[class: PM Camp@Fast Campus#13] 사용자 행동 데이터 분석하기 #1 (my note is WIP)

7주차

6. 20 토

사용자 행동 데이터 분석하기 #1

구글 애널리틱스 개요, 활용 사례 및 기능 기능들 둘러보기 Google Analytics 개요 및 활용 사례 기능 둘러보기 및 핵심 개념 소개 분석 실습 #1

강규영

1. Google Analytics basics, application, function [Gyuyoung Kang@Box and Whisker, Founder]
1. lesson:
1. wrong approach of focusing on pageviews needs to be avoided and why data analysis is important
1. purpose of below ad technique
1. “헉” or “설마”: hooking
2. moving ad: design of eyes follow moving object, error click
3. small x button: error click
2. reason: page view ⇔ revenue
3. loser: user, advertiser
4. winner: platform (e.g. Google ad network), publisher
5. solution: smart advertiser using conversion metrics
2. pitfalls of mechanical application of data analysis without intuitive judgment
1. benefit of intuition: in data analysis, intuition helps avoids local optimum and seasonal bias
2. how to obtain skilled intuition: set up mechanism and environment, requiring both regularity and quantitative feedback
3. pitfalls of A/B test: seasonal bias (e.g. users’ color preference of green and red in Halloween and Christmas season), staying within local optimum (due to hill climbing algorithm)
3. data analysis requires complex learning task
4. proper order of data analysis: action based quest -> questions -> data -> data analysis
5. user story writing method (avoid including functions): “As a <ROLE>, I want <FEATURE> so that <BENEFIT> e.g.  As a <bank customer>, I want <to withdraw cash from an ATM>, so that <I don't have to wait in line at the bank.>
6. log (or weblog): system status change history (URL) by time and user (& IP address)
1. web browser (or world wide web browser) is web client (or http client) (c.f. web or http server)
2. c.f. add event type on GA to track down activities (e.g. transaction) within a web page
7. GA:
1. how-to
1. for additional analysis, consider adding this
1. e.g. ga('require', 'displayfeatures'); ga('require', 'linkid', 'linkid.js')
2. menu
1. audience: 누가 (e.g. 어떤 사람들)
1. session: 방문회수 by given time
2. user: unique browser number not a user (e.g. Chrome, IE, app)
3. engagement metrics: e.g. new sessions, pages/sessions
1. number can’t give either positive or negative (c.f. in general, higher number may mean positive); thus, combine with other metrics)
2. acquisition: 어디에서 (e.g. push message, Facebook, etc.)
1. direct
2. referral: social (e.g. Facebook), search (organic, paid), email (e.g. Gmail), referral (others)
3. behavior: 뭘했나?
4. conversion: 얼마 벌었나? (e.g. purchase, download)
1. goal: selection of metric needs to influence people’s behavior
2. consider analyzing Top Conversion Path
3. try
1. modify bounce rate, filter IP for tracking
4. bounce rate: session base
8. read Extreme Programming Explained: Embrace Change by Kent Beck

2. personal takeaway:
1. new term: hill climbing algorithm, Return On Advertising Spend (ROAS)
2. 10,000 hour law:
1. to obtain skilled intuition, establish mechanism and environment, requiring both regularity and quantitative feedback
2. improve areas of weakness with focus
3. key concept of agile development methodology: deliver values to users everyday
4. try Google Data Saver for VPN
5. Chrome Extension: Table Booster
6. when communicating with software engineers, tell them what you want to accomplish (aka your intentions) instead of detailed function list 
7. consider implementing “careful reading” JavaScript into your website to track down accurate user feedback