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The Core of Data Experimentation Culture: A/B Testing [Monthly Datarian Seminar Replay | November 2022]

If you were curious about what A/B testing is and how other companies experiment, attend this November seminar!

(5.0) 5 reviews

183 learners

Level Beginner

Course period 12 months

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Reviews from Early Learners

Reviews from Early Learners

5.0

5.0

Jang Jaehoon

100% enrolled

Thank you for the good lecture!

5.0

김하제

100% enrolled

I was able to grasp the concept of A/B testing without any burden. I recommend it if you are curious about the practical experience of A/B testing!

5.0

윤엑스

67% enrolled

I heard it well

What you will gain after the course

  • A/B test concept

  • Practical A/B Testing Cases

📍Notice

  • This course will be converted to a free course starting Monday, June 2, 2025. Please note this before paying for the course.
  • For inquiries, please click the 'Contact Us' button at the bottom right.

Cumulative number of applicants: approximately 2,600!
Watch the hotly debated seminar in video format.

📢 Please check before taking the class!

  • This lecture is a recorded video of the live seminar “The Core of Data Experimentation Culture: A/B Testing” held in November 2022.
  • Includes replies to real-time chat that comes up during the live presentation.

In November we're talking about A/B testing!
Monthly Datalian Seminar 🎤


Datalian Seminar in November is 🔍

I recommend this to those who are having these concerns

  • A/B testing, I've seen it a lot in job postings, but I'm curious about what it is exactly.
  • Anyone who wants to hear about practical A/B testing cases
  • Anyone who wants to know about tips and precautions when conducting practical A/B testing
  • For those of you who are curious about what the Carrot Market planners are thinking about between intuition and A/B testing

📺 In December, we'll be talking about data analytics side projects!


November Seminar Timeline

#1 - The Core of a Data Experimentation Culture: A/B Testing

✔ " The story of a PM who failed after trusting only his intuition and making a fuss"

  • Speaker Demi - Carrot Market Search Product Manager / Data Analyst, then transitioned to Product Manager. I love getting to know users and improving product experiences based on data and experiments.

Carrot Market is a place that puts a lot of effort into doing A/B tests well. We are constantly thinking about how to create an environment where experiments can be conducted well and how to utilize them well. I used to be someone who would talk a little about such things, but embarrassingly, I overlooked it when I was making decisions and got in big trouble. I will tell you my story of how I suffered when I distributed without conducting experiments.

" A/B testing stories that are useful to know "

  • Speaker Seonmi Yoon - Datarian Data Analyst / Worked as a data analyst at Coupang, Hi-Connect, and Kakao, and is currently working at Datarian in data analysis consulting and education.

A basic explanation of what A/B testing is,
- The more experimental data, the better?
- I tried the test, but what should I do if there is no difference in the indicators between Group A and Group B?
- I started testing and the indicator went up a lot and then started dropping. Is there something wrong?
Let's talk about some miscellaneous practical A/B testing stories that are useful to know.

#2 - Q&A

  • Live Q&A with live webinar attendees
Expand the pre-questions answered in Part 2 💬

Warm up

Q1. What is the difference between the data analysis work of a PM and the analysis work of a data analyst?

Ⅰ. A/B test design

Q2. What are the criteria and methods for selecting A/B test cases among many cases?

Q3. What target indicators do you set when designing A/B tests?

Q4. How should I determine the sample size?

Q5. How should I conduct A/B testing when there are few users?

Q6. How do I set the A/B test period?

Ⅱ. Interpreting A/B test results

Q7. When analyzing A/B test results, to what extent do you consider it a success/failure?

Q8. Please give me some tips for analyzing results and common mistakes!

Ⅲ. Other questions

Q9. Many companies ask or require experience with A/B testing. However, in an environment where it is practically impossible to gain experience with A/B testing, what kind of experience can replace this?

Q10. I am a planner. I need to convince designers and developers to do A/B testing. What would be an effective method?


November Seminar
About the participants 📖

Moderator Lee Bo-min

I used to work as a data analyst at the recruitment platform Jobplanet, and now I work at Datalian. My hobby is writing resumes, and my specialty is data analysis.

Demi Part 1 Speaker

I started out as a data analyst and then transitioned to Product Manager. I am now working as a search Product Manager at Carrot Market. I like getting to know users and improving product experiences based on data and experiments.

Yoon Seon-mi Part 1 Speaker

After working as a data analyst at Coupang, Hi-Connect, and Kakao, I am currently working at Datalian, providing data analysis consulting and training.

Bae Ye-seul panel

After working at a food e-commerce startup, I now work as a data analyst at Carrot Market.


