It's generally understood that data, when used correctly, can be used to build great products that grow like bamboo; but it's never obvious how to do so. Over the last 3 years, Atlassian has grown its Product Analytics team from 1 analyst to 12 (a 1200% increase!) and 0kb of data to over 6TB (infinite % increase). Come find out how we've built a team, metrics, and a culture of data within engineering at Atlassian. Most importantly, learn how to unlock the power of data in your company and set a growth trajectory for your product.

1. REED JOHNSON • PRODUCT ANALYST • ATLASSIAN • @JMROHNSON
How Atlassian Uses
Analytics to Build Better
Products

2. • Big cool statistic
• 2,56
9
• Add-Ons in Marketplace

3. • Big cool statistic
• 2,56
9
• Add-Ons in Marketplace

4. Too fast

5. HOW?

6. EXPERIMENTATION
Pyramid of Analytics
DATA LITERACY
FUNNELS
DATA
SCIENCE

7. DATA LITERACY
Agenda
ATLASSIAN JOURNEY
FUNNELS
EXPERIMENTATION

8. The Atlassian Journey

9. Atlassian
2012
0Product Analysts
400+Staff

10. SOURCE: OPTIMIZELY

11. • Big cool statistic
• 2,56
9
• Add-Ons in Marketplace

12. SOURCE: LEIGH PRATHER

13. Too busy

14. Not in my product

15. You did what?

16. SO YOU’RE A GROWTH HACKER YOU
SAY?

17. Pyramid of Analytics
EXPERIMENTATION
DATA LITERACY
FUNNELS
DATA
SCIENCE

18. Crystal Ball of Analytics

19. We have data

20. Validate ideas

21. Make better
decisions

22. Find growth

23. Pyramid of Analytics
EXPERIMENTATION
DATA LITERACY
FUNNELS
DATA
SCIENCE

24. SOURCE: JIM STOPPANI - BODYBUILDING.COM

25. ATLASSIAN JOURNEY
Agenda
DATA LITERACY
FUNNELS
EXPERIMENTATION

26. DATA LITERACY
Pyramid of Analytics
EXPERIMENTATION
FUNNELS
DATA
SCIENCE

27. Source: amitypublications.com

28. Vanity
metrics
220KPages /
Week in Confluence
2MIssues / Week
in JIRA

29. Blog in Confluence
(I know you aren’t)

33. Product Outreach
Teams

34. Management Buy-In

35. Don’t starve

36. Graduation
Criteria
Developers add analytics to
new features
Data is accessible to all
members of the organization
Culture of looking at data

37. Pyramid of Analytics
DATA LITERACY
DATA
SCIENCE
FUNNELS
EXPERIMENTATION

39. Acquisition
Activation
Retention
Revenue
Referral

40. How do customers find us?
Do they have a great first experience?
Do they stay or do they churn?
Do they pay us?
Do they bring in others?
Acquisition
Activation
Retention
Revenue
Referral

41. Onboarding for JIRA
Evaluations
Signed In
Created a Project
Created an Issue
Second Issue
Second User
Purchased
0 0,25 0,5 0,75 1
10%
5%
18%
34%
43%
21%

42. You’ve got issues

43. Graduation
Criteria
Funnels are central to data
Conversations

44. FUNNELS
Pyramid of Analytics
DATA LITERACY
DATA
SCIENCE
EXPERIMENTATION

46. The scientific method
ADDRESS A PROBLEM
PROPOSE A SOLUTION
RUN AN EXPERIMENT
ANALYZE RESULTS
MAKE A CONCLUSION

47. Problem: First Issue Is Too Hard To Create
Finding Focus
Evaluations
Signed In
Created a Project
Created an Issue
Second Issue
Second User
Purchased
0 0,25 0,5 0,75 1

48. Classic Create
Button

49. Log Issue
Button

50. Onboarding For JIRA
Before
Evaluations
Signed In
Created a Project
Created an Issue
Second Issue
Second User
Purchased
0 0,25 0,5 0,75 1

51. Onboarding For JIRA
Finding Focus
Evaluations
Signed In
Created a Project
Created an Issue
Second Issue
Second User
Purchased
0 0,25 0,5 0,75 1

52. SO YOU’RE A GROWTH HACKER YOU
SAY?

53. Graduation
Criteria
Tooling around
experimentation
Experiment analysis is self-
service
Experimentation used to
resolve debates

54. ATLASSIAN JOURNEY
DATA LITERACY
Agenda
FUNNELS
EXPERIMENTATION

55. SOURCE: JIM STOPPANI - BODYBUILDING.COM

56. EXPERIMENTATION
Pyramid of Analytics
DATA LITERACY
FUNNELS
DATA
SCIENCE

57. Thank you!
REED JOHNSON • PRODUCT ANALYST • ATLASSIAN • @JMROHNSON