This is a web-based app that works with Google Analytics data to explore site search usage on a site. There are three main components of what it does:

* "Stemming" of site search terms -- Sébastien Brodeur did a demo at Superweek 2017 of how he collapsed the variations of search terms into a single "stemmed" term. This makes for more meaninful frequency counts.

* Selective removal of terms -- many sites have some "dominant" search terms that are valid...but that dwarf the ability to get to the really interesting stuff. This app allows the user to simply type in words to remove them from the frequency counts and word cloud.

* Questions in search -- this was something Nancy Koons presented a few years ago -- filter down to just the searches that start with a "question word." These are searches well out on the long tail of searches, but they can be very insightful

Link 1 included here shows the first two items -- a word cloud and how "dominant but uninteresting" terms can be removed to make a more meaningful word cloud.

Link 2 shows the second item -- how "questions" get surfaced by filtering for specific terms.

A more complete description of this approach is available at: http://analyticsdemystified.com/google-analytics/exploring-site-search-help-r/ (Link 3)

If you have access to a Google Analytics account that is configured for site search tracking, you can try this tool out without doing any coding at: https://gilligan.shinyapps.io/ga-site-search/.

If you would like to download the R code to run it locally or make modifications, it is available on Github: https://github.com/gilliganondata/site-search-wordcloud.

RELATED: Link 1 · Link 2 · Link 3