Triangulation is an approach to data collection and analysis that uses multiple methods, measures, or approaches to look for convergence on product requirements or problem areas. While the term “triangulation” may not trip off the tongues of HCI practitioners, we often employ triangulation, implicitly or explicitly, to bolster our recommendations and be more persuasive to our colleagues. Consider how convincing you might be if the results you obtain independently from usability tests, field interviews, and customer support data all indicate similar problems. This convergence of results across different data collection methods can help you convince a team to focus on core problems—the things that tend to emerge across methods. Triangulation can be used to determine core problems with a system or reduce the “inappropriate certainty” that sometimes comes when a single evaluation method or approach indicates that not much is wrong with a product. For example, if you run a single usability test and find that participants don’t have a serious problem, your product team may feel so confident that they think that they can forego further usability work. However, if you use multiple methods, say a large-scale customer survey and face-to-face interviews, in addition to a usability test, you might discover usability problems that were not evident in your usability test. Triangulating data from the test, survey, and interviews could help you convince the team that not all is right with the product as the usability test seemed to indicate (the inappropriate certainty to which I referred earlier).
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