TDP Monthly Talks - A/B Testing Guidelines & Storytelling with Data

We will enforce code of conduct in all our events.
https://twdatany.blogspot.com/2018/03/code-of-conduct.html

Anyone is welcome to TDP's event whether or not you're from Taiwanese communities!

【Event】Taiwanese Data Professionals Monthly
【Time】10/18 (Thu) 6:30 PM - 8:30 PM
【Location】Microsoft Store 6th Floor 677 5th Ave, New York, 10022
【Ticket】https://goo.gl/zCuNoM

【Talks】
“Storytelling with Data”
When it comes to storytelling with data, most people associate it with data visualization, exploratory analysis, presentation, or standard reports with a bunch of charts. However, many times the audiences are either lost in the middle of the presentation, getting confused with the graphs and resulted in no further actions after all the ‘interesting’ findings.
To avoid these situations, the best practice is to tell a story with it. A lot of time we communicate the findings within the data, but it isn’t always so meaningful when there are only data insights. Instead, making data a pivotal point in an overarching story can enable us to guide the audience to what we want them to see and take action on. This talk will discuss how to make a good story that can bring data to life.
Lydia is going to talk about using the appropriate graph for certain contents, directing audience’s thoughts with data visualization designs, and sending the message across by using actual case about consumer journey of products purchasing.

"A/B Testing Guidelines"
A classic A/B testing example you might have heard is changing the color of a button on a website. You randomly show 50% of people the old button, 50% of people the new, and measure the click or purchase rate to see if they improved. Sounds pretty simple right? Why exactly do you need a data scientist to analyze experiments?
Unfortunately, “generating numbers is easy; generating numbers you should trust is hard!” If you’ve been thinking about starting A/B testing at your company, have been doing it for a while but aren’t sure you’re following best practices, or are simply curious, this talk is for you. We don’t assume any level of A/B testing knowledge, statistics background, or programming experience.
We’ll begin with an introduction to A/B testing using actual examples from Etsy and DataCamp. Then we’ll dive into the main part of the talk, covering 10 guidelines for proper A/B Testing. Finally, we’ll end with a list of great resources so you can continue learning.

【Speakers】
Emily Robinson is a Data Scientist at DataCamp, where she works on the growth team building an A/B Testing analytics system. Previously, she was a Data Analyst at Etsy working with their search team to design, implement, and analyze experiments on the ranking algorithm, UI changes, and new features. On her data science blog, hookedondata.org, she writes about topics ranging from managing the business challenges in data science to making R code faster to giving your first data science talk. She also recently released a course on DataCamp on working with categorical data in the tidyverse.
Lydia Kan is a Data Scientist at Publicis North America, where she works on identify consumers’ insights using machine learning algorithms. She collaborates with strategy, analytics, and creative team to develop a methodology to meet clients’ needs. She received her Master degree in Marketing Analytics from New York University, where she developed a passion for predictive analysis. She is fascinated by the stories of customers’ activities behind the data, which leads her to where she at now.

【Schedule】
6:30 - 6:55 networking time (Light refreshment included)
6:55 - 7:00 TDP Introduction
7:00 - 7:30 talk 1
7:30 - 7:40 Q&A 1
7:40 - 8:10 talk 2
8:10 - 8:20 Q&A 2
8:20 - 8:30 wrap up

【Organizers】KT Chang, Yu-Han Chen, Robin Lee, Yi-Hsuan Hsu, Szu-Min Yu, Amy Liu, Wei-Chun Kao, Tina Huang
【Moderator】Yu-Han