Lean Analytics - How to Measure Your Product

  • Published on
    18-Dec-2014

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DESCRIPTION

This presentation was given to startup founders and software people to help them understand how to better measure the success (or failure) of their product by using objective data.

Transcript

  • 1. How to Measure Your Product Data Driven Little Bets Liron Hayun [ UX & Analytics Consultant ] | lironh@gmail.com
  • 2. ANALYTICS UX
  • 3. ANALYTICS DATABASE SURVEYS EMAIL SERVICE
  • 4. ANALYTICS DATABASE SURVEYS EMAIL SERVICE
  • 5. 5 Steps to Epiphany 1) Identify business objectives 2) Translate to technical requirements 3) Implement 4) Measure & Learn 5) Maintain
  • 6. Business Objectives Step 1
  • 7. The 5 Common Business Objectives Ecommerce - sell products/services Lead Generation - collect user info & connect Content - engagement & visits Online Support - finding info at the right time Branding - awareness, engagement & loyalty
  • 8. Practical Guidelines Include macro and micro conversions ------------------------------------------------------------ Distill customer-problem-solution hypothesis Find the riskiest assumptions
  • 9. Technical Requirements Step 2
  • 10. How It Works Users Sessions Interactions
  • 11. Your Product Analytics Server
  • 12. Session User Interaction
  • 13. Session
  • 14. Data Types Dimensions - characteristics of your users, their sessions and actions (e.g. country, traffic source). Metrics - the quantitative measurements of users, sessions and actions.
  • 15. Key Metrics Pageviews / Screens Events --------------------------------------------------- Users Sessions Time on Page Bounce Rate
  • 16. Practical Guidelines Use a consistent syntax upper/lower case letters name of event actions use of - Collect campaign data
  • 17. Implementation Step 3
  • 18. Code Configuration
  • 19. Practical Guidelines Build an infrastructure maintain data integrity easily measure new features keep consistent syntax Setup goals in your analytics tool (!)
  • 20. Measure & Learn Step 4
  • 21. AARRR! 1) Acquisition - users come from various channels 2) Activation - users enjoy first visit 3) Retention - users come back 4) Referral - users like product and refer others 5) Revenue - users conduct monetization behavior
  • 22. Analysis Techniques Segmentation - isolate and analyze data subsets to understand behavior (by location, source). Context - use benchmarks to understand if your performance is good or bad (internal / external). Exploration - browse your data to find your next questions (landing/exit pages, bounce rates).
  • 23. Acquisition
  • 24. Sources Quality
  • 25. Activation
  • 26. Retention
  • 27. Retention
  • 28. Referral
  • 29. Revenue
  • 30. Maintain & Refine Step 5
  • 31. Recommended Tools Google Analytics - free, robust analytics tool Optimizely - easy A/B testing --------------------------------------------------------------------- Google Forms - free surveys, easily embedded Qualaroo - onsite nudges
  • 32. Thank You Liron Hayun [ UX & Analytics Consultant ] | lironh@gmail.com