Data Analysis 101:
A Basic Guide to Take the First Step of UX Analysis
Data-Driven UX: A Step-by-Step Approach To Take the Fear Out of Data Analysis
Data-Driven UX is defined as a data-based decision-making process
rather than relying on guesswork of former experience.
This book is a basic guide to take the first step of UX analysis.
For those of you who want to analyze your data,
but don't know how to get started,
this book guide you with a practical methodology for understanding and interpreting UX data.
An overall guide for user behavior analysis is provided as well as key metrics for UX analysis.
It also discusses how to share the outcome of your UX strategy based on data within your organization.
About the Author
4Grit strive to popularize UX.
As a developer of Beusable and Beusable Analytics,
4Grit leads the field of machine learning-based UX big data solutions.
We give concrete shape to UX with big data,
to help better understand and generalize Data-Driven UX analysis.
Limitation of the Book
As all the illustrated examples of this book have been the service, developed and operated by 4Grit, it may look like we are advertising our service.
This book covers about data analytics that is specific to customer experience, called CX. As it deals with the specific category of data analysis, the contents have been limited to the user data analysis.
For the last, we are a novice publisher.
We published the book from scratch, from registering the publishing business to carrying out all the publishing matter.
For these reasons, the result may not be perfect, but we hope this may help readers to better understand UX data analysis.
Yet, the Reason Why We Published the Book
The concept of UX is still hard to grasp needless to say the concept of big data. This book even adds to the recklessness of linking the two. And interestingly, the outcome is the opposite. Based on the ambiguity and subjectivity of user individuality, UX can be shaped by meeting big data, and UX can be easily handled, making it more practical and feasible.
It's not easy to handle data. Because a series of activities that collect and compute data to find meaning requires an understanding of the data. In order to lower the hurdle of data analysis, this book uses a visualization technique called Heatmap, which is intuitive to understand, to help you get started with it. These customer behavior heatmaps are provided in ‘Beusable’ and similar analytics tools, so once you've learned how to read them, you can apply to other types of heatmaps.
4Grit is developing big data solutions while consulting on UX Big Data at the same time. Through the heatmap, the actual for-profit business of "data analysis" has led to success as well as our methodology for data analysis. And to generalize the field of data analytics, we wanted to share our trial and error with the technology assets.
Table of Contents
Chapter 1 - Basics to Start Data Analysis
- Understanding the Background of Data-Driven UX
- Advantages of Designers Who Can Handle Data
- Mindset Before Starting Data Analysis
- Misunderstandings About Data
Chapter 2 - Understanding the Data Analysis Process
- Understanding Data-Based UX Design Process
- Understanding the Data Analysis Process
- Setting a Goal of Data Analysis
- Another Name with Quantification of the Target, Kpi
- Prioritize and Implement Improvement Measures
Chapter 3 - Understand Basic UX Data Analysis Terminology
- Understand UX Information from Your Data
- Five Things to Consider in the Analysis of Numerical Indicators
- Data Analytics Tools for UX Designers
- Understanding Key Indicators and Terms
Chapter 4 - Analyzing User Behavior with Heatmap Data
- Understanding Heatmaps
- Basic Click Analysis
- Advanced Click Analysis
- Scroll Analysis
- Cross-Analysis of Scroll Data
- Analyze Average Fold to Improve Service
- Analyze Fold to Improve UX Design
- Sequential Analysis of User Navigation with Stream
Chapter 5 - Getting Started with Advanced Analysis
- Understanding the Inflow Channel
- Call to Action (Cta) Analysis
- Funnels Analysis
- Individual User Behavior Analysis
Chapter 6 - Data Analysis, Putting Theory in Practice
- Analyze Why Certain Content Is Not Being Consumed
- Discover Where to Improve to Increase Conversion Rate
- Measure If the Page Has Been Delivered as Designed
- Discover the Issues Where User Feel Uncomfortable
- Discover How to Improve in GUI to Increase Conversion Rate
- Analyze the User Navigation Flow
- Analyze Factors and Causes That Fail to Achieve the Purpose of the Website
- Discover User's Pain Points and Cause
- Analyze User's Navigation Flow and Needs of Each Device
- Creating a Data-Based Persona
- Setting up a Data-Based User Journey Map
- Heuristic Evaluation: Synergistic Effect with UX Data Analysis
Chapter 7 - Verification of the Improvement Results
- Understanding A/B Testing
- Running A/B Test
- Case Study: Beusable Main Page
- Verification of the Improvement Results with Other Methods
Chapter 8 - Sharing UX Performance Report
- UX Analysis Report
- How to Write Effective Problem-Solving UX Reports
Recommended for those who:
- Service planner, who wants to definitize where and how to improve UX, which directly linked to revenue generation
- Designer, who aims to elevate user experience by improving UI design
- Marketer, who needs to optimize content marketing through quantitative/qualitative user behavior tracking
- CRM manager, who wants to improve performance by analyzing the content and user behaviors that affect customer increase
- Developer, who wants to reduce costs by reproducing bugs and analyzing data
- Sales manager, who wants to discover and analyze the messages/content users respond to
- CS manager, who needs to reduce CS resources by reproducing reported issues
Prof. Lee Ji-hyun (Industrial Design Department at Seoul Women's University)
『Data-Driven UX』 will serve as a map for companies and students who want to adopt data analysis in the online business or study the process of it. It covers the basic concepts to the entire process of data analysis, which can be the handy guide to introduce Data-Driven UX in your organization or to start UX analysis even for those who are not familiar to the subject.
In addition, it provides detailed instructions on how to process Visual In-page Analytics, which has been gaining attention recently. This allows you to derive insights beyond page conversion to analyze the user behavior analysis. Moreover, it details the meaning of the data such as heatmaps, scroll data, stream, fold and CTA(Call to Action) with Beusable solution.
It also introduces specific methods such as Persona, Journey maps, A/B tests, and Analysis reports that companies cannot afford to miss out on to make good use of data. For this reason, I believe this book can be a friendly UX analysis guide for those who have a thirst of UX analysis knowledge.
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