If the time after search is low it could mean that they easily found what they were looking for, consumed the content and left (although it will depend on the type of website)
If the time after searching is high or very high, it could mean that you finally found what you were looking for and you were checking everything, or that it took you a long time to find it and you had to go around the web a lot to get it (it will depend again on the type of website).
This is why it is very productive to cross-reference internal searches with objectives, and not only with web behavior metrics.
You can also cross-reference searches and look at topics to see if “people searching for SEO tend to read more articles or generate more subscriptions than those searching for social list of cabo verde consumer email media, or vice versa.” Or analyze what depth of searches each type of user needs, that is, if they find what they were looking for once or if they needed more than one search to find it. You can see the latter in Google Analytics in the reports of:
After all this grouped analysis, you will need to carry out this same exercise but identifying one by one all the searches that users have made or, at least, the most important ones by volume or performance. In the report that I have attached with the template you have your TOP 10 internal searches. And if you still did not have the internal search engine configured, the searches that users make will gradually appear there from the moment you configure it.
What are your potential customers or readers not finding?
We anticipated this in the previous point, but very low figures for “average time after search” will indicate that we have not managed to respond to what the potential client or reader was looking for.
