on latest code) Success Event with the number value of the position clicked (let’s call this Search Position). For example, if a visitor conducts a search and clicks on the 5th position, you would pass a value of “5” to the new success event. This will create the numerator needed to calculate the average search position.
Once you have done this, you have the two metrics you need to calculate the average – search position numbers and the number of search clicks. Simply create a new Calculated Metric that divides the Search Position by the # of Search Clicks to compute the average as shown here:
This will produce a metric repost like this:
Average Search Position by Search Phrase
Since you are most likely already capturing the search phrase when visitors search, you can also view this new Calculated Metric by search phases, by simply adding it to the dimension (eVar) report:
This report and the preceding ones can be used to watch your search result clicks overall and by search phrase. This may help you determine if your search results are meeting the needs of your users and whether you even need to have pages and pages of search results.
One fun way I have used this type of analysis is to take my top search phrases and hand-pick specific links that I want them to go to for the top search phrases (recommended links). Then you can see if your users prefer the organic results or the ones you have picked for them (using a new eVar!). Another way to use this analysis is to see if changes made to your internal search makes the average search position clicked go up or down. Regardless of how you use it, if you are going to use internal search on your site, you may as well track it appropriately. Enjoy!