UX Research

• UX research
• Why, when
• Methods (qualitative/ quantitative)
• Interviews, Questionairs, others
• Cognitive bias
• Data analysis
• AI

Agenda

Risk reduction

People don't buy products, they hire them to do the job.

+ Desk research

Methods

What they say

What they do

Quantitative

Qualitative

If I had asked people what they wanted, they would have said faster horse

-Henry Ford

Interviews

What can we learn?

• A deeper understanding of the customer

• Who are they? Goals and needs

• Personas, segments

• Mental models

• How do they think about this? What do they expect?

• Customer journey

• What are their processes?

• How do they use it?

Opportunities

• What are they missing?

• What makes them angry?

• What is important to them?

What we cannot

• Future behaviour (I would pay...)

• Quantification

Interviews

• Structured - rigid, script, easy to compare data (basically a moderated survey)
• Unstructured - free-flowing
• Semi structured - script but ability to deep dive into topics

Types of questions:

• Sequence: "Tell me about your day."

• Specific example: "Tell me about the last time you bought shoes."

• Detailed list: "Tell me all the apps you use."

• Also ask about feelings: "How did that make you feel?" or "What feelings came up for you?"

Active listening techniques

Active listening techniques

Techniques

• Paraphrasing: Restating what the other person has said in your own words to show you've understood.
• Mirroring: Repeating the last few words or key phrase the person said to encourage them to elaborate.
• Silence: Pausing to give the other person time to think and speak.
• Unfinished questions: Starting a sentence and leaving it open-ended to prompt the other person to complete the thought (e.g., "You mentioned the meeting was...").
• Boomerang: Turning a question back to the person who asked it (e.g., "How is this supposed to work?" becomes "What do you think?").
• 5 whys vs. no whys

Tips and tricks

• Establish a relationship of trust and respect

• Use open-ended questions

• Nodding and affirming

• Active listening

• Inquiring and probing

• "Why" (but use a different word)

• Always return to the topic

• Replace "typically" with "the last time you"

• Don't judge or comment

• Don't explain

• Don't lead (no leading questions)

• Don't interrupt

• Don't use closed-ended questions

• Don't use double-barreled questions

• Don't use hypothetical questions

Cognitive biases

Data analysis

Fictive typical representative  of the user segment

Goal is to build an empathy and focus

Personas

Personas should not be about demographics. They should be about the problems and challenges people face

• Born 1948, grew up in England
• Likes dogs
• Male
• Married twice
• 2 kids
• Wealthy and famous
• Lives in a castle

Persona 1

• Born 1948, grew up in England
• Likes dogs
• Male
• Married twice
• 2 kids
• Wealthy and famous
• Lives in a castle

(jtbd)

When (situation), a user needs to..., so they can...
 

Persona: Mark, 24, a university student, stays up late at night, likes latenight coffee.

Story: When studying late at night, Mark wants to stay focus and productive longer, so he can finish his paper.

User story

Visual representation of the entire process a customer goes to when interacting with company, product service.

Customer journey maps

• Identify insights, topics
• Define problems (with context)
• Prioritisation (e.g. MoSCoW)

And now what?

AI in discovery research

• Research preparation
• Data gathering (transcripts, synthetic research)
• Analysis and summary 
• Visualisation (Persona creation, mind maps)

Activities

• Claude, CHatGPT
• Gemini gems
• Dovetail, Notebooklm,
• EnjoyHQ, Quadrilics

Tools

Notebooklm - interface

Notebooklm

- mind map