Practice! Startup Data-Driven Decision Making [Monthly Datarian Seminar Replay | April 2023]

Monthly Data Analyst Seminar 💡
Check out Monthly Datalian again in April 2023!

Monthly Datalian Seminar
In April, we'll cover data usage cases for startups !

April's Datalian Seminar is 🔍

I recommend this to those who are having these concerns ✅

• Planners, marketers, designers, and other practitioners who want to utilize data in startups
• Performance marketers, growth hackers, and startup CEOs who are wondering how to analyze marketing performance
• If you are curious about how Posttype uses data for decision making
• How are other companies doing it? Anyone who wants to hear about real-world data analysis cases

April Seminar Timeline ⏰

#1 - Measurable Marketing Performance Analysis: How to Use Customer Lifetime Revenue (LTR)

✔ Speaker Kim Min-joo

• Datalian Growth Marketer, Data Analyst
• Former B2B logistics startup SwatchOn data analyst, performance marketer
• Former Co-Founder, COO of shared housing startup Napster
• I learned data analysis to find answers in a world where there are no right answers after starting a business. I worked as a data analyst and now I am working on growing services based on data.

If you had to look at just one metric to measure marketing performance, what would it be?
It may vary depending on the purpose of the marketing campaign, but ultimately, the purpose of the entire business is sales. Since a business can survive only by making sales, we need to check how the users we brought in behave later and whether they generate sales from our service.
In this talk, we'll talk about how to measure marketing performance by comparing marketing costs to the total revenue generated by users on our service.

#2 - Data Analytics from a BizOps Perspective: Useful Data vs. Data That Hurts Business

✔ Speaker Cha Gil-ho

• Post Type Biz Ops Lead
• Former Dong-A Ilbo reporter
• I lead the strategic and operational work related to management at a creator economy startup. I help companies, businesses, and products solve problems they face. I am interested in concisely defining and solving problems that are difficult to standardize through data analysis.

Data analysis is a powerful tool for decision-making and problem solving, but if you are repeating the wrong analysis with the wrong data, it can actually be poisonous to your business. In the field, it is common to unintentionally focus on data that is not related to business growth and try to solve problems.
So, how should we analyze what data to better define the problem and make sound decisions? Let’s think about the best case of business data analysis for decision making through a practical case called ‘Counting the number of active users’.

April Seminar
About the participants 📖

Expected Questions Q&A 💬

Live participation review
If you're curious 👏

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

• I was impressed with the CPA analysis using Google Analytics!
• I was very impressed with the cohort analysis using GA4 and the ability to view data separately.
• I was impressed by the method of calculating LTR with GA4. Startups often have incomplete data, so it was nice to learn how to make decisions even in such situations!
• When covering the LTR analysis, I really liked that you didn't just stop at looking at some indicators, but showed the actual GA4 analysis screen. When I saw the specific screen, which I didn't really understand just by listening to the lecture, I looked at it carefully and thought that I could do it too, and I wanted to try applying it even more.
• It was impressive to see how to estimate CPA for free channels using Fermi estimation when payment data cannot be obtained from GA4.
• I was able to see the indicators together while looking at the GA4 screen, so I thought that I could apply what I learned in this way. It was a time to learn a lot of things I didn't know about because Gilho Choi told me about the methods of accessing data and the problems that can be encountered in practice. It was also fun to learn about a new content platform called Posttype.
• It was great to learn about the methods used in the data analysis field and the concerns that field workers have!
• It was a useful time to learn about the field called BizOps. In particular, it was impressive that even indicators that are used inertially, such as active users, were redefined according to the business and used as useful indicators. In particular, I thought a lot about the attitude I should have in the future, such as the fact that I should look at data unfamiliarly and try not to be biased by first impressions and first thoughts.
• The part about the illusion indicator was the most impressive! It made me think about the indicator again.
• It was nice to be able to indirectly experience a case from the field.
• What struck me was that there is data that is hurting businesses, that is analysis that misses the context and the lines, that has no predictive power, and that cannot be used to make decisions.
• It made me realize that we need to do useful analysis, not just analysis for the sake of analysis.
• There were many practical application points and inspirations from the various KPI examples and cases.
• Although I had heard the term BizOps, I didn't know what it specifically involved. Rather, I found it interesting that it was a job that involved thinking more about how to use data and developing a business than a data analyst.

A word to Datalian!

• Recently, I felt the need for data analysis skills, so I started studying, and I searched for posts on various channels such as Careerly and LinkedIn. Then, I found Datalian. I was surprised by the high-quality materials, including monthly magazines, blog posts, and today's seminar! Thank you so much for preparing so many high-quality materials. I also asked a lot of questions today, and I'm glad you answered most of them. 😊😊 Thank you! I'll see you next month~
• Today's seminar was very useful!
• Thank you always, my precious Datalian!
• Thank you for planning a great seminar.
• I am a statistics student, and it was great to hear about how data is handled in the workplace, which is not covered in detail in class. Also, the materials related to the presentation were posted in the chat window, which helped me understand the presentation.
• I was able to understand more clearly and listen with more interest because you gave me direct examples from real-life situations.
• I think the seminar content will be useful in practice.
• I hope to see many more informative seminars in the future!
• Through the seminar, I realized that there are many things I do not know about data analysts. I am learning a lot about what I need by learning new information through Datalian. Thank you for providing good information. I will work hard so that I can have the opportunity to help Datalian someday :)
• It was nice to be able to hear the stories of practitioners so closely.
• I was able to understand it more quickly because you explained it based on real-life examples.
• Thank you for the great seminar. I received a lot of help from the Datalian seminar, from getting a job to actual work!
• The seminar content was very informative and it was great to be able to hear in detail the experiences and cases of those in the field!
• I think it will be of practical help to many job seekers who are challenging the job of data analysis.
• Thanks for providing insight into data from real-world jobs!
• Thank you for providing such useful information every month~
• I was satisfied with the seminar content, the way it was conducted, and the materials that allowed me to understand the content at a glance.

2023 Monthly Datalian
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