October 5, 2021

What do you prioritize when doing qualitative research?

Qualitative user research is about exploration. Exploration is about the journey, not only the destination (or outcome). Gaining information and insights about your users through interviews, usability testing, contextual, observations and diary entries. Using these qualitative research methods to not only answer your direct queries, but to uncover and unravel your users ‘why’.

It can be important to use qualitative research to really dig deep, get to know your users and get inside their heads, and their reasons. Creating intuitive and engaging products that deliver the best user experience. 

What is qualitative research? 🔎

The term ‘qualitative’ refers to things that cannot be measured numerically and qualitative user research is no exception. Qualitative research is primarily an exploratory research method that is typically done early in the design process and is useful for uncovering insights into people’s thoughts, opinions, and motivations. It allows us to gain a deeper understanding of problems and provides answers to questions we didn’t know we needed to ask. 

Qualitative research could be considered the ‘why’. Where quantitative user research uncovers the how or the what users want. Qualitative user research will uncover why they make decisions (and possibly much more).

Priorities ⚡⚡⚡⚡

When undertaking user research it is great to do a mix of quantitative and qualitative research. Which will round out the numbers with human driven insights.

Quantitative user research methods, such as card sorting or tree testing, will answer the ‘what’ your users want, and provide data to support this. These insights are number driven and are based on testing direct interaction with your product. This is super valuable to report to stakeholders. Hard data is difficult to argue what changes need to be made to how your information architecture (IA) is ordered, sorted or designed. To find out more about the quantitative research options, take a read.

Qualitative user research, on the other hand, may uncover a deeper understanding of ‘why’ your users want the IA ordered, sorted or designed a certain way.  The devil is in the detail afterall and great user insights are discoverable. 

Priorities for your qualitative research needs to be less about the numbers, and more on discovering your users ‘why’. Observing, listening, questioning and looking at reasons for users decisions will provide valuable insights for product design and ultimately improve user experience.

Usability Testing - this research method is used to evaluate how easy and intuitive a product is to use.  Observing, noting and watching the participant complete tasks without interference or questions can uncover a lot of insights that data alone can’t give. This method can be done in a couple of ways, moderated or unmoderated. While it can be quicker to do unmoderated and easier to arrange, the deep insights will come out of moderated testing. 

Observational - with this qualitative research method your insights will be uncovered from observing and noting what the participant is doing, paying particular attention to their non-verbal communication. Where do they demonstrate frustration, or turn away from the task, or change their approach? Factual note taking, meaning there shouldn’t be any opinions attached to what is being observed, is important to keep the insights unbiased.

Contextual - paying attention to the context in which the interview or testing is done is important. Is it hot, loud, cold or is the screen of their laptop covered in post-its that make it difficult to see? Or do they struggle with navigating using the laptop tracker? All of this noted, in a factual manner, without personal inferring or added opinion based observations can give a window into why the participant struggled or was frustrated at any point.

These research methods can be done as purely observational research (you don’t interview or converse with your participant) and noting how they interact (more interested in the process than the outcome of their product interaction). Or, these qualitative research methods can be coupled with an

Interview - a series of questions asked around a particular task or product. Careful note taking around what the participant says as well as noting any observations. This method should allow a conversation to flow. Whilst the interviewer should be prepared with a list of questions around their topic, remain flexible enough to dig deeper where there might be details or insights of interest. An interviewer that is comfortable in getting to know their participants unpicks reservations and allows a flow of conversation, and generates amazing insights.

With an interview it can be of use to have a second person in the room to act as the note taker. This can free up the interviewer to engage with the participant and unpick the insights.

Using a great note taking side kick, like our Reframer, can take the pain out of recording all these juicy and deep insights. Time-stamping, audio or video recordings and notes all stored in one place. Easily accessed by the team, reviewed, reports generated and stored for later.

Let’s consider 🤔

You’re creating a new app to support your gym and it’s website. You’re looking to generate personal training bookings, allow members to book classes or have updates and personalise communication for your members. But before investing in final development it needs to be tested. How do your users interact with it? Why would they want to? Does it behave in a way that improves the user experience? Or does it simply not deliver? But why?

First off, using quantitative research like Chalkmark would show how the interface is working. Where are users clicking, where do they go after that. Is it simple to use? You now have direct data that supports your questions, or possibly suggests a change of design to support quicker task completion, or further engagement.

While all of this is great data for the design, does it dig deep enough to really get an understanding of why your users are frustrated? Do they find what they need quickly? Or get completely lost? Finding out these insights and improving on them can make the most of your users’ experience.

When quantitative research is coupled with robust qualitative research that prioritizes an in-depth understanding of what your users need, ultimately the app can make the most of your users’ experience.

