From findings to insights: harnessing triangulation to elevate your research
A pathway to meaningful, actionable UX research
1 minute takeaway:
I’ve put together a handy 8-Step Triangulation Checklist Guide — included at the end of this article.
A question I’m often asked is, “how do I turn research findings into actionable insights?”
As UX researchers, a key challenge we face is ensuring that our findings are credible and truly reflect real user experiences.
A powerful approach to achieving this is through triangulation — a method long used in fields like health and social sciences. While often associated with those disciplines, the principles of triangulation are equally valuable in UX research.
It’s a bit rare for me to come across emerging researchers, especially in UX, who fully embrace triangulation as part of their research approach. I’d love to see it become a more common practice.
By employing triangulation, you move beyond merely identifying patterns in your data (i.e., findings) to uncovering deeper insights, providing a clearer understanding of what’s happening and guiding your next steps.
In this article, I’ll explore:
- what triangulation is,
- the various types,
- its key benefits, and
- anchor the discussion with practical UX examples
At the end of this article, you’ll find additional resources — including a Triangulation Checklist Guide, recommended courses, and references — to help you deepen your skills and expand your knowledge on this topic.
Let’s dive in!
What is triangulation?
Definition: In its simplest form, triangulation refers to the combination of at least two or more theoretical perspectives, methodological approaches, data sources, investigators, or data analysis methods to study something.
In UX research, triangulation can:
- Provide a way to confirm findings across different methods, which then lead to our final insights
- Offer a more nuanced understanding of user experiences, and
- Allow you to prioritize your insights (alongside your recommendations) more effortlessly
- Plus more (detailed below)
Our goal here: counterbalance the limitations of a single method and enhance the richness of research findings — ultimately, we want to transform our findings to insights, and prioritize them for our team with ease.
Example: Imagine you’re researching how users interact with a new mobile app feature.
You could start with usability testing to observe user behavior in real time and gather qualitative insights. However, by also running a quantitative study — tracking metrics like task completion rates and time-on-task — you’d gain additional data that helps verify your initial observations. Combining these methods (triangulation) allows you to see not just what users are doing (recounting) but also why they behave that way (motivations, potential expectations).
This example illustrates “Methodological Triangulation”, but the true power of triangulation emerges when all five types of triangulation are employed together.
Types of triangulation
There are several types of triangulation you can use in your research (the numbers below are for clarity and do not indicate their importance):
Data Triangulation: First, we have “Data Triangulation” or “Source Triangulation” — this involves gathering data from different sources to see if the findings hold across different contexts, such as different user groups or testing environments.
In UX research, this could involve conducting usability tests across multiple devices and contexts — e.g., not just focusing on the mobile experience, but also exploring how users interact on desktop, tablet, and other platforms.
Investigator Triangulation: Next, we have “Investigator Triangulation” — this approach uses multiple researchers to collect or analyze data.
The benefit here is that it minimizes personal biases, which may arise if only one researcher conducts the study.
For UX teams, collaborative research involving multiple analysts can lead to more reliable findings.
Note: Often, having multiple researchers on a study isn’t feasible, and one researcher is responsible for the entire process from start to finish. In these cases, it’s up to that researcher to actively seek collaboration, check their biases, and be open to refining their insights and recommendations.
Methodological Triangulation: This involves using more than one method to collect data, such as combining quantitative and qualitative techniques.
For example, pairing survey results with usability tests can provide a more comprehensive view of user interactions. This is a common practice in many UX settings.
However, I’ve noticed that competitor reviews are often under-utilized in many contexts.
- Many teams tend to examine their products in a vacuum, focusing on how they compare to other products within the same company rather than exploring the solutions that competitors are offering.
- This narrow perspective can limit opportunities for improvement.
- By not considering what competitors bring to the table, teams miss valuable insights that could inform their design decisions and enhance the overall user experience.
- Conducting thorough competitor tests (in addition to ongoing studies, such as usability studies) can help identify gaps and inspire new ideas, ultimately leading to more competitive products.
I really want to make this point clear, so let’s dive into an example from the oil industry together!
Example: Imagine a team working on a new oil exploration software.
During usability tests, they might find that users have difficulty navigating the interface and accessing real-time data efficiently.
To gain deeper insights, they decide to conduct thorough competitor analysis by examining similar software from companies like Schlumberger or Halliburton.
Through this analysis, they discover that these competitors offer features like advanced data visualization tools and integrated communication platforms that significantly improve decision-making.
By identifying these gaps, the team could choose to incorporate similar functionalities or develop innovative features that cater specifically to their users’ needs. This approach not only enhances the software’s usability and effectiveness but also helps position it more competitively within the industry.
Theoretical Triangulation: This type of triangulation involves using multiple theories to interpret data, allowing you to explore the topic from various perspectives.
UX researchers can draw from psychology, design theory, and economics to deepen their understanding of user motivations.
I observe that this type of triangulation is often underutilized in practice, despite its numerous benefits.
Example: Imagine analyzing a fitness app.
By applying psychological theories like self-determination theory, researchers can better understand how factors like user autonomy influence engagement levels.
