In this walkthrough, I introduce the tool by accessing it directly through a web browser to extract data and analyze it in R.
The highest peak is July 2014 and represents the 100% maximum search for the term. Everything else is scaled from that peak, and that is how Google Trends displays a single search term over time (i.e. nothing will be over 100 in the graph). The term also peaks with clockwork regularity every summer. This decline can mean that people’s interest in cycling is declining, that the term cycling in the English language is replaced by another more popular term, or that cyclists aren’t using Google like they used to (your theory is as good as mine).
Let’s make things more interesting and add a second search term to our graph. Let’s add the term
So far, we’ve seen two interesting pieces of data using Google Trends: the term’s popularity and its seasonal effect. There is plenty more to explore and compare as trends can be narrowed by time, region and city. Here we see both terms applied to
cycling is more popular than