November 6, 2025
4 min

A beginner’s guide to qualitative and quantitative research

In the field of user research, every method is either qualitative, quantitative – or both. Understandably, there’s some confusion around these 2 approaches and where the different methods are applicable. This article provides a handy breakdown of the different terms and where and why you’d want to use qualitative or quantitative research methods.

Qualitative research

Let’s start with qualitative research, an approach that’s all about the ‘why’. It’s exploratory and not about numbers, instead focusing on reasons, motivations, behaviors and opinions – it’s best at helping you gain insight and delve deep into a particular problem. This type of data typically comes from conversations, interviews and responses to open questions. The real value of qualitative research is in its ability to give you a human perspective on a research question. Unlike quantitative research, this approach will help you understand some of the more intangible factors – things like behaviors, habits and past experiences – whose effects may not always be readily apparent when you’re conducting quantitative research. A qualitative research question could be investigating why people switch between different banks, for example.

When to use qualitative research

Qualitative research is best suited to identifying how people think about problems, how they interact with products and services, and what encourages them to behave a certain way. For example, you could run a study to better understand how people feel about a product they use, or why people have trouble filling out your sign up form. Qualitative research can be very exploratory (e.g., user interviews) as well as more closely tied to evaluating designs (e.g., usability testing). Good qualitative research questions to ask include:

  • Why do customers never add items to their wishlist on our website?
  • How do new customers find out about our services?
  • What are the main reasons people don’t sign up for our newsletter?

How to gather qualitative data

There’s no shortage of methods to gather qualitative data, which commonly takes the form of interview transcripts, notes and audio and video recordings. Here are some of the most widely-used qualitative research methods:

  • Usability test Test a product with people by observing them as they attempt to complete various tasks.
  • User interview Sit down with a user to learn more about their background, motivations and pain points.
  • Contextual inquiry – Learn more about your users in their own environment by asking them questions before moving onto an observation activity.
  • Focus group – Gather 6 to 10 people for a forum-like session to get feedback on a product.

How many participants will you need?

You don’t often need large numbers of participants for qualitative research, with the average range usually somewhere between 5 to 10 people. You’ll likely require more if you're focusing your work on specific personas, for example, in which case you may need to study 5-10 people for each persona. While this may seem quite low, consider the research methods you’ll be using. Carrying out large numbers of in-person research sessions requires a significant time investment in terms of planning, actually hosting the sessions and analyzing your findings.

Quantitative research

On the other side of the coin you’ve got quantitative research. This type of research is focused on numbers and measurement, gathering data and being able to transform this information into statistics. Given that quantitative research is all about generating data that can be expressed in numbers, there multiple ways you make use of it. Statistical analysis means you can pull useful facts from your quantitative data, for example trends, demographic information and differences between groups. It’s an excellent way to understand a snapshot of your users. A quantitative research question could involve investigating the number of people that upgrade from a free plan to a paid plan.

When to use quantitative research

Quantitative research is ideal for understanding behaviors and usage. In many cases it's a lot less resource-heavy than qualitative research because you don't need to pay incentives or spend time scheduling sessions etc). With that in mind, you might do some quantitative research early on to better understand the problem space, for example by running a survey on your users. Here are some examples of good quantitative research questions to ask:

  • How many customers view our pricing page before making a purchase decision?
  • How many customers search versus navigate to find products on our website?
  • How often do visitors on our website change their password?

How to gather quantitative data

Commonly, quantitative data takes the form of numbers and statistics.

Here are some of the most popular quantitative research methods:

  • Card sorts Find out how people categorize and sort information on your website.
  • First-click tests See where people click first when tasked with completing an action.
  • A/B tests – Compare 2 versions of a design in order to work out which is more effective.
  • Clickstream analysis – Analyze aggregate data about website visits.

How many participants will you need?

