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When it comes to taking notes, everyone seems to work out their own favorite method over time. Some take longhand notes in a journal, some prefer to red-pen hard-copy output, and so on. Below, we describe some methods that have worked well for us in past studies. Feel free to mix and adapt them as you see fit.

Whichever method you use, make sure that:

  • Each finding comes from the results of one or more tasks, not your own personal opinion of a given tree.

  • Each finding that you record describes a success or an issue, but does not jump to a solution just yet. (Those come later – see below.)

  • Each finding applies to a specific part or characteristic of the tree.

    For example, findings such as “This tree confused users” are not useful. We should be able to get more specific, as in “New customers had trouble navigating the top-level headings”.


Examples of findings

Here are some examples of typical findings, to give you an idea of what you should be aiming for:

  • ~good and bad examples?


Marking up the hardcopy

The most obvious way to record findings is to print the results of each task and mark them up with a red pen, circling items of interest and jotting down findings (and follow-up questions) beside them:

  • ss of each tool’s task output with typical markups

 

This method is simple and direct, and can be cleaned up for a slide presentation later.

However, because the findings are scattered across disparate tasks, it’s a bit harder to pull together the big picture – that is, patterns that recur across tasks or across several trees. We recommend that you:

  • Do a first pass on a given tree, examining each task separately.

  • Do a second pass on that tree to look for insights across tasks, and record these on a separate sheet.

  • If you’re testing several trees, do a third pass to look for similarities and differences across all the trees.


Using a tree/task matrix

Another way to recording findings is list the tasks down a column of a spreadsheet, then list your findings beside each task:

  • ss of tasks from single tree

 

This method really comes into its own when we compare several trees that we tested with the same (or very similar) tasks:

  • We add a column for the findings of each tree.

    ~ss

  • We add a summary column on the right. For each row (i.e. for each task), this lets us adding common findings across all trees.

    ~ss

  • We add summary rows at the bottom. For each column (i.e. for each tree), we can add common findings across all tasks for that tree.

    ~ss

This gives us a matrix of trees vs. tasks, where all of our findings are in a single place, making it easier to see the bigger patterns. It’s also a compact way of coming back to our findings later:

  • ss

 

Note that we’ve used a spreadsheet here, but we’ve also done this matrix using a whiteboard, adding each finding as a color-coded sticky note (where green is good, pink is bad, and yellow is neutral).

You may find the whiteboard method better for on-site collaboration with your team, whereas the spreadsheet may work better for remote collaboration (assuming you’re using an online spreadsheet like Google Sheets) or for cases where the results need to be portable and easily accessed later in the project.

 

Adding findings to the tree spreadsheet

Another simple way of recording findings is to add a “Findings” column to the spreadsheet where we created our tree(s).

  • ss with sample findings added, with color coding

 

This works well when the findings map directly to specific items in our trees. For findings that need action (see below), you may want to highlight these according (e.g. red cell background).

For more general findings, you may want to create an area at the bottom of the spreadsheet to document these:

  • ss

 

The benefit of this method is context – when you come back to revise this tree (or extract the best ideas from it for a new tree), you’ll see the specific items that performed well or poorly.

The main drawback of this method is the same for hardcopy markup above – it makes it a bit harder to see the big picture across tasks and across different trees.

 


Next: Turning findings into actions

 

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