By the end of this topic, you should be able to...
distinguish between primary and secondary sources, qualitative and quantitative data and how they are used to identify design opportunities, develop an understanding of users and generate ideas for solutions to problems.
Guiding Question
How do designers approach problem-solving?
Why Does Research Matter in Design?
Imagine you are asked to design a better walking aid for elderly people. Where do you begin? Do you immediately start sketching ideas?
Not quite — not yet.
Before a designer generates a single idea, they must first gather information. This information — called research — is what separates a design that truly solves a problem from one that merely looks good. Research helps designers understand who they are designing for, what problems genuinely exist, and where opportunities for innovation lie.
But not all research is the same. Designers must understand what type of research to use, when to use it, and what it tells them.
Two Types of Research Sources
Research in design comes from two fundamental sources:
Primary Sources
Primary research is information that you collect directly and yourself. It is original, first-hand data gathered specifically for your design project.
Primary research methods include:
Interviews — speaking directly with users, clients, or experts
Surveys and questionnaires — gathering responses from a group of people
Observations — watching how people interact with products or environments
User testing — observing people using existing or prototype products
Focus groups — facilitated discussions with a group of target users
Key characteristic: Primary research is unique to your project. Nobody has collected this specific information before you.
Real-World Example:
When IDEO was commissioned to redesign the shopping cart for a major supermarket chain, their designers didn't sit in an office making assumptions. They went directly to supermarkets and observed shoppers in action — watching how parents managed trolleys with young children, how elderly shoppers struggled with heavy loads, and how people navigated crowded aisles.
This direct, first-hand observation — primary research — revealed design opportunities that no secondary source could have provided.
Secondary Sources
Secondary research is information that has already been collected by someone else. It is existing data that you find, analyse, and apply to your design project.
Secondary research sources include:
Books and academic journals — published research and expert knowledge
Websites and online articles — publicly available information
Product reviews and case studies — analysis of existing products
Government statistics and reports — demographic and social data
Patent databases — existing design solutions and innovations
Anthropometric data — published measurements of the human body
Key characteristic: Secondary research is pre-existing. It was created for a different purpose but can inform your design thinking.
Real-World Example:
When designers at Oxo International were developing new universal design kitchen tools beyond their original Good Grips peeler, they consulted anthropometric data — published measurements of hand sizes, grip strength ranges, and dexterity limitations across different age groups and abilities.
This secondary research provided statistical evidence about the range of human physical capabilities, helping designers set precise dimensions and force requirements for their products without needing to measure every potential user personally.
Two Types of Data
Beyond where research comes from, designers must also understand what kind of information their research produces. All research data falls into two categories:
Quantitative Data
Quantitative data is information that can be measured and expressed as numbers.
Examples include:
"78% of users found the handle uncomfortable"
"The average grip strength of adults over 65 is 24 kg"
"The product was rated 3.2 out of 5 for ease of use"
"45 out of 50 participants could not open the packaging without assistance"
Key characteristic: Quantitative data tells you how many, how much, how often. It is objective and measurable.
Strengths of quantitative data:
Allows comparison across large groups
Produces clear, defensible evidence
Can identify patterns and trends
Limitations of quantitative data:
Does not explain why something happens
Can miss the human story behind the numbers
Qualitative Data
Qualitative data is information that describes qualities, experiences, opinions, and feelings — things that cannot easily be reduced to numbers.
Examples include:
"Users described the handle as feeling like it was 'cutting into' their palm"
"Participants expressed frustration and embarrassment when unable to open the packaging independently"
"Elderly users said the product made them feel 'capable and independent'"
Key characteristic: Qualitative data tells you how people feel, think, and experience. It adds depth and human meaning to design research.
Strengths of qualitative data:
Reveals the emotional and experiential dimension of design problems
Uncovers unexpected insights and needs
Helps designers develop genuine empathy for users
Limitations of qualitative data:
Based on smaller groups — harder to generalise
Can be subjective and open to interpretation
Combining Both: The Complete Picture
The most effective design research uses both quantitative and qualitative data together. Each type answers a different but equally important question:
Data Type | The Question It Answers | Example |
|---|---|---|
Quantitative | How many? How much? How often? | 68% of wheelchair users cannot reach standard supermarket shelves |
Qualitative | Why? How does it feel? What matters? | Wheelchair users describe feeling excluded and frustrated by inaccessible shelf heights |
Together, these two data types give designers a complete understanding of the problem — the scale of the issue AND the human experience behind it.
Real-World Example: Designing the Microsoft Adaptive Controller
Microsoft's research team used both data types when developing their Xbox Adaptive Controller for gamers with limited mobility:
Quantitative data: Research showed that over 33 million gamers in the US alone have some form of disability — a significant market and human need
Qualitative data: Interviews with disabled gamers revealed deep feelings of exclusion and a powerful desire to participate in gaming communities equally
The quantitative data confirmed the scale of the need. The qualitative data revealed the emotional urgency of the problem. Together, they gave the design team both the justification and the human motivation to develop a genuinely inclusive solution.