While you only need a small number of participants for qualitative research, you need significantly more for quantitative research. Quantitative research is all about quantity. With more participants, you can generate more useful and reliable data you can analyze. In turn, you’ll have a clearer understanding of your research problem. This means that quantitative research can often involve gathering data from thousands of participants through an A/B test, or with 30 through a card sort. Read more about the right number of participants to gather for your research.

Mixed methods research

While there are certainly times when you’d only want to focus on qualitative or quantitative data to get answers, there’s significant value in utilizing both methods on the same research projects.Interestingly, there are a number of research methods that will generate both quantitative and qualitative data. Take surveys as an example. A survey could include questions that require written answers from participants as well as questions that require participants to select from multiple choices.

Looking back at the earlier example of how people move from a free plan to a paid plan, applying both research approaches to the question will yield a more robust or holistic answer. You’ll know why people upgrade to the paid plan in addition to how many. You can read more about mixed methods research in this article:

Where to from here?

Now that you know the difference between qualitative and quantitative research, the best way to build confidence is to start testing. Hands-on experience is the fastest path to deeper insight. At Optimal, we make it easy to run your first study, no matter your role or research experience.

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1 min read

Efficient Research: Maximizing the ROI of Understanding Your Customers

Introduction

User research is invaluable, but in fast-paced environments, researchers often struggle with tight deadlines, limited resources, and the need to prove their impact. In our recent UX Insider webinar, Weidan Li, Senior UX Researcher at Seek, shared insights on Efficient Research—an approach that optimizes Speed, Quality, and Impact to maximize the return on investment (ROI) of understanding customers.

At the heart of this approach is the Efficient Research Framework, which balances these three critical factors:

  • Speed – Conducting research quickly without sacrificing key insights.
  • Quality – Ensuring rigor and reliability in findings.
  • Impact – Making sure research leads to meaningful business and product changes.

Within this framework, Weidan outlined nine tactics that help UX researchers work more effectively. Let’s dive in.

1. Time Allocation: Invest in What Matters Most

Not all research requires the same level of depth. Efficient researchers prioritize their time by categorizing projects based on urgency and impact:

  • High-stakes decisions (e.g., launching a new product) require deep research.
  • Routine optimizations (e.g., tweaking UI elements) can rely on quick testing methods.
  • Low-impact changes may not need research at all.

By allocating time wisely, researchers can avoid spending weeks on minor issues while ensuring critical decisions are well-informed.

2. Assistance of AI: Let Technology Handle the Heavy Lifting

AI is transforming UX research, enabling faster and more scalable insights. Weidan suggests using AI to:

  • Automate data analysis – AI can quickly analyze survey responses, transcripts, and usability test results.
  • Generate research summaries – Tools like ChatGPT can help synthesize findings into digestible insights.
  • Speed up recruitment – AI-powered platforms can help find and screen participants efficiently.

While AI can’t replace human judgment, it can free up researchers to focus on higher-value tasks like interpreting results and influencing strategy.

3. Collaboration: Make Research a Team Sport

Research has a greater impact when it’s embedded into the product development process. Weidan emphasizes:

  • Co-creating research plans with designers, PMs, and engineers to align on priorities.
  • Involving stakeholders in synthesis sessions so insights don’t sit in a report.
  • Encouraging non-researchers to run lightweight studies, such as A/B tests or quick usability checks.

When research is shared and collaborative, it leads to faster adoption of insights and stronger decision-making.

4. Prioritization: Focus on the Right Questions

With limited resources, researchers must choose their battles wisely. Weidan recommends using a prioritization framework to assess:

  • Business impact – Will this research influence a high-stakes decision?
  • User impact – Does it address a major pain point?
  • Feasibility – Can we conduct this research quickly and effectively?

By filtering out low-priority projects, researchers can avoid research for research’s sake and focus on what truly drives change.

5. Depth of Understanding: Go Beyond Surface-Level Insights

Speed is important, but efficient research isn’t about cutting corners. Weidan stresses that even quick studies should provide a deep understanding of users by:

  • Asking why, not just what – Observing behavior is useful, but uncovering motivations is key.
  • Using triangulation – Combining methods (e.g., usability tests + surveys) to validate findings.
  • Revisiting past research – Leveraging existing insights instead of starting from scratch.