At the same time, using design theory lets researchers evaluate the app’s interface for usability, ensuring it’s user-friendly and intuitive.
For instance, looking at how the color blue impacts user interaction might reveal that users are drawn to elements that are not only attractive but also fit the app’s visual context. This blend of perspectives helps create an app that’s engaging, easy to use, and visually appealing.
Data-Analysis Triangulation: As importantly, this form of triangulation involves applying multiple methods of data analysis to the same dataset.
For example, combining non-verbal analysis (e.g., behavioral coding) with linguistic analysis (e.g., contextualist thematic analysis on open-ended responses) on the same participant or sample could shed light on patterns that are not obvious from one data analysis alone.
Note that in the provided example, both non-verbal analysis and linguistic analysis fall under the umbrella of qualitative analysis.
Notice as well how data analysis triangulation differs from methodological triangulation (where we employ different types of qualitative and quantitative research methods).
Benefits of triangulation in UX research
Key takeaways from this section — triangulation:
- Increases reliability and validity
- Reveals deeper insights
- Reduces bias
- Encourages creativity
- Provides a comprehensive view
The ultimate advantage of triangulation is that it enables you to share actionable insights, not just research findings. This approach helps you prioritize and highlight the most important points, like sharing the top two insights from your report with your team.
This is possible because triangulation provides you with:
- Increased Confidence in Findings: When multiple methods or perspectives lead to the same conclusion the reliability of those findings is enhanced. For example, if both usability testing and surveys show users struggling with the same feature, it’s likely a strong signal that improvements are needed.
- Deeper Insights: Different methods reveal different types of information. Quantitative methods can uncover frequency or magnitude patterns, while qualitative methods can explain why those patterns occur (which, as a side note, may in themselves indicate patterns of motivation). By using both, UX researchers can gain a more comprehensive understanding of user behavior.
- Minimized Bias: Ultimately, no single method is free from bias, but by using triangulation, UX researchers can cross-check findings across multiple methods, reducing the likelihood that biases will distort the results.
- Creative Insight: Triangulation often leads to unexpected understandings. By combining different approaches, researchers can uncover new dimensions of user experiences that may not have been visible through a single method.
A note on potential challenges
Despite its advantages, triangulation comes with potential challenges.
It can be a bit time-consuming, especially for beginners who are just getting the hang of things.
Learning the ropes and navigating the various methodologies can feel overwhelming at first. Plus, it often requires extra resources — like training materials, tools, or even software — to help streamline the process.
Collaboration across teams is another key element. Working together brings diverse perspectives that enrich the project, but it can also make coordination a bit tricky.
Ensuring everyone is on the same page and communicating effectively can take time, but it ultimately leads to a more thorough understanding and better results. While it may seem complex initially, with patience and teamwork, the process can become much more manageable and rewarding!
The key is to clearly define the purpose of triangulation and ensure that the methods chosen complement each other rather than creating confusion.
A final note:
Triangulation offers a pathway to actionable UX insights.
By drawing on multiple methods, perspectives, and sources, we can deliver more comprehensive research that better reflects the diversity of user experiences.
It is crucial to use triangulation thoughtfully, ensuring that it adds value to the research without overcomplicating the process.
My challenge to you: Try using triangulation in your next project and discover how it can elevate your findings!
Don’t forget to share your experiences and insights with the UX community — we’re all learning together, and your input can make a big difference.
About the author: I’m a UX Researcher @Microsoft / / .
I earned my Bachelor of Arts in Psychology with Honours from the University of Waterloo, followed by a Master’s in Social Psychology from Wilfrid Laurier University. I then returned to the University of Waterloo for a Master’s in Digital Experience Innovation, where I delved deeper into how technology can enhance user experiences and drive meaningful interactions.
I’m passionate about UX research and love getting to know users deeply.
Let’s connect! https://uwaterloo.ca/scholar/h2alhome/about
I’ve put together a handy 8-Step Triangulation Checklist Guide (below) — read through and let me know what you think!
Additional reading:
Integrating UX research into existing design teams: navigating the challenges
Getting started with UX design: a beginner’s guide | by The UX Times Magazine | Bootcamp
Triangulation: repurposing a surveying technique for UX design
Helpful courses:
(1) — “UX Design: Implementation Planning” by Chris Nodder
(2) — “UX Deep Dive: Analyzing Data” by Amanda Stockwell
(3) — “Presenting your research: A crash course in persuasive techniques” by Sarah Weise
References:
Creswell, J. W., & Plano Clark, V. L. (2017). “Designing and Conducting Mixed Methods Research.” SAGE Publications.
Bazeley, P. (2013). “Qualitative Data Analysis: Practical Strategies.” SAGE Publications.
Kams Thorum (2020). “Triangulation: repurposing a surveying technique for UX design.” UX Collective. https://uxdesign.cc/triangulation-repurposing-a-surveying-technique-for-ux-design-9a4151d15421
Patton, M. Q. (2015). “Qualitative Research & Evaluation Methods.” SAGE Publications.
Flick, U. (2018). “An Introduction to Qualitative Research.” SAGE Publications.
