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Mobile Metrics and Analytics

An analytics workshop held during the Growth Hacking Asia meetup in Jan 2016 (https://www.townscript.com/e/growthhackingbootcamp)

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Mobile Metrics and Analytics

  1. 1. “Helping startups grow into success stories!” Mobile Metrics and Analytics
  2. 2. • VP Product @ MoEngage • Product Manager and a Developer Advocate @ Vserv - Drove developer products - AppWrapper & SDKs • Android Developer @ TechJini - Lead Android developer & Project Manager • Co-organizer @ Blrdroid, a 7000 strong Android Community. • Masters in Computer Science from Florida State University • My Current interests lie in Analytics, Growth & SAAS. • Twitter : @ravivyas84 • Email: ravi@vyas.me or ravivyas@moengage.com • Medium: medium.com/ravivyas • WWW: Ravivyas.com About Me
  3. 3. What we will work on today: • Overview of analytics platforms and tools (3-4PM) • Introduction to relevant mobile metrics for different stages of the Growth Hacking Funnel (4-5PM) • How to extract actionable insights from data (5-6PM) • Learn how to build a culture of being data driven (6-7PM) AGENDA
  4. 4. What we will work on today: • Overview of analytics • Mobile metrics for different stages of the Growth Hacking Funnel • How to extract actionable insights from data • Overview platforms and tools • Learn how to build a culture of being data driven AGENDA
  5. 5. Overview of analytics 1
  6. 6. What is Analytics? OVERVIEW OF ANALYTICS
  7. 7. What is Analytics? From Wikipedia : Analytics is the discovery and communication of meaningful patterns in data OVERVIEW OF ANALYTICS
  8. 8. What is Analytics? From Wikipedia : Analytics is the discovery and communication of meaningful patterns in data MY TRAVELS VISUALIZED
  9. 9. OVERVIEW OF ANALYTICS http://www.statista.com/statistics/430830/share-of-
  10. 10. FACEBOOK AD REACH 0 20000000 40000000 60000000 80000000 100000000 120000000 140000000 160000000 Nigeria India South Africa Indonesia FB Ad reach
  11. 11. FACEBOOK AD REACH TO POPULATION 0 200000000 400000000 600000000 800000000 1000000000 1200000000 1400000000 Nigeria India South Africa Indonesia FB Ad reach Population
  12. 12. Descriptive – What HAS happened? - Our MAUs were up 10% last month - Descriptive Analytics is the examination of data or content, usually manually performed, to answer the question “What happened?” (or What is happening?) - Traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives Diagnostic – WHY did this happen? - Diagnostic Analytics is a form of advance analytics which examines data or content to answer the question “Why did it happen?” - Drill-down, data discovery, data mining and correlations. Predictive – What COULD happen? - Predictive Analytics is a form of advanced analytics which examines data or content to answer the question “What is going to happen?” or more precisely, “What is likely to happen? - Regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling, and forecasting. Prescriptive – What SHOULD happen? - Prescriptive Analytics is a form of advanced analytics which examines data or content to answer the question “What should be done?” or “What can we do to make _______ happen?” - Graph analysis, simulation, complex event processing, neural networks, recommendation engines, heuristics, and machine learning. TYPES OF ANALYTICS – THE THEORY
  13. 13. TYPES OF ANALYTICS – THE THEORY http://www.ciandt.com/card/four-types-of- analytics-and-cognition
  14. 14. • What Happened • Why it happened • What may happen • How to prevent bad things from happening and make good things happen TYPES OF ANALYTICS – THE THEORY
  15. 15. WHAT HAPPENED
  16. 16. WHY IT HAPPENED ET TechCrunch Product Hunt
  17. 17. WHAT MAY HAPPEN
  18. 18. WHAT MAY HAPPEN
  19. 19. WHAT MAY HAPPEN
  20. 20. Mobile metrics for different stages of the Growth Hacking Funnel 2
  21. 21. Mobile metrics for different stages of the Growth Hacking Funnel 2 Hacking Analytics
  22. 22. HACKING ANALYTICS
  23. 23. HACKING ANALYTICS
  24. 24. HACKING ANALYTICS
  25. 25. HACKING ANALYTICS - TRUE NORTH - HEALTH METRICS
  26. 26. HACKING ANALYTICS
  27. 27. HACKING ANALYTICS
  28. 28. HACKING ANALYTICS
  29. 29. • Acquisition • Activation • Referrals • Retention • Revenue • True North • Health Metrics METRICS - HAPTIK
  30. 30. • Acquisition • Ad Group • City • CAC • ?? • Activation • Signed Up • Send Message • Tutorial done • Push Preference • Referrals • Referrals (if done) • Social mentions • Retention • 1D, 7D , 30D • Revenue • Recharges, orders etc. • True North • Sessions/ Users • Health Metrics • Messages per user • Avg Topics per user METRICS - HAPTIK
  31. 31. • Acquisition • Activation • Referrals • Retention • Revenue • True North • Health Metrics METRICS - SNAPDEAL
