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How Atlassian Broke Down the Walls Between Support & Development

At Atlassian, support is essential to a successful customer experience. And, because of it's customer-facing position, support is also a great resource for product teams to continually use customer feedback to improve their product or service. Creating strong customer feedback loops means you are building a better experience for your customers day by day.

In this talk, you'll learn 5 ways Atlassian tools facilitate the relationship between support and development and how you can establish these processes and metrics in your own organization.

This talk is a follow on from "How Atlassian Support & Development Team Up to Release Software" from Summit 2016.

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How Atlassian Broke Down the Walls Between Support & Development

  1. 1. How Atlassian Broke Down the Walls Between Support & Development MATT SAXBY | SERVICE ENABLEMENT TEAM LEAD | ATLASSIAN MATT HUNTER | SERVICE ENABLEMENT TEAM LEAD | ATLASSIAN
  2. 2. $0 $30 $60 $90 $120 07-2008 01-2009 07-2009 01-2010 07-2010 01-2011 07-2011 01-2012 07-2012 01-2013 07-2013 01-2014 07-2014 01-2015 07-2015
  3. 3. Agenda Reporting Insights Prediction The Problem
  4. 4. DEVELOPMENT CUSTOMERS SUPPORT PRODUCT
  5. 5. 9SUPPORT CENTERS 350+CUSTOMER SUCCESS STAFF 89,200+CUSTOMERS
  6. 6. CUSTOMERS SUPPORT PRODUCT DEVELOPMENT
  7. 7. Insights Readiness SERVICE ENABLEMENT SUPPORT DEVELOPMENT
  8. 8. 88 SERVICE ENABLEMENT EXISTS TO Create a frictionless product experience for our customers
  9. 9. ShirtVoteTM INTRODUCING
  10. 10. Shirts, for everything For Products
  11. 11. Shirts, for everything For Products
  12. 12. Shirts, for everything For Products For Events
  13. 13. Shirts, for everything For Products For Events
  14. 14. Shirts, for everything For Products For Events For Celebrations
  15. 15. Shirts, for everything For Products For Events For Celebrations
  16. 16. Shirts, for everything For Products For Events For Celebrations For Fun
  17. 17. SHIRT VOTE Add a new shirt design View existing shirt designs ordered