Expected Questions Q&A 💬

Q. When is the monthly Datalian Live Seminar? Where can I apply?

You can check out the next month's seminar information on the Datalian website . You can also apply right away!

Q. Is there anything I need to prepare before listening?

No :D Anyone can hear it!

Q. Can I view the slides you used in the seminar separately?

Please check the slides at the link below!
November Seminar Slides: http://bit.ly/3V6D41X


Live participation review
If you're curious 👏

What was the most impressive thing you learned during the seminar?

  • It was great that Carrot Market practitioners shared their experiences and various perspectives on problematic situations they encountered.
  • Part 1 of the lecture on the failed story! It was so much fun. And I really liked the examples you gave in your explanation of A/B testing.
  • I was impressed by how A/B testing was more about business than statistics!
  • What I particularly remember is the part about collecting and analyzing data to understand current users, and having the courage to apply intuition based on that.
  • The content on the Peeking Problem was something I had been thinking about while working on a project recently, so it really resonated with me and was fun!
  • I remember that experiments aren't about success or failure, but rather what insights you gain.
  • It was great to hear the perspectives of both data analysts and PMs at the same time.
  • What impressed me was that experiments go beyond piecemeal product improvements and are a factor in influencing the direction in which the team works!
  • I was impressed by the part where you explained the steps to consider and what to do in each A/B test, from the execution preparation stage to the result interpretation stage.
  • In the second Q&A, it was impressive that you said that when it is realistically difficult to do A/B testing at a company, it is good to appeal by saying, "I did it this way and up to this extent." I thought that A/B testing had to be done according to the procedure unconditionally to be recognized.
  • I liked the story about the guy who convinced his team members to do an experiment! I also liked the methodology for deciding on the sample size.
  • I liked the explanations of why you should look at data and do A/B testing, and the mindset you should have.
  • It was really fun to hear the detailed practical story. As a designer, I was learning data analysis because I was thirsty for data, and it was so interesting that I wanted to learn quickly and go to work.😊😊
  • It was good to see specific examples of how Carrot Market applied it in practice. I think the Sunshining culture of failure is good content that I can apply to my company as well.
  • I was impressed by the reminder that the results we get from A/B testing are not permanent and have a clear expiration date!

A word to Datalian!

  • This time, as we are launching a new service, I had a lot of concerns about 'what should we track and what should we improve?' and I think I'm finally getting the answers. I'm very satisfied with the feedback!
  • I first came across the Datalian seminar through the CEO's recommendation, and I really liked the fact that they held seminars on various topics every month! I would like to attend seminars and camps often in the future! Thank you for providing such a great opportunity :)
  • The seminar content was very informative and the way it was conducted was clean and good! Thank you for your hard work :)
  • I liked the stories from real life experiences and the way you tried to explain things in an easy-to-understand way!
  • Thank you for your hard work in preparing for this seminar. I feel like I have found some more clues to the difficulties I am currently experiencing.
  • I always enjoy listening to the seminars and I feel like my knowledge about the data industry is broadening!
  • Thank you so much for hosting and continuing the data analysis seminar, and I always support you. The lecture content is really helpful every time. Datalian, fighting!
  • I'm not a data expert, but I'm listening carefully. Thank you!
  • I hope to see you at many more great seminars in the future! I hope to see you at your current position.
  • I always cheer for Datalian, who always watches well and provides very useful information to those who are interested in data!
  • I just found out about Datalian and it was very informative. I will participate in topics that interest me often :)
  • I am always learning and improving by attending Datalian seminars! Thank you always for the great seminars and passion.
  • The quality and level of the content was so good that I learned a lot and it motivated me to further develop myself.
  • Thank you for preparing a data analysis seminar with in-depth topics every month :)
  • I am learning a lot from you always organizing informative seminars!
  • It's a continuously evolving seminar, so I like that I can continue to learn and gain a lot of insights.
  • This seminar was more informative because it covered topics that are not easy to hear. Please continue holding seminars in the future!

Monthly Datalian
Watch the last seminar together 📺


Recommended for
these people

Who is this course right for?

  • A/B testing, often seen in job postings. For those curious about exactly what it is.

  • Those who want to hear about practical A/B test cases

  • For those who want to know tips and precautions when conducting practical A/B tests

  • People curious about what a Danggeun Market planner thinks between intuition and A/B testing.

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6 lectures ∙ (1hr 57min)

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  • rlaekdud9229294님의 프로필 이미지
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    • jjhgwx님의 프로필 이미지
      jjhgwx

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      Thank you for the good lecture!

      • hajekim님의 프로필 이미지
        hajekim

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        I was able to grasp the concept of A/B testing without any burden. I recommend it if you are curious about the practical experience of A/B testing!

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          yunxxxui

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          I heard it well

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