How to optimize your search strategy using data visualization

In this video, we’ll look at how using data visualization techniques can help us understand and improve our search strategies.

The benefits offered by visualization become more apparent as the complexity of your search increases. For example, here is a relatively complex search string used by a recruiter to find social profiles for project managers in the Republic of Ireland. As you can see, it is quite hard to visualize how this search is structured, and even harder to debug or improve.

But when we open it using 2Dsearch, we immediately see that it consists of 5 nested blocks, corresponding to a role, a location, and various other terms designed to include CVs but exclude other unwanted document types. Note that elements shown in dark blue correspond to specialist operators that in this case restrict the search to specific fields such as the url or filetype.

Once we have our search opened in 2Dsearch we can visualize it in different ways. For example, we might choose to view it as a hierarchical tree structure, with various branches that we can open or close on demand. Or we could view it as an Inline sequence of blocks with a left to right reading - much like a traditional Boolean string, but more transparent and directly editable. Or we could go back to our default Nested view, which visualizes our search as a set of nested containers.

It’s important to note that there is no such thing as the perfect visualization - each one has its strengths and weakness. Choose the one that helps you best understand and optimize your searches.

Finally, let’s look at how to save blocks for later re-use. Suppose I want to create some new searches that also focus on the RoI. Rather than have to re-enter this block every time, I can simply save it in my personal repository, ready to be imported and re-used in a future search.