Using moderated usability testing for your gym app, observations can be made about how the participant interacts with the interface. Where do they struggle, get lost, or where do they complete a task quickly and simply. This type of research enhances the quantitative data and gives insight into where and why the app is or isn't performing.

Then interviewing participants about why they make decisions on the app, how they use it and why they would use it. These focussed questions, with some free flow conversation will round out your research. Giving valuable insights that can be reviewed, analyzed and reported to the product team and key stakeholders. Focussing the outcome, and designing a product that delivers on not just what users need, but in-depth understand of why. 

Wrap Up 🥙

Quantitative and qualitative user research do work hand in hand, each offering a side to the same coin. Hard number driven data with quantitative user research will deliver the what needs to be addressed. With focussed quantitative research it is possible to really get a handle on why your users interact with your product in a certain way, and how. 

The Optimal Workshop platform has all the tools, research methods and even the note taking tools you need to get started with your user research, now, not next week! See you soon.

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1 min read

What gear do I need for qualitative user testing?

Summary: The equipment and tools you use to run your user testing sessions can make your life a lot easier. Here’s a quick guide.

It’s that time again. You’ve done the initial scoping, development and internal testing, and now you need to take the prototype of your new design and get some qualitative data on how it works and what needs to be improved before release. It’s time for the user testing to begin.

But the prospect of user testing raises an important question, and it’s one that many new user researchers often deliberate over: What gear or equipment should I take with me? Well, never fear. We’re going to break down everything you need to consider in terms of equipment, from video recording through to qualitative note-taking.

Recording: Audio, screens and video

The ability to easily record usability tests and user interviews means that even if you miss something important during a session, you can go back later and see what you’ve missed. There are 3 types of recording to keep in mind when it comes to user research: audio, video and screen recording. Below, we’ve put together a list of how you can capture each. You shouldn’t have to buy any expensive gear – free alternatives and software you can run on your phone and laptop should suffice.

  • Audio – Forget dedicated sound recorders; recording apps for smartphones (iOS and Android) allow you to record user interviews and usability tests with ease and upload the recordings to Google Drive or your computer. Good options include Sony’s recording app for Android and the built-in Apple recording app on iOS.
  • Transcription – Once you’ve created a recording, you’ll no doubt want a text copy to work with. For this, you’ll need transcription software to take the audio and turn it into text. There are companies that will make transcriptions for you, but software like Transcribe means you can carry out the process yourself.
  • Screen recording – Very useful during remote usability tests, screen recording software can show you exactly how participants react to the tasks you set out for them, even if you’re not in the room. OBS Studio is a good option for both Mac and Windows users. You can also use Quicktime (free) if you’re running the test in person.
  • Video – Recording your participants as they make their way through the various tasks in a usability test can provide useful reference material at the end of your testing sessions. You can refer back to specific points in a video to capture any detail you may have missed, and you can share video with stakeholders to demonstrate a point. If you don’t have access to a dedicated camera, consider mounting your smartphone on a tripod and recording that way.

Taking (and making use of) notes

Notetaking and qualitative user testing go hand in hand. For most user researchers, notetaking during a research session means busting out the Post-it notes and Sharpie pens, rushing to take down every observation and insight and then having to arduously transcribe these notes after the session – or spend hours in workshops trying to identify themes and patterns. This approach still has merit, as it’s often one of the best ways to get people who aren’t too familiar with user research involved in the process. With physical notes, you can gather people around a whiteboard and discuss what you’re looking at. What’s more, you can get them to engage with the material directly.

But there are digital alternatives. Qualitative notetaking software (like our very own Reframer) means you can bring a laptop into a user interview and take down observations directly in a secure environment. Even better, you can ask someone else to sit in as your notetaker, freeing you up to focus on running the session. Then, once you’ve run your tests, you can use the software for theme and pattern analysis, instead of having to schedule yet another full day workshop.

Scheduling your user tests

Ah, participant scheduling. Perhaps one of the most time-consuming parts of the user testing process. Thankfully, software can drastically reduce the logistical burden.

Here are some useful pieces of software:

Dedicated scheduling tool Calendly is one of the most popular options for participant scheduling in the UX community. It’s really hands-off, in that you basically let the tool know when you’re available, share the Calendly link with your prospective participants, and then they select a time (from your available slots) that works for them. There are also a host of other useful features that make it a popular option for researchers, like integrations and smart timezones.

If you’re already using the Optimal Workshop platform, you can use our  survey tool Questions as a fairly robust scheduling tool. Simply set up a study and add in prospective time slots. You can then use the multi-choice field option to have people select when they’re available to attend. You can also capture other data and avoid the usual email back and forth.

Storing your findings

One of the biggest challenges for user researchers is effectively storing and cataloging all of the research data that they start to build up. Whether it’s video recordings of usability tests, audio recordings or even transcripts of user interviews, you need to ensure that your data is A) easily accessible after the fact, and B) stored securely to ensure you’re protecting your participants.

