User Research Basics

Why Research Before Designing?

The most common reason digital products fail is not bad execution -- it is building the wrong thing. Teams spend months building features users do not want, or solving problems in ways that do not match how users actually think and behave.

User research is the discipline of systematically learning about users: who they are, what they need, how they behave, and what motivates them. It is the foundation of all good product design.

A common objection: "We do not have time for research." The reality: not doing research wastes far more time. Building a feature nobody uses is infinitely more expensive than spending two days researching whether it is needed.

Qualitative vs Quantitative Research

Like data types in analytics, user research falls into two broad categories:

Qualitative Research

Explores the "why" behind behaviour. Rich, descriptive insights from small numbers of participants.

• What it answers: Why do users abandon the checkout? What mental model do users have of how the product works?
• Common methods: User interviews, focus groups, diary studies, usability testing, field observations
• Sample size: 5-10 participants per round is often sufficient (you see recurring patterns quickly)

Quantitative Research

Measures behaviour at scale. Numbers and statistics from large samples.

• What it answers: How many users abandon the checkout? At which step do most users drop off?
• Common methods: Analytics, A/B testing, surveys, clickstream analysis
• Sample size: Hundreds or thousands of responses for statistical significance

Best practice: Use both. Quantitative data tells you what is happening; qualitative research tells you why.

User Interviews: The Most Valuable Research Method

A one-on-one conversation with a user, conducted to understand their experiences, behaviours, and motivations. Done well, a user interview reveals insights no survey or analytics tool can capture.

How to conduct a good user interview:

1. Recruit the right participants Talk to people who represent your actual users, not just whoever is convenient. Use screener questions to filter for relevant characteristics.

2. Prepare a discussion guide List the topics and questions you want to explore. These are not a rigid script -- they are a guide to ensure you cover what you need.

3. Ask open-ended questions "Tell me about the last time you sent money to someone" not "Do you use mobile payment apps?"

Open questions get stories and context. Closed questions get yes/no answers.

4. Follow the user, not your script When something interesting comes up, explore it. "You mentioned it felt frustrating -- can you tell me more about that?"

5. Do not lead or confirm Avoid "So would you say the experience was frustrating?" (leading) Prefer "How would you describe that experience?" (neutral)

6. Observe as much as you listen Body language, hesitations, moments of confusion -- these are often more revealing than words.

Surveys: Reaching Many People at Once

Surveys are useful when you need quantitative data from a large group. They are faster and cheaper than interviews but cannot follow up on interesting answers.

Writing good survey questions:

• Clear and unambiguous: One idea per question
• Neutral language: Avoid implying a preferred answer
• Appropriate scale: Likert scales (Strongly Disagree to Strongly Agree) for attitude questions
• Short: Most respondents abandon surveys over 10 minutes long

Where surveys work well: Measuring satisfaction after a feature launch, understanding demographic distribution, validating findings from interviews at scale.

Usability Testing: Watching Users Use Your Product

Usability testing involves observing real users attempting to complete tasks with your product or prototype.

The five-user rule

Research by Jakob Nielsen showed that testing with just 5 users reveals about 85% of usability problems. You do not need dozens of participants to get actionable insights.

Remote vs in-person testing

• In-person: Richer data, can observe body language, better for early-stage prototypes
• Remote: Tools like Maze, UserTesting, or Zoom allow testing with users anywhere in the world, faster and cheaper

Task-based testing

Give users a realistic task: "You want to view your last three transactions. Show me how you would do that."

Do not say "Find the transaction history screen" -- that tells them what to look for. Let them navigate naturally.

Creating User Personas

A persona is a semi-fictional character that represents a key user segment. It synthesises research insights into a relatable profile that keeps the team focused on real users rather than abstractions.

What a persona includes:

• Name, age, occupation, and a photo
• Goals: What are they trying to achieve?
• Frustrations: What are their pain points?
• Behaviours: How do they currently solve the problem?
• Context: What devices do they use? How tech-savvy are they?

Example persona:

Name: Adaeze, 29
Occupation: Small business owner, sells fabric online and at markets
Goals: Receive payments quickly without asking customers to download new apps
Frustrations: Inconsistent internet connectivity means payment apps sometimes fail during transactions, embarrassing her in front of customers
Behaviours: Uses Opay and bank transfer; prefers Opay for speed but sometimes has to resort to cash
Context: Uses a Samsung mid-range Android phone, primarily on a data plan

Personas are tools for building empathy across the whole team, not just designers.

Research Ethics

User research involves real people sharing their time and experiences. Ethical obligations:

• Informed consent: Tell participants what the research is for and how their data will be used
• Privacy: Store and handle participant data securely
• Anonymisation: Do not share identifying information about specific participants without consent
• Honesty: Do not deceive participants about the purpose of the research
• Right to withdraw: Participants can stop at any time without consequence