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

1. “Helping startups grow into success stories!”
Mobile Metrics and Analytics

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. 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. 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. Overview of analytics
1

6. What is Analytics?
OVERVIEW OF ANALYTICS

7. What is Analytics?
From Wikipedia : Analytics is the discovery and communication of
meaningful patterns in data
OVERVIEW OF ANALYTICS

8. What is Analytics?
From Wikipedia : Analytics is the discovery and communication of
meaningful patterns in data
MY TRAVELS VISUALIZED

9. OVERVIEW OF ANALYTICS
http://www.statista.com/statistics/430830/share-of-

10. FACEBOOK AD REACH
0
20000000
40000000
60000000
80000000
100000000
120000000
140000000
160000000
Nigeria India South Africa Indonesia
FB Ad reach

11. FACEBOOK AD REACH TO POPULATION
0
200000000
400000000
600000000
800000000
1000000000
1200000000
1400000000
Nigeria India South Africa Indonesia
FB Ad reach Population

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. TYPES OF ANALYTICS – THE THEORY
http://www.ciandt.com/card/four-types-of-
analytics-and-cognition

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. WHAT HAPPENED

16. WHY IT HAPPENED
ET TechCrunch Product Hunt

17. WHAT MAY HAPPEN

18. WHAT MAY HAPPEN

19. WHAT MAY HAPPEN

20. Mobile metrics for different stages of the
Growth Hacking Funnel
2

21. Mobile metrics for different stages of the
Growth Hacking Funnel
2
Hacking Analytics

22. HACKING ANALYTICS

23. HACKING ANALYTICS

24. HACKING ANALYTICS

25. HACKING ANALYTICS
- TRUE NORTH - HEALTH METRICS

26. HACKING ANALYTICS

27. HACKING ANALYTICS

28. HACKING ANALYTICS

29. • Acquisition
• Activation
• Referrals
• Retention
• Revenue
• True North
• Health Metrics
METRICS - HAPTIK

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. • Acquisition
• Activation
• Referrals
• Retention
• Revenue
• True North
• Health Metrics
METRICS - SNAPDEAL

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. • Acquisition
• Activation
• Referrals
• Retention
• Revenue
• True North
• Health Metrics
METRICS - ZOMATO

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. • Acquisition
• Activation
• Referrals
• Retention
• Revenue
• True North
• Health Metrics
METRICS - CLEARTRIP

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. • Acquisition
• Activation
• Referrals
• Retention
• Revenue
• True North
• Health Metrics
METRICS – EXERCISE

38. How to extract actionable insights
from data
3

39. • Charts
• Pie
• Bar
• Stacked
• Cohorts
• Funnels
• Pivots
• Data Filters
TOOLS TO EXTRACT DATA

40. • Charts
• Pie
• Bar
• Stacked
• Cohorts
• Funnels
• Pivots
• Data Filters
TOOLS TO EXTRACT DATA
Plan

41. NEEDLE IN A HAYSTACK

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. 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. LETS LOOK AT SOME DATA

45. LETS LOOK AT SOME DATA

46. LETS LOOK AT SOME DATA

47. LETS LOOK AT SOME DATA

48. LETS LOOK AT SOME DATA

49. LETS LOOK AT SOME DATA

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. 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. TOOLS – PIE CHARTS

53. TOOLS – STACKED CHARTS

54. TOOLS – AREA CHARTS

55. TOOLS – COHORTS

56. TOOLS – COHORTS

57. TOOLS – COHORTS http://bslatkin.github.io/cohorts/

58. TOOLS – COHORTS http://bslatkin.github.io/cohorts/

59. TOOLS – FUNNELS

60. TOOLS – PIVOTS

61. TOOLS – PIVOTS

62. Overview of Tools & Platforms
4

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. FLURRY http://flurry.com
Cohorts Yes
Timelines
Flows
Funnels Yes
Pivots
Others
Personas,
Demographics
Segmentation Yes
A/B Testing
Engagement
Attribution

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. MIXPANEL http://mixpanel.com
Cohorts Yes
Timelines
Flows
Funnels Yes
Pivots
Others
Segmentation Yes
A/B Testing Yes
Engagement Yes
Attribution

67. LOCALYTICS http://localytics.com
Cohorts Yes
Timelines
Flows
Funnels Yes
Pivots
Others
Segmentation Yes
A/B Testing
Engagement Yes
Attribution Yes

68. MOENGAGE http://moengage.com
Cohorts Yes
Timelines Yes
Flows
Funnels
Pivots
Others
Segmentation Yes
A/B Testing
Engagement Yes
Attribution Yes

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. OTHERS

71. Learn how to build a culture of being data
driven
5

72. CULTURE
• Building Culture is inherently hard

73. CULTURE

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