Here are some things to ask yourself when you store any piece of customer or user data:

  • Who will have access to this data?
  • How long do I plan to keep this data?
  • Will this data be anonymized?
  • If I’m keeping physical data on hand, where will it be stored?

Don’t make the mistake of thinking user data is ‘secure enough’, whether that’s on a company server that anyone can access, or even in an unlocked filing cabinet beneath your desk. Data privacy and security should always be at the top of your list of considerations. We won’t dive into best practices for participant data protection in this article, but instead, just mention that you need to be vigilant. Wherever you end up storing information, make sure you understand who has access.

Wrap up

Hopefully, this guide has given you an overview of some of the tools and software you can use before you start your next user test. We’ve also got a number of other interesting articles that you can read right here on our blog.

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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?

With an understanding of qualitative and quantitative user research, the next best step would be to start learning more about the various methods that fall under each of these research approaches and how to actually conduct research effectively.

Here are some of the best articles to read next:

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1 min read

Optimal vs Dovetail: Why Smart Product Teams Choose Unified Research Workflows

UX, product and design teams face growing challenges with tool proliferation, relying on different options for surveys, usability testing, and participant recruitment before transferring data into analysis tools like Dovetail. This fragmented workflow creates significant data integration issues and reporting bottlenecks that slow down teams trying to conduct smart, fast UX research. The constant switching between platforms not only wastes time but also increases the risk of data loss and inconsistencies across research projects. Optimal addresses these operational challenges by unifying the entire research workflow within a single platform, enabling teams to recruit participants, run tests and studies, and perform analysis without the complexity of managing multiple tools.

Why Choose Optimal over Dovetail? 

Fragmented Workflow vs. Unified Research Operations

  • Dovetail's Tool Chain Complexity: Dovetail requires teams to coordinate multiple platforms—one for recruitment, another for surveys, a third for usability testing—then import everything for analysis, creating workflow bottlenecks and coordination overhead.
  • Optimal's Streamlined Workflow: Optimal eliminates tool chain management by providing recruitment, testing, and analysis in one platform, enabling researchers to move seamlessly from study design to actionable insights.
  • Context Switching Inefficiency: Dovetail users constantly switch between different tools with different interfaces, learning curves, and data formats, fragmenting focus and slowing research velocity.
  • Focused Research Flow: Optimal's unified interface keeps researchers in flow state, moving efficiently through research phases without context switching or tool coordination.

Data Silos vs. Integrated Intelligence

  • Fragmented Data Sources: Dovetail aggregates data from multiple external sources, but this fragmentation can create inconsistencies, data quality issues, and gaps in analysis that compromise insight reliability.
  • Consistent Data Standards: Optimal's unified platform ensures consistent data collection standards, formatting, and quality controls across all research methods, delivering reliable insights from integrated data sources.
  • Manual Data Coordination: Dovetail teams spend significant time importing, formatting, and reconciling data from different tools before analysis can begin, delaying insight delivery and increasing error risk.
  • Automated Data Integration: Optimal automatically captures and integrates data across all research activities, enabling real-time analysis and immediate insight generation without manual data management.

Limited Data Collection vs. Global Research Capabilities

  • No Native Recruitment: Dovetail's beta participant recruitment add-on lacks the scale and reliability enterprise teams need, forcing dependence on external recruitment services with additional costs and complexity.
  • Global Participant Network: Optimal's 100+ million verified participants across 150+ countries provide comprehensive recruitment capabilities with advanced targeting and quality assurance for any research requirement.
  • Analysis-Only Value: Dovetail's value depends entirely on research volume from external sources, making ROI uncertain for teams with moderate research needs or budget constraints.
  • Complete Research ROI: Optimal delivers immediate value through integrated data collection and analysis capabilities, ensuring consistent ROI regardless of external research dependencies.

Doveetail Challenges: 

Dovetail may slow teams because of challenges with: 

  • Multi-tool coordination requiring significant project management overhead
  • Data fragmentation creating inconsistencies and quality control challenges
  • Context switching between platforms disrupting research flow and focus
  • Manual data import and formatting delaying insight delivery
  • Complex tool chain management requiring specialized technical knowledge

When Optimal is the Right Choice

Optimal becomes essential for:

  • Streamlined Workflows: Teams needing efficient research operations without tool coordination overhead
  • Research Velocity: Projects requiring rapid iteration from hypothesis to validated insights
  • Data Consistency: Studies where integrated data standards ensure reliable analysis and conclusions
  • Focus and Flow: Researchers who need to maintain deep focus without platform switching
  • Immediate Insights: Teams requiring real-time analysis and instant insight generation
  • Resource Efficiency: Organizations wanting to maximize researcher productivity and minimize tool management

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