  32. 32. • Acquisition • Ad Group • City • CAC • Reinstalls, ?? • Activation • Product Viewed • Product Search • Referral • Referrals (if done) • Social mentions, shares • Retention • 1D, 7D , 30D, 60D, Email Opens & Clicks • Revenue • Purchases • True North • Purchases • Health Metrics • Searches per user, Products viewed per user • Add to Carts per user • Avg sessions to first purchase • Avg Product viewed per user METRICS - SNAPDEAL
  33. 33. • Acquisition • Activation • Referrals • Retention • Revenue • True North • Health Metrics METRICS - ZOMATO
  34. 34. • Acquisition • Ad Group • City • CAC • ?? • Activation • Restaurant Search • City Selection • Referrals • Referrals (if done) • Social mentions, shares • Retention • 1D, 14D , 30D, Email Opens & Clicks • Revenue • Calls • True North • Views per user • Health Metrics • Feedback per user • Rating per user • check-in per user METRICS - ZOMATO
  35. 35. • Acquisition • Activation • Referrals • Retention • Revenue • True North • Health Metrics METRICS - CLEARTRIP
  36. 36. • Acquisition • Ad Group • City • CAC • Reinstalls • Activation • Trip Search • Referrals • Referrals (if done) • Social mentions, Ticket Forwards • Retention • 1D, 30D, 90D, 360D, Email Opens & Clicks • Revenue • Booking • True North • Booking • Health Metrics • Bookings per user • Categories per user • Booking per user per Quarter METRICS - CLEARTRIP
  37. 37. • Acquisition • Activation • Referrals • Retention • Revenue • True North • Health Metrics METRICS – EXERCISE
  38. 38. How to extract actionable insights from data 3
  39. 39. • Charts • Pie • Bar • Stacked • Cohorts • Funnels • Pivots • Data Filters TOOLS TO EXTRACT DATA
  40. 40. • Charts • Pie • Bar • Stacked • Cohorts • Funnels • Pivots • Data Filters TOOLS TO EXTRACT DATA Plan
  41. 41. NEEDLE IN A HAYSTACK
  42. 42. PLAN • Figure out what is the data you need • Figure out what are the inputs you will need • Go to war with the tech team Exercise - Clients who sent a campaign each week where user base was > 5000 • What are the inputs?
  43. 43. PLAN • Figure out what is the data you need • Figure out what are the inputs you will need • Go to war with the tech team Exercise - Clients who sent a campaign each week where user base was > 5000 • What are the inputs? • Campaigns sent • date time • User count • Aggregate it to each week • Put on a date histogram
  44. 44. LETS LOOK AT SOME DATA
  45. 45. LETS LOOK AT SOME DATA
  46. 46. LETS LOOK AT SOME DATA
  47. 47. LETS LOOK AT SOME DATA
  48. 48. LETS LOOK AT SOME DATA
  49. 49. LETS LOOK AT SOME DATA
  50. 50. LETS LOOK AT SOME DATA https://medium.com/swlh/diligence-at-social-capital-part-1-accounting-for-user-growth- 4a8a449fddfc#.4p7jqeq4z https://goo.gl/sKzq8s
  51. 51. LETS LOOK AT SOME DATA https://medium.com/swlh/diligence-at-social-capital-part-1-accounting-for-user-growth- 4a8a449fddfc#.4p7jqeq4z https://goo.gl/sKzq8s
  52. 52. TOOLS – PIE CHARTS
  53. 53. TOOLS – STACKED CHARTS
  54. 54. TOOLS – AREA CHARTS
  55. 55. TOOLS – COHORTS
  56. 56. TOOLS – COHORTS
  57. 57. TOOLS – COHORTS http://bslatkin.github.io/cohorts/
  58. 58. TOOLS – COHORTS http://bslatkin.github.io/cohorts/
  59. 59. TOOLS – FUNNELS
  60. 60. TOOLS – PIVOTS
  61. 61. TOOLS – PIVOTS
  62. 62. Overview of Tools & Platforms 4
  63. 63. AMPLITUDE https://amplitude.com/ Cohorts Yes Timelines Yes Flows Yes Funnels Yes Pivots Growth Discovery Engine Others SQL Segmentation Yes A/B Testing Engagement Attribution
  64. 64. FLURRY http://flurry.com Cohorts Yes Timelines Flows Funnels Yes Pivots Others Personas, Demographics Segmentation Yes A/B Testing Engagement Attribution
  65. 65. GOOGLE ANALYTICS http:// Google it ;) Cohorts Beta Timelines Flows Yes Funnels Partly Pivots Yes Others Export to Sheets, Ad Integration Segmentation Partly A/B Testing Engagement Attribution
  66. 66. MIXPANEL http://mixpanel.com Cohorts Yes Timelines Flows Funnels Yes Pivots Others Segmentation Yes A/B Testing Yes Engagement Yes Attribution
  67. 67. LOCALYTICS http://localytics.com Cohorts Yes Timelines Flows Funnels Yes Pivots Others Segmentation Yes A/B Testing Engagement Yes Attribution Yes
  68. 68. MOENGAGE http://moengage.com Cohorts Yes Timelines Yes Flows Funnels Pivots Others Segmentation Yes A/B Testing Engagement Yes Attribution Yes
  69. 69. OTHERS Excel Dies at 1M rows, great for small data sets Google Sheets Can’t work offline Tableau Not free Qlikview Free on windows & qlikview web Kibana Technically challenging, powerful visualization SQL Caveman approach, non tech folks will run the other way …... ......
  70. 70. OTHERS
  71. 71. Learn how to build a culture of being data driven 5
  72. 72. CULTURE • Building Culture is inherently hard
  73. 73. CULTURE
  74. 74. CULTURE • Open Data culture • Be driven by numbers • Plan to track at product launch • Product specs should have details on what to track • Retrospect on the data post launch • Question the data • Baseline • Drilldown • Provide tools to visualize the data • Live Dashboards • Data Export tools

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