How Research Is Used in Design
Understanding research types is only valuable if you understand what research is used for in the design process. Research serves three critical purposes:
Identifying Design Opportunities
Research reveals gaps — places where existing products, services, or systems fail to meet people's needs. These gaps are design opportunities.
Example: Secondary research into global ageing populations revealed that by 2030, 1 in 6 people globally will be over 60. This demographic data identified a massive design opportunity for products that support older users — driving the growth of the entire universal design industry.
Developing and Understanding of Users
Research builds empathy and knowledge about the people a designer is designing for — their physical characteristics, behaviours, preferences, frustrations, and aspirations.
Example: When designers at OXO conducted qualitative interviews with arthritis sufferers, they discovered that the problem wasn't just physical pain — users also felt embarrassed and frustrated by their inability to perform simple kitchen tasks independently. This emotional insight shaped the design of Good Grips products to feel empowering and dignified, not clinical or medicalized.
Generating Ideas for Solutions
Research inspires and informs ideation. When a designer deeply understands a problem through research, ideas for solutions emerge more naturally and are more likely to be relevant and effective.
Example: Research by the IKEA design team into how people with cognitive impairments navigate and assemble flat-pack furniture led to the redesign of their instruction sheets — replacing numbered steps with clearer visual sequences and tactile packaging cues. The research didn't just define the problem — it pointed directly toward the solution.
Primary vs Secondary | Qualitative vs Quantitative
Primary Research | Secondary Research | |
|---|---|---|
Definition | Collected by you, first-hand | Already exists, collected by others |
Examples | Interviews, observations, surveys | Books, websites, anthropometric data |
Best for | Understanding your specific users | Understanding broader context and trends |
Qualitative Data | Quantitative Data | |
|---|---|---|
Definition | Descriptive — feelings, opinions, experiences | Numerical — measurements, statistics, counts |
Examples | User interview responses, observation notes | Survey percentages, body measurements, ratings |
Best for | Understanding why and how it feels | Understanding how many and how much |
Key Takeaway
Effective design research uses primary and secondary sources to gather information, and produces both qualitative and quantitative data. Primary research gives designers direct, first-hand insight into their specific users and context. Secondary research provides broader knowledge, statistics, and existing expertise. Qualitative data captures the human experience — feelings, frustrations, and desires. Quantitative data provides measurable evidence of scale and pattern. Together, these research types allow designers to identify genuine design opportunities, develop deep understanding of users, and generate informed, relevant ideas for solutions to real human problems.
Practical Application
Research methods are central to your Internal Assessment (IA) from the very beginning of your project:
Research Type | Your IA Application |
|---|---|
Primary Research | Client interview, user observations, surveys of target users, testing existing products |
Secondary Research | Anthropometric data, existing product analysis, published statistics about your design context |
Qualitative Data | Interview responses, user feedback, observational notes |
Quantitative Data | Survey results, body measurements, product performance measurements |
IA Criteria Connection
Criterion | Research Methods Connection |
|---|---|
Criterion A — Analysis of a Problem | Demonstrates use of primary and secondary research to identify and understand the design problem |
Criterion B — Conceptual Design | Shows how research findings informed and inspired your ideation |
Criterion C — Development of a Prototype | References research data — particularly anthropometric and user data — in design decisions |
Criterion D — Testing and Evaluation | Uses qualitative and quantitative data gathered through user testing to evaluate the solution |
💡Student Tip
In your IA, always explain what your research told you and how it influenced your design decisions. Collecting research is not enough — examiners want to see that your research actively shaped your thinking. Connect your findings directly to your design choices.
Sources
Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 4th ed., SAGE Publications, 2014.
International Baccalaureate Organization. Design Technology Guide. International Baccalaureate Organization, 2014.
Kumar, Vijay. 101 Design Methods: A Structured Approach for Driving Innovation in Your Organization. John Wiley and Sons, 2013.
Martin, Bella, and Bruce Hanington. Universal Methods of Design: 100 Ways to Research Complex Problems, Develop Innovative Ideas, and Design Effective Solutions. Rockport Publishers, 2012.
Cross-reference: B2.1.3 primary research; B2.1.4 secondary research; B2.1.5–B2.1.6 for research outputs.
Linking Questions
What ergonomic considerations are important to be able to engage successfully with the design process? (A1.1)
How do design technology students ensure they engage with user-centred research methods? (A2.1)
To what extent are the goals of the design process aligned with the goals of a user-centred design (UCD) process? (B1.1)
To what extent does the model, test, refine cycle require full engagement with modelling and prototyping at several levels of fidelity? (B2.2)
Which aspects of the design process require engagement with material selection? (B3.1)
How do the requirements of the design process ensure students are addressing the responsibility of the designer? (C1.1)
Why is product analysis and evaluation important in the design process? (C3.1)
To what extent does the design process require the exploration of design for manufacture strategies? (C4.1)