Skills You’ll Learn
What is product data analysis?
Explore how data analysis is used in the product development cycle.
What is data literacy?
Learn about the pitfalls that are easy to fall into when interpreting data.
What is indicator hierarchy management?
Learn how to design and view indicators that indicate product directionality.
Data visualization
Learn how to present data in the right way of visualizing it.
Improving products through data analysis
Learn how to find patterns and gain insights through cohorts and correlation analysis.
Experiments (A/B testing)
Learn what A/B testing is and what you need to keep in mind.
Causal inference
Learn what causal reasoning is and what guidelines you can use in practice.
The purpose of our analysis of data
It's clear.
“What kind of technology should we draw and what conclusions should we draw to further increase the value of our business?” This is to find the answer to. In an uncertain situation where we need to learn about ever-changing users, How to use data analysis to create more effective productsConcerns about continue.
As interest in data grows, there are many lectures on techniques for dealing with data. However, based on technology A deep view of the product and ways to improveLectures that teach are rare.
▶ Why is it rare?
Because there's no formula.
Since products and business models are all different from company to company and industry, there is no uniform methodology for 'product data analysis'.
▶ Therefore, learning from practitioners who have experienced various domains for many years is the fastest way to learn.
Of product data analysis
Practical insights
It is a PAP that will be distributed in a concentrated manner.
Hello, this is Product Data Analysis Community PAP.
PAP is a product data analysis community created by product analysts, data analysts, and data product owners. It is an abbreviation of Product Analytics Playground, and the intention is to create a space where people can play while comfortably talking about product data analysis.
Five business data practitioners have prepared a product data analysis class along with Class 101 to share with you the insights they have learned while running into each other.
To be able to more widely publicize the role of data that contributes to decision-making in product development,
I hope that the insight into the work we have experienced will help more people in their work.
Product data analysis
Changes that occur when applied to practice
Product data analysis refers to the process of understanding the interaction between users and products through data. It's a framework for putting users at the heart of the business by analyzing user behavior data, identifying conversion opportunities, and creating impactful experiences.
▶ Why product teams should not be aware of data analysis
product data analysis,
I know what's important
If you don't know how to learn.
- How can we grow products through data?
- What are the concerns of other practitioners? What kind of trial and error did you go through, and how did you solve it?
- I'm not a data analyst, but what should I start by thinking about in order to make good use of data in my work?
Super-compressing the experience of 5 practitioners
The most authentic curriculum that has been melted
▶ Class curriculum
Three things that will become your own weapon after attending the course
▶ I recommend it to people like this!
▶ Player knowledge: Ability to use basic Python
Data analysis is sometimes exciting and fun, but it's mostly a headache and a passing day.
I hope that data analysis will be a little more fun while taking this class together.
Curriculum
Creator
PAP
PAP is a product data analysis community created by product analysts, data analysts, and data product owners.
PAP stands for Product Analytics Playground, with the intention of organizing a space where people can comfortably talk about product data analysis and play.
People interested in various topics such as product analysis, metrics, causal inference, experiments, and data visualization come together to produce content. We have a blog, Facebook, and YouTube channel so that more people can lead the data-driven product culture in their own place! 😆
Start product data analysis with 5 business data practitioners
Bo-kyung Choi: Currently working on data analysis for a domestic search portal company. I'm exploring data analysis methodologies that define causal relationships in data. Previously, I was the first data analyst on the Kanda team, an AI-based search app used by 2 out of 3 elementary and middle school students. I personally learned how to define the role of data analysts in product organizations and work better with various job groups.
Park Hye-min: After several startups, I am currently working on data analysis in Kanda. I believe asking good questions is the beginning of a good analysis. I think about what questions to ask and what answers to look for in changes in indicators, believe that the answers are in user data, and think about improving the product.
Kim Sang-hyeon: I work as a data analyst at DataRise. We are creating data products that help e-commerce grow. Even users who are not familiar with data are thinking about ways to easily gain value from data.
Ji-chul Woo: After working for various companies including Kakao, I am currently working as a data lead at DataRise, which creates e-commerce Allinone Growth Solutions. We consider ways for B2B users who are not familiar with data to obtain data-based value easily and quickly.
Lee Min Ho: I started my career as a data analyst, but now I'm working as a product owner creating services so that more people can experience the experience of using data. Currently, DataRise creates data products that help e-commerce grow.
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