Balancing speed with depth ensures research is not just fast, but meaningful.

6. Anticipation: Stay Ahead of Research Needs

Proactive researchers don’t wait for stakeholders to request studies—they anticipate needs and set up research ahead of time. This means:

  • Building a research roadmap that aligns with upcoming product decisions.
  • Running continuous discovery research so teams have a backlog of insights to pull from.
  • Creating self-serve research repositories where teams can find relevant past studies.

By anticipating research needs, UX teams can reduce last-minute requests and deliver insights exactly when they’re needed.

7. Justification of Methodology: Explain Why Your Approach Works

Stakeholders may question research methods, especially when they seem time-consuming or expensive. Weidan highlights the importance of educating teams on why specific methods are used:

  • Clearly explain why qualitative research is needed when stakeholders push for just numbers.
  • Show real-world examples of how past research has led to business success.
  • Provide a trade-off analysis (e.g., “This method is faster but provides less depth”) to help teams make informed choices.

A well-justified approach ensures research is respected and acted upon.

8. Individual Engagement: Tailor Research Communication to Your Audience

Not all stakeholders consume research the same way. Weidan recommends adapting insights to fit different audiences:

  • Executives – Focus on high-level impact and key takeaways.
  • Product teams – Provide actionable recommendations tied to specific features.
  • Designers & Engineers – Share usability findings with video clips or screenshots.

By delivering insights in the right format, researchers increase the likelihood of stakeholder buy-in and action.

9. Business Actions: Ensure Research Leads to Real Change

The ultimate goal of research is not just understanding users—but driving business decisions. To ensure research leads to action:

  • Follow up on implementation – Track whether teams apply the insights.
  • Tie findings to key metrics – Show how research affects conversion rates, retention, or engagement.
  • Advocate for iterative research – Encourage teams to re-test and refine based on new data.

Research is most valuable when it translates into real business outcomes.

Final Thoughts: Research That Moves the Needle

Efficient research is not just about doing more, faster—it’s about balancing speed, quality, and impact to maximize its influence. Weidan’s nine tactics help UX researchers work smarter by:


✔️  Prioritizing high-impact work
✔️  Leveraging AI and collaboration
✔️  Communicating research in a way that drives action

By adopting these strategies, UX teams can ensure their research is not just insightful, but transformational.

Watch the full webinar here

Learn more
1 min read

A beginner’s guide to qualitative and quantitative research

In the field of user research, every method is either qualitative, quantitative – or both. Understandably, there’s some confusion around these 2 approaches and where the different methods are applicable. This article provides a handy breakdown of the different terms and where and why you’d want to use qualitative or quantitative research methods.

Qualitative research

Let’s start with qualitative research, an approach that’s all about the ‘why’. It’s exploratory and not about numbers, instead focusing on reasons, motivations, behaviors and opinions – it’s best at helping you gain insight and delve deep into a particular problem. This type of data typically comes from conversations, interviews and responses to open questions. The real value of qualitative research is in its ability to give you a human perspective on a research question. Unlike quantitative research, this approach will help you understand some of the more intangible factors – things like behaviors, habits and past experiences – whose effects may not always be readily apparent when you’re conducting quantitative research. A qualitative research question could be investigating why people switch between different banks, for example.

When to use qualitative research

Qualitative research is best suited to identifying how people think about problems, how they interact with products and services, and what encourages them to behave a certain way. For example, you could run a study to better understand how people feel about a product they use, or why people have trouble filling out your sign up form. Qualitative research can be very exploratory (e.g., user interviews) as well as more closely tied to evaluating designs (e.g., usability testing). Good qualitative research questions to ask include:

  • Why do customers never add items to their wishlist on our website?
  • How do new customers find out about our services?
  • What are the main reasons people don’t sign up for our newsletter?

