Research Foundations
Introduction
It is impossible to describe what you do as UX and product design if you do not include users in your workflow. Users are included through research. Research is the backbone of great product design, providing the insights that inform every decision, from initial concept to final launch. It's about understanding user needs, behaviors, and pain points to create products that truly resonate. By diving deep into user research, you can uncover hidden opportunities, validate assumptions, and make data-driven decisions that lead to exceptional user experiences.
The UX planning phase is all about understanding what you have been asked to do and working out the best combination of activities that will give you the outcome you need, within the time, budgetary, and resource constraints of the project. It is your job as a UX professional to deliver the best user experience within the time and budget available. The key principle for all UX projects is that you must ensure that you involve users in the design process in some way.
You need to include activities which answer the following questions:
What are the business requirements?
Why is the project going ahead?
What would make the project a success?
Is there a project brief which outlines:
A description of the project
Business goals, objectives, and expected outcomes
Target audience
Brand guidelines
Key stakeholders
Expected timings
Technology constraints
Related activities
Kick-off meetings
Stakeholder Interviews
Requirements workshops
The advantages of using a UX approach
Better products
Cheaper to fix problems
Less risk
Deliver to deadline and avoid scope creep
Research brings insights
Products that are easy to use make more money
User led projects can get products to market more quickly
Ease of use is a common customer requirement
The RDTI “Research Design Test Iterate” circle
Product designers should consult the end user of the product as often as possible. There is a circle of user research to design to research and design again. This is an iterative process and the design should change over time to reflect the knowledge gained from the research which each successive iteration being better than the last.
To find the right UX methods for discovery, ideation, and testing, alongside other useful product design resources check out the sister site to Design Manager Hub, Product Design Reference.
Generative vs. Summative
There is a fundamental difference between generative and summative research. One means to find problems to work on, while the other means to make sure the solution really solves the problem.
Generative Research
Identifying Problems and Opportunities.
Generative research, also known as exploratory research, serves as the foundation of the design process. Its purpose is to uncover problems, needs, desires, and opportunities that are often unarticulated by users. This type of research is essential in the early stages of product development, as it helps to identify what problems are worth solving and who the target audience is.
Techniques like user interviews, ethnographic studies, diary studies, and focus groups allow researchers to gather insights into user behaviour, motivations, and pain points. The insights derived from generative research help shape the product’s direction, ensuring it is built on a deep understanding of user needs. The end result is a clearer roadmap of where to focus design and development efforts.
For example, when a UX team begins exploring how to improve the shopping experience for an e-commerce platform, generative research might reveal that users struggle with decision fatigue due to an overwhelming number of product choices. This insight would guide the design team to address this problem.
Summative Research
Validating Solutions.
Summative research, on the other hand, comes into play after a solution has been proposed or developed. Its main purpose is to ensure that the product or feature truly addresses the problems uncovered during the generative research phase. It focuses on evaluating the effectiveness and success of the solution through methods like usability testing, A/B testing, and surveys.
This type of research helps measure how well the solution works, whether users can complete tasks effectively, and whether the product meets business goals. Summative research is critical in refining and optimising the design, ensuring that it delivers the intended value to users.
Using the earlier e-commerce example, after designing a streamlined product selection process, summative research might involve testing the new feature with users to assess whether it reduces decision fatigue and improves the overall shopping experience.
The Symbiosis of Generative and Summative Research
While generative research focuses on problem identification and understanding, and summative research centres on solution validation, the two methodologies are not isolated. They form a symbiotic relationship, each building on the other to create user-centred designs. Generative research provides the insights necessary to guide design, while summative research ensures that the design addresses the problems effectively.
In UX design, both research types are the responsibility of the UX professional, who must navigate the entire lifecycle of a product. By embracing both approaches, UX teams can create products that not only solve real user problems but also deliver a seamless and meaningful experience.
Conclusion
The duality of generative and summative research highlights the importance of a holistic approach to UX. Without generative research, the design team might tackle the wrong problems. Without summative research, the solution might fall short in practice. Together, they form the backbone of a user-centred design process, ensuring that both the problems and the solutions are well understood and validated.
Is Summative Research the Same As Testing?
Summative research and testing are closely related but not exactly the same thing. Summative research is a broader concept that includes various forms of evaluation, of which testing is just one method. In essence, testing is one method used in summative research to gather feedback, but summative research itself can involve other evaluative approaches, depending on the product or solution being assessed.
Summative Research: As a general term, summative research refers to the evaluation phase that occurs after a solution is developed. Its aim is to determine how well a product or feature meets the goals and solves the identified problems. It encompasses multiple methods, such as:
Usability Testing: Direct testing of how users interact with the product.
A/B Testing: Comparing different versions of a design to see which performs better.
Surveys and Questionnaires: Collecting feedback from users to gauge their experience and satisfaction.
Analytics and Performance Metrics: Reviewing quantitative data to assess how users are engaging with the product.
Testing: This is a more specific activity, typically involving users performing tasks with a prototype or product to identify usability issues, validate assumptions, and refine designs. Testing is a key component of summative research, but it doesn’t cover the full spectrum of summative evaluation methods.
Attitudinal vs. Behavioral
Attitudinal research gathers self-reported data from participants by asking questions about their thoughts, feelings, and opinions about a product or service whereas behavioral research involves directly observing user interactions with a product, providing data on user behavior.
Quantitative vs. Qualitative
Quantitative research relies on numerical data and statistical analysis, while qualitative research focuses on non-numerical data such as interviews, observations, and open-ended responses.
Empirical Validation
"Empirical" and "Empirical Validation" are often terms used in research. "Empirical" basically means "based on real-world evidence." When we talk about "empirical validity," we're checking if something is true by looking at real-world data. This is different from "logical validity," which is about whether something makes sense in theory.
Imagine you want to know if eating chocolate makes you smarter.
Empirical Validity
Observation and Experiment: You could do an experiment. You'd get a group of people, give half of them chocolate every day, and the other half nothing. Then, you'd test their intelligence. If the chocolate group scores higher, that's empirical evidence. It's based on real-world observation and testing.
Real-world Examples: Scientists use this method all the time. They test new medicines, study how plants grow, or analyse how people behave in different situations. It's about gathering data and drawing conclusions from that data.
Logical Validity
Reasoning and Logic: You could argue, "Chocolate is delicious, and smart people like delicious things. Therefore, eating chocolate makes you smarter." This sounds logical, but it's not based on real-world evidence. It's just a way of reasoning.
Everyday Examples: We use logical reasoning all the time. "If it's raining, I'll get wet." That's a logical statement, but it doesn't mean it's always true. You might have an umbrella.
Key Difference
Empirical: Based on real-world evidence, experiments, and observations.
Logical: Based on reasoning and thinking, but not necessarily on real-world evidence.
So, while logical reasoning can help us think critically, empirical research gives us the concrete evidence we need to understand the world around us.
Considerations
During user testing, good design often goes unacknowledged
"User test participants will be vocal when things are not as expected. However, good design often goes unacknowledged in testing. Consider a design that meets participants' needs and expresses their understanding of the brand. This design will feel right, and it will flow beautifully. Test participants will simply get on with using it, feeling no need to comment." – Smashing UX Design, Chapter 1, Page 14
Further Reading
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