how buffer uses looker to create user targeted emails

Download How Buffer uses Looker to create user targeted emails

Post on 08-Aug-2015



Data & Analytics

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  1. 1. How uses to create user targeted emails
  2. 2. Numbers Founded Late 2010 48k DAU / 190K MAU (~3k daily signups) $470k Monthly Revenue Run-Rate from ~33k customers ~600k social media posts scheduled per day 31 Team members 9 Engineering, 3 Marketing, 7 Support, 2 data
  3. 3. Sign-up/Onboarding lifecycle emails (2012-2015) Welcome Install Extensions Buffer Tips
  4. 4. Why didnt we iterate on emails? Hard coded templates in our code base Required developer time to think and implement email triggers Small developer team, emails not a dev priority over product Targeting users part of our larger data problem
  5. 5. Led to not-so-great marketing habits Mass emailing our 2 million users Lower open and click rates Higher spam rates and bounces Rough experience for users with irrelevant messages
  6. 6. October 2014
  7. 7. Dec 2014 Awesome! Moving fast with data analysis But iteration cant keep up.
  8. 8. Solution: Remove developers out of the equation Empower any team member to create/style their own emails Give them the power to target individual users (without needing dev help) ie. Build our own version of, leveraging Looker to target users
  9. 9. Example: New Targeted Welcome emails
  10. 10. Example: Welcome email to users who joined 3 hours ago and who have set up their schedule
  11. 11. Buffers Trigger Email CMS
  12. 12. How it works Simple cron job running every 10 minutes Runs Looker generated SQL queries in redshift to grab user ids Sends users notications/emails Some regex magic to look up currently used PDT
  13. 13. How the team is using it Started with marketing and lifecycle emails Outbound support. Predicting areas for confusion and errors Customer Development, targeted surveys
  14. 14. Where we want to go In app notifications (mobile and web) Dynamic data through templating (eg. %column2%) Request to Looker (adjusting column order reflected in SQL statement)