How to gather qualitative data

There’s no shortage of methods to gather qualitative data, which commonly takes the form of interview transcripts, notes and audio and video recordings. Here are some of the most widely-used qualitative research methods:

  • Usability test Test a product with people by observing them as they attempt to complete various tasks.
  • User interview Sit down with a user to learn more about their background, motivations and pain points.
  • Contextual inquiry – Learn more about your users in their own environment by asking them questions before moving onto an observation activity.
  • Focus group – Gather 6 to 10 people for a forum-like session to get feedback on a product.

How many participants will you need?

You don’t often need large numbers of participants for qualitative research, with the average range usually somewhere between 5 to 10 people. You’ll likely require more if you're focusing your work on specific personas, for example, in which case you may need to study 5-10 people for each persona. While this may seem quite low, consider the research methods you’ll be using. Carrying out large numbers of in-person research sessions requires a significant time investment in terms of planning, actually hosting the sessions and analyzing your findings.

Quantitative research

On the other side of the coin you’ve got quantitative research. This type of research is focused on numbers and measurement, gathering data and being able to transform this information into statistics. Given that quantitative research is all about generating data that can be expressed in numbers, there multiple ways you make use of it. Statistical analysis means you can pull useful facts from your quantitative data, for example trends, demographic information and differences between groups. It’s an excellent way to understand a snapshot of your users. A quantitative research question could involve investigating the number of people that upgrade from a free plan to a paid plan.

When to use quantitative research

Quantitative research is ideal for understanding behaviors and usage. In many cases it's a lot less resource-heavy than qualitative research because you don't need to pay incentives or spend time scheduling sessions etc). With that in mind, you might do some quantitative research early on to better understand the problem space, for example by running a survey on your users. Here are some examples of good quantitative research questions to ask:

  • How many customers view our pricing page before making a purchase decision?
  • How many customers search versus navigate to find products on our website?
  • How often do visitors on our website change their password?

How to gather quantitative data

Commonly, quantitative data takes the form of numbers and statistics.

Here are some of the most popular quantitative research methods:

  • Card sorts Find out how people categorize and sort information on your website.
  • First-click tests See where people click first when tasked with completing an action.
  • A/B tests – Compare 2 versions of a design in order to work out which is more effective.
  • Clickstream analysis – Analyze aggregate data about website visits.

How many participants will you need?

While you only need a small number of participants for qualitative research, you need significantly more for quantitative research. Quantitative research is all about quantity. With more participants, you can generate more useful and reliable data you can analyze. In turn, you’ll have a clearer understanding of your research problem. This means that quantitative research can often involve gathering data from thousands of participants through an A/B test, or with 30 through a card sort. Read more about the right number of participants to gather for your research.

Mixed methods research

While there are certainly times when you’d only want to focus on qualitative or quantitative data to get answers, there’s significant value in utilizing both methods on the same research projects.Interestingly, there are a number of research methods that will generate both quantitative and qualitative data. Take surveys as an example. A survey could include questions that require written answers from participants as well as questions that require participants to select from multiple choices.

Looking back at the earlier example of how people move from a free plan to a paid plan, applying both research approaches to the question will yield a more robust or holistic answer. You’ll know why people upgrade to the paid plan in addition to how many. You can read more about mixed methods research in this article:

Where to from here?

Now that you know the difference between qualitative and quantitative research, the best way to build confidence is to start testing. Hands-on experience is the fastest path to deeper insight. At Optimal, we make it easy to run your first study, no matter your role or research experience.

Learn more
1 min read

5 Signs It's Time to Switch Your Research Platform

How to Know When Your Current Tool Is Holding You Back

Your research platform should accelerate insights, not create obstacles. Yet many enterprise research teams are discovering their tools weren't built for the scale, velocity, and quality standards that today’s product development demands.

If you're experiencing any of these five warning signs, it might be time to evaluate alternatives.

