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AI-powered UX data analysis for designers and PMs

"We did user research... but is this result truly representative of all users?" If you're having this concern, pay attention! We will show you exactly how to add persuasiveness to your designs based on data. ✅ We explain complex statistical terms in the simplest way possible. ✅ We select only the 3 core hypothesis tests essential for UX practice and introduce them thoroughly, from principles to hands-on practice. ✅ We show you how to easily analyze user data using AI—with zero cost and no hallucinations.

14 learners are taking this course

Level Basic

Course period Unlimited

Statistics
Statistics
Service Planning
Service Planning
UX Research
UX Research
DDD
DDD
data-analysis
data-analysis
Statistics
Statistics
Service Planning
Service Planning
UX Research
UX Research
DDD
DDD
data-analysis
data-analysis

What you will gain after the course

  • Ability to select data analysis methods that align with research objectives

  • How to validate design hypotheses based on data

  • Practical UX data analysis skills using AI



Practical
AI-based UX Data Analysis for immediate use



I did some user research, but...
Is this result really representative of all users?

Have you ever felt uncertain after conducting research because of these concerns?
Now, learn how to add persuasiveness to your designs based on data!





What you'll learn 🔍



Section 1 - Essential UX Basic Statistics: Carefully Selected Core Concepts

We have carefully selected only the essential statistical concepts for UX design and will explain them to you in an easy and detailed manner.

You can understand 5 essential terms that have been confusing, such as P-value and significance level,
and build a solid foundation
for UX statistics.



Section 2 - Increasing Design Persuasiveness with Statistics

Even for the same A/B test, you should use the Chi-square test for click-through rates and the T-test for changes in dwell time?!

You can learn how to select research methods suitable for various situations and discover how to increase the persuasiveness of design decision-making through hypothesis testing, which is most frequently used in actual UX research.


Section 3 - AI-Based Practical UX Data Analysis

If you've been wondering how to perform accurate data analysis using AI without hallucinations, pay attention!

We will teach you everything from the format of organizing research results to how to perform T-Tests, ANOVA, and Chi-square tests quickly and efficiently using AI.







4 key points packed exclusively into this lecture!



Point 1. Easy and friendly visual materials

Statistical terms that are difficult to understand no matter how many times you hear them.
To ensure you never get confused again,
I have carefully prepared visual materials
that break down concepts into small, digestible pieces.

Point 2. Complete the course in just 1.5 hours, over 3 days of commuting!

The time required to complete the course is only 1.5 hours!
Invest just 3 days of your 30-minute commute
to finish UX statistics;
we've prepared it compactly.


Point 3. A lecture strictly for PMs and designers

There are many lectures that teach statistical analysis,
but it was hard to find a statistical analysis lecture specifically for UX, wasn't it?
We have selected and will teach you only the essential core concepts
necessary for UX design.


Point 4. AI data analysis know-how without hallucinations

Were you worried because AI analyzes things however it wants, and statistical tools like SPSS are
expensive and unfriendly?
I will show you how to analyze data accurately
using AI without hallucinations.





Created for people like this



✔️ UX/UI designers who want to do data-driven design

  • Those who want to add persuasiveness to design decision-making based on data

  • Those who want to easily understand only the core concepts of difficult statistics needed for UX design


✔️ PMs/POs who want to properly understand user data for service improvement

  • Those who want to enhance product planning based on quantitative evidence

  • Those who want to establish and verify data-driven hypotheses for service improvement


✔️ Anyone interested in UX data analysis

  • Those who have been curious about statistical terms and hypothesis testing used in product data analysis, such as p-value and null hypothesis.


  • Those who want to gain trustworthy AI-based UX data analysis know-how without hallucinations


Notes before taking the course

  • Hands-on Environment: AI-based practice sessions will be conducted in a web environment without the need for additional program installation.

  • Learning Materials: Example data required for the practice sessions will be provided.


Recommended for
these people

Who is this course right for?

  • UX/UI designers who want to validate design decisions with data

  • PMs/POs who want to advance product planning with quantitative evidence

  • Practitioners who want to quickly finish UX data analysis using AI

Need to know before starting?

  • Anyone can do it as long as they are interested in UX data analysis! 👀

Hello
This is commdelab

Spent 6 years as an in-house brand marketer, then pivoted to become a 4th-year product designer!

Currently pursuing a Master's degree in HCI Design at Yonsei University

I know better than anyone the strengths a designer who started as a non-major can possess.

I will generously share the know-how you need to become a planner or designer who remains essential even in the age of AI!

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