When running a content experiment, what is a crucial best practice for a business practitioner?

Isolating the variables being tested is a crucial best practice when running a content experiment because it ensures that the effects observed can be attributed directly to the changes made in those specific variables. When only one variable is altered at a time, it becomes clear how that variable influences the overall results. This clarity is essential for accurately interpreting the outcomes of the experiment and making informed decisions based on the data.

In contrast, including multiple variables or testing multiple metrics simultaneously can lead to confounding results, where it's difficult to discern which variable or metric is responsible for any observed changes. Similarly, using a single measurement method can overlook important insights that might emerge from a more diverse evaluation approach, but it doesn’t inherently isolate the variables being tested as effectively as focusing strictly on one variable at a time. Thus, isolating variables is fundamental to conducting effective and reliable experiments.