One of the central problems we run into when discussing research finds, particularly when we’re using those finding to give strategic direction, is having the research’s validity called into question. I’ve talked over the years a fair amount about the idea of triangulation, but I’ve rarely summed up what it means. Here’s my take in a nutshell. Validity refers to whether the findings of a study are true in the sense that findings accurately reflect the situation and are supported by evidence. Triangulation is used by qualitative researchers in particular to check and establish validity in their studies by analyzing a research question from multiple perspectives. The goal of triangulation isn’t to arrive at consistency across data sources or approaches since inconsistencies may be likely point to opportunities to uncover deeper meaning in the data. In other words, points of contradiction signal things we can leverage. The point of triangulation is to start to make sense of complexity and to operationalize how we uncover insights. So what do I mean by triangulation? That’s easiest to understand in terms of triangulation types:
- Data triangulation
- Theory triangulation
- Methodological triangulation
- Environmental triangulation
Data triangulation involves using different sources of information in order to increase the validity of a study. These sources are likely to be stakeholders in a project – participants, other researchers, employees, community members, etc. I the case of studying fast food and family meals, for example, the research process would start by identifying the stakeholder groups such as parents, children, cooks, cashiers, coaches, etc. Participant observation could be conducted with each of these groups to gain insight into their practices, habits, and beliefs. Or, more likely, concessions are made and in-depth interviewing takes place with a smaller set of stakeholders. During the team analysis stage, observations are compared to determine areas of agreement as well as areas of divergence. This type of triangulation, is perhaps the most popular because it is the easiest and quickest to implement..
Theory triangulation involves the use of multiple perspectives to interpret a single set of data. This method typically entails using sources outside of a particular field of study. One popular approach is to bring together people from different disciplines. For example, a team looking into grocery shopping habits might have people trained in research at its core, but it might also bring in people with backgrounds in theater or storytelling because shopping is increasingly a performative act. These individuals from different disciplines or positions bring different perspectives. Therefore if each evaluator from the different disciplines interprets the information in the same way, then validity is established.
Methodological triangulation involves the use of multiple qualitative and/or quantitative methods to study the topic. For example, results from surveys, focus groups, and interviews are compared to see if similar results are being found. If the conclusions from each of the methods are the same, then validity is established. If contradictions are found, then there is either a flaw or an area to dig into in more depth.
For example, suppose a researcher is conducting a case study of a video gaming to determine how best to position a brand. A researcher would use interviewing, observation, document analysis, or any other feasible method to assess gaming habits. In addition, a researcher could also survey participants, people watching Twitch, and game developers as a quantitative strategy. If the findings from all of the methods draw the same or similar conclusions, then validity has been established.
Environmental triangulation involves the use of different locations, settings, season, and other factors related to the environment in which the study took place. The key is identifying which environmental factors, if any, might influence the information that is received during the study. These environmental factors are changed to see if the findings are the same across settings. For example, suppose a research team wants to evaluate how people use gym memberships in order to determine when and how best to market to potential new members. If the evaluation occurs during the holiday season, there may be different results because people are too busy to get in workouts or look into memberships. In order to triangulate the data, a researcher would need to evaluate fitness habits throughout the year in order to gather true and certain information on behavior changes and the reasons driving them.
Benefits and Problems. The benefits of triangulation are that it increasing confidence in research data, creating innovative ways of understanding a phenomenon, revealing unique findings, challenging or integrating theories, and providing a clearer understanding of the problem. That leads to new opportunities, richer marketing and advertising strategies, and reduced risk. On the downside, the primary disadvantage of triangulation is that it can be time consuming. Collecting and sifting through more data requires greater planning, resources, and commitment. Triangulation is a useful in research and the development of solid marketing strategies, but it’s absolutely necessary to weigh the advantages and disadvantages before putting it into practices.