Key takeaways
🔍 Bias in research is real and apart from leading to misleading conclusions, it can also massively impact decision-making.
🍯 Triangulation can limit bias in research and help enhance the authenticity and validity of the findings.
✨ A well-triangulated study can ensure that research insights are not overly influenced by biases, providing a framework for cross-verification of the research data gathered.
🔦 Triangulation is a research strategy that revolves around using multiple sources and methodologies to validate research findings.
💡 UXtweak can help you with your triangulation as it integrates multiple research methods within a single platform making cross-validation of insights feel like a breeze.
If you are incorporating findings from qualitative research into your product design decisions, then triangulation is a term you want to be aware of!
Bias in research can literally break your UX research as it can lead to misleading findings that can harm the user experience of your product. And this is where triangulation comes into play.
Triangulation is a research strategy that revolves around using multiple sources and methodologies to validate findings. Keep reading to learn how you can produce well-triangulated studies for biases-free insights!
The issue of bias in research
Bias in research is real and apart from leading to misleading conclusions, it can also massively impact decision-making.
It can occur due to a host of reasons, each of which can highly influence the integrity of the research findings.
For example, researchers may unconsciously choose to focus on data that supports their assumptions and not take into consideration conflicting evidence.
This is known as confirmation bias and it can lead to skewed data that validate pre-existing beliefs. On the other hand, participants can also carry biases.
According to the observer bias, the presence of a researcher might influence the participant responses and distort the authenticity of the insights gathered.
Eliminating bias in research, especially when it comes to qualitative research, is a complex task as it naturally involves subjective interpretation of the insights gathered.
It is challenging due to human involvement. For instance, a researcher’s socioeconomic background or lived experience will, whether we like it or not, shape the way they collect and interpret data.
With that said, triangulation can mitigate the risk and help enhance the authenticity and validity of the findings.
A triangulated study can ensure that research insights are not overly influenced by biases, strengthening in this way the overall research validity and providing a framework for cross-verification of the research data gathered.
💡 Pro Tip
To tackle confirmation bias in your research, mix different data collection methods like surveys, interviews, and usability tests to gather a broader range of insights.
This helps ensure you’re not just validating your assumptions, but uncovering a fuller, more accurate picture.
What Is triangulation in qualitative research?
Triangulation is essentially a research strategy that revolves around using multiple sources and methodologies to validate findings.
It is known to enhance the validity of qualitative research not only by cross-verifying data but also by removing biases that naturally come with qualitative research.
Triangulation can help you better understand and answer a research question in a more rounded and holistic way bringing to the table diverse perspectives.
Imagine a UX research team who are tasked with studying the usability of a new marketplace app.
To ensure a rounded approach to qualitative research the team decides to use different research methodologies and to combine user interviews with a survey to collect broader feedback from a larger pool of users.
Finally, they also choose to come in contact with the customer support department to identify frequent issues and questions reported by the users of the app.
With this rounded approach, the team can rest assured that they are not only reducing biases but also cross-checking insights.
Triangulation and trustworthiness in research
By bringing diverse perspectives to the table, triangulation increases trustworthiness in research. More specifically, triangulation can strengthen all four criteria that make research more trustworthy and robust.
Well-triangulated studies are more consistent and objective enhancing in this way their credibility and confirmability.
As a result, their value can be transferred to other studies strengthening their dependability and transferability as other researchers might choose to use those findings to back up their own study.
Four types of triangulation
There are four different types of triangulation that researchers could deploy:
1. Data triangulation
Data triangulation revolves around using different data sources to obtain a more rounded understanding of a research question.
By collecting data from different user groups researchers have the opportunity to remove bias in research and caption a broader and more realistic depiction of the problem being researched.
Data triangulation is known to provide a richer set of data which in turn can strengthen its validity while reducing biases.
For example, a UX researcher might choose to collect data from both technology-savvy users and users who are not familiar with technology, to better understand the overall usability of an app.
By attempting to understand how different user groups interact with the app, researchers can augment their design process.
2. Methodological triangulation
Methodological triangulation involves the application of a range of research methods to address the same research problem.
With this approach, researchers have the opportunity to gather different types of data, both quantitative and qualitative, allowing for a more holistic analysis that is biased-free.
