Which decision tree format is easier for humans?

Decision trees are a useful way to organize choices. Unfortunately, the quality of these trees varies quite a bit. One of the biggest problems I’ve seen is in the way that they are structured. I’m going to describe two approaches here and then suggest the better option.

Both of the following decision trees lead the reader through the same options of choosing a fruit, but the formats are different. This first version, called a “binary decision” tree, asks a question at each step that can only be answered with a “yes” or a “no”.


It’s great from a programming perspective (i.e. binary), but is is best for humans? Try this Binary Decider we created based on the decision tree above. Do you find it usable?

Now, take a look at this second version which can show multiple options at each step, and requires a description of each answer.


Notice a difference? Give this Fruit Attribute Decider a try now. Which is easier to use? I would contend, that for the human reader, this second option is superior for the following reasons:

  • There are fewer options to decide among. The binary tree above has 8 options, while the second one has only 6. This is because you can have more than two choices at each step. It lets you deal with several mutually-exclusive options at once.
  • It’s easier to skim. The descriptive answers don’t require you to to look back at the questions to ensure you didn’t get mixed up.
  • It’s easier to review. It is also much easier to review your route when you are done. (i.e. {yellow, round, small = lemon} versus {no, yes, yes, no = lemon})

The reason I’m describing this is because I often see online decision trees written in the unfriendly binary format. Take the time to rewrite them for your human readers by avoiding “yes” and “no” as options. Your readers will thank you!

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