Tuesday, April 28, 2015

[lecture] Growth Hacking by 고영혁 from 쫄지마 창업스쿨 (translation: Don’t be Afraid Entrepreneurship School)



Subject
쫄지마 창업스쿨 (translation: Don’t be Afraid Entrepreneurship School)
Place
Maru 180 B1F, Seoul
Time
April 28, 2015 (Mon) 19:30~21:50
Speaker
고영혁 (Dylan Ko)
Host
Asan Nanum
Focus
growth hacking concept, how-to, case


  1. Lesson
    1. concept: intersection between engineering and marketing
    2. component: analytics in the center, and others (viral growth, landing page optimization, SEO, product management, on-boarding, analytics, PR, etc.) around
    3. essence: increase conversion by consistent measurement and analysis
    4. steps to growth hack
      1. step #1: create PMF (product market fit) in product market
        1. PMF is similar to lean startup’s MVP (minimum viable product)
        2. conduct interactive prototyping by observing interviews closely for their quantity and quality
        3. use tools (e.g. Optimizely for A/B testing)
      2. step #2: generate leads
        1. focus on passionate and targeted first 100~1,000 users
        2. know user cohorts
      3. step #3: maximize word-of-mouth
        1. add share buttons to assist users wanting to spread news to fulfill their rewards such as emotional or monetary
        2. read the Buzzfeed case (e.g. link)
      4. step #4: retain customers and optimize
        1. watch closely customer experience and conversion: e.g. 5% increase of customer retention generates 30 % increase of company profitability (source: Bain & Company)
    5. prep for growth hacking based on data analysis
      1. metrics: standard (i.e. base), milestone (e.g. from a to b, try one scenario, then move to next scenario), stock (i.e. snapshot) and flow (i.e. change over time)
        1. quantity vs. quality
        2. investigative vs reportive
        3. void vs. actionable: void (e.g. click, page view, visit (reach), unique visitor, follower/friend/like) vs. actionable (e.g. when growth rate speed changes from 4.4 to 3.4, find bottleneck)
        4. number vs. rate
        5. predictive vs. summarized
        6. relational vs. causal: relational (e.g. relationship between soft drink and umbrella during rain season) vs. causal (e.g. b/c of a, b occurs)
      2. CLV (customer lifetime value)
        1. use this concept in service planning
        2. life in CLV means from the start and end of the user in using service
        3. determining factor: decreasing AC (customer acquisition cost)
      3. Dave McClure’s AARRR
        1. acquisition: focus on user acquisition cost
        2. activation: registration rate, email readers rate
        3. retention
        4. referral
        5. revenue
      4. A/B testing: control other factors when modifying an independent factor
      5. cohort analysis: pay attention to various factors more than one factor influencing users’ exit (e.g. on x and y axis: put member date on x and exit date on y)
      6. The Stages of Lean Analysis
      7. look at checklist
    6. case
      1. non-Korean example
        1. LinkedIn: allowed service appearing organically on Google’s SERP (search engine result page)
        2. YouTube: used embedding links
        3. Airbnb: used spam mail to craigslist users by solving users’ pain point
        4. Hotmail: inserted a tiny ad at the bottom of message
        5. PayPal: included logo on eBay’s search result page
      2. Korean example
        1. 젤리버스 (Jelly Bus)
          1. finding market: pivoted from photo-editing to photo-collaging
          2. marketing: visited mad users’ posts and added replies, generating viral through loyalty users
          3. l10n with SEO: localized translations by using words appeared on Google SERP
          4. metrics: MAU, monthly app usage frequency
          5. tool: Appstatics for hot app downloads
        2. 요기요 (Yogiyo)
          1. PMF: minimize order and delivery process and touch interactions, and list just contact info and address
          2. paid attention to rate at each funnel process
          3. targeted minimizing CAC per channels
          4. took advantage of IPTV ad by matching users between app and IPTV
          5. created a success team tracking all data and provided feedback to each member (e.g. asked about meaningful data)
          6. minimized delivery failure to zero by changing map structure
          7. iterated test -> action -> optimize
      3. c.f. implement user’s developed feature in your service
    7. know-how
      1. analyze first experience thoroughly to see how new users came, what happened environmentally, how users moved, etc.
      2. create growth hacking culture from the top and spread within organization
      3. communicate within departments of development, planning, marketing and design team
      4. list up success and failure history structurally by sharing which change influenced what, what environment was there when something happened to find out cause and effect
      5. reuse success patterns by listing up rules from success history
      6. customize dashboards to meet your needs
      7. talk about performance through metrics within your organization by creating stories by metrics
      8. divide measuring subjects? until you can’t divide
      9. focus on causality not relation-ability?
      10. share small success within organization
    8. tools
      1. Fanpagekarma.com to investigate competitors to know e.g. demographics and topics
      2. Social Lead Freak to target users
      3. bit.ly for link tracking
      4. http://www.usertesting.com/ for outsourced user testing
  1. personal takeaway
    1. AC is the most important number to minimize
    2. growth hack everything