In the same app example, the research team decides to learn more about the app usage. They decide to use a range of different methods to collect data including a survey, usability testing studies, and in-depth user interviews.
Each of these approaches will help the team gather unique data which will paint a comprehensive picture of the user interactions with the app.
🍯 Try it yourself with UXtweak’s usability testing!
3. Investigator triangulation
Investigator triangulation is an approach to triangulation where more than one researchers analyze the same data. It is a great way to remove individual biases that can occur during the interpretations of the results.
In the same app example, the lead UX researcher as part of a usability study focusing on the accessibility of the app decides to allocate two different researchers to work on the analysis of the data gathered.
This collaborative process will ensure that more than one perspective is taken into account when it comes to the result interpretation, removing any individual biases that might arise during the analysis.
This collaborative approach is also a great way to ensure that diverse viewpoints are incorporated into the final study results improving research quality.
4. Theory triangulation
Finally, theory triangulation is about using different theoretical frameworks to try and make sense of the same data. By applying different frameworks, researchers can enrich their analysis and uncover deeper underlying meanings.
For instance, in the app example above, the UX team wants to understand how easy it is for a user to start using their app.
To do so, they might analyze usability results using both the principles of behavioral psychology and cognitive theory.
This approach helps researchers avoid relying solely on one theoretical framework for the interpretation of the results leading to more comprehensive insights.
Mixed methods research
John W. Creswell defines mixed methods research as:
‘’a research design (or methodology) in which the researcher collects, analyzes, and mixes (integrates or connects) both quantitative and qualitative data in a single study or a multiphase program of inquiry.”
This blended approach to data collection allows researchers to interpret data using a more rounded, holistic approach.
Mixed methods research is particularly beneficial in cases where one research methodology might not be able to fully answer the research question.
Hence by combining more than one methodologies to answer the same research query, researchers can capture statistically significant results backed up by contextual insights.
A great example of this approach is using both the data gathered from a survey coupled with insights from in-depth user interviews to better understand the way that users interact with a language learning app.
In this instance, while the survey can capture data from a broader audience, in-depth user interviews can drill down into the user’s thoughts and motivations behind the language app usage.
It is worth noting, that mixed-method research does come with its challenges.
In mixed methods research, researchers must be seasoned enough to be able to maintain coherence while analyzing different sources and types of data.
How to use triangulation in qualitative UX research
Here is how you can use triangulation in purely qualitative UX research:
1. Parallel research rather than sequential
Triangulation in qualitative research calls for parallel research, rather than sequential, where findings are integrated in real-time.
This approach can help massively in hitting the deadlines of the study while obtaining a holistic view of the research topic.
For instance, teams might choose to conduct in-depth interviews concurrently with focus groups so that they quickly identify key trends and insights on a topic.
2. Assign confidence levels to data sources
Not all data sources are weighted equally. Assigning confidence levels to data sources is a great way to work through data sets obtained from different sources.
This approach can help researchers prioritize data and focus on the most trustworthy information while at the same time incorporating various perspectives on the research problem.
3. More data is not always better
More data does not equal better results so avoid information overload by focusing on data that can lead to meaningful insights. Keep in mind that excessive data can make it more difficult to extract findings and actionable insights.
Always aim for quality over quantity by selecting methodologies and sources that align with your research objectives.
The best tool for triangulation
There are many tools out there that can help you with your journey for well-triangulated and streamlined research studies.
UXtweak can help you hit the ground running by providing your UX teams with tools to nail your mixed methods research studies.
With a dedicated user panel you can tap into at any time, it can massively help you with the participants’ recruitment process.
In a nutshell, UXtweak provides insights into both qualitative and quantitative research—all in one powerful platform. Talk to our team today! 🍯
To sum up
Triangulation is an invaluable tool to strengthen qualitative research not only by removing biases but also by increasing trustworthiness.
By leveraging different data sources, methodologies, theoretical frameworks, and more than one investigator in the analysis process, UX teams have a unique opportunity to ensure that their findings are accurate.
To wrap up, triangulation helps to obtain richer and more in-depth insights that ultimately lead to better design decisions.
Enhance your research with UXtweak, an all-in-one research tool that seamlessly blends quantitative data and qualitative insights for smarter decisions! 🐝