1. Your Research Team Is Creating Internal Queues

The Challenge: When platforms limit concurrent studies, research becomes a first-come-first-served bottleneck and urgent research gets delayed by scheduled projects. In fast-moving businesses, research velocity directly impacts competitiveness. Every queued study is a delayed product launch, a missed market opportunity, or a competitor gaining ground.

The Solution: Enterprise-grade research platforms allow unlimited concurrent studies. Multiple teams can research simultaneously without coordination overhead or artificial constraints. Organizations that remove study volume constraints report 3-4x increases in research velocity within the first quarter of switching platforms.

2. Pricing Has Become Unpredictable 

The Problem: When pricing gest too complicated, it becomes unpredictable. Some businesses have per-participant fees, usage caps and seat limits not to mention other hidden charges. Many pricing models weren't designed for enterprise-scale research, they were designed to maximize per-transaction revenue. When you can't predict research costs, you can't plan research roadmaps. Teams start rationing participants, avoiding "expensive" audiences, or excluding stakeholders from platform access to control costs.

The Solution: Transparent, scalable pricing with unlimited seats that grows with your needs.  Volume-based plans that reward research investment rather than penalizing growth. No hidden per-participant markups. 

3. Participant Quality Is Declining

The Problem: This is the most dangerous sign because it corrupts insights at the source. Low-quality participants create low-quality data, which creates poor product decisions.

Warning signs include:

  • Participants using AI assistance during moderated sessions
  • Bot-like response patterns in surveys
  • Participants who clearly don't meet screening criteria
  • Low-effort responses that provide no actionable insight
  • Increasing "throw away this response" rates in your analysis

Poor participant quality isn't just frustrating, it's expensive. Research with the wrong participants produces misleading insights that derail product strategy, waste development resources, and damage market positioning.

The Solution: Multi-layer fraud prevention systems. Behavioral verification. AI-response detection. Real-time quality monitoring. 100% quality guarantees backed by participant replacement policies. When product, design and research teams work with brands that offer 100% participant quality guarantees, they know that they can trust their research and make real business decisions from their insights. 

4. You Can't Reach Your Actual Target Audience

The Problem: Limited panel reach forces compromises. Example: You need B2B software buyers but you get anyone who's used software. Research with "close enough" participants produces insights that don't apply to your actual market. Product decisions based on proxy audiences fail in real-world application.

The solution: Tools like Optimal that offer 10M+ participants across 150+ countries with genuine niche targeting capabilities. Proven Australian market coverage from broad demographics to specialized B2B audiences. Advanced screening beyond basic demographics.

5. Your Platform Hasn't Evolved with Your Needs

The Problem: You chose your platform 3-5 years ago when you were a smaller team with simpler needs. But your organization has grown, research has become more strategic, and your platform's limitations are now organizational constraints. Platform limitations become organizational limitations. When your tools can't support enterprise workflows, your research function can't deliver enterprise value.

The Solution: Complete research lifecycle support from recruitment to analysis. AI-powered insight generation. Enterprise-grade security and compliance. Dedicated support and onboarding. Integration ecosystems that connect research across your organization.

Why Enterprises Are Switching to Optimal

Leading product, design and research teams are moving to Optimal because it's specifically built to address the pain points outlined above:

  1. No Study Volume Constraints: Run unlimited concurrent studies across your entire organization
  2. Transparent, Scalable Pricing: Flexible plans with unlimited seats and predictable costs
  3. Verified Quality Guarantee: 10M+ participants with multi-layer fraud prevention and 100% quality guarantee
  4. Enterprise-Grade Platform: Complete research lifecycle tools, AI-powered insights, dedicated support

Next Steps 

If you're experiencing any of these five signs, it's worth exploring alternatives. The cost of continuing with inadequate tools, delayed launches, poor data quality, limited research capacity, far outweigh the effort of evaluation.

Start a Free Trial – Test Optimal with your real research projects

Compare Platforms – See detailed capability comparisons

Talk to Our Team – Discuss your specific research needs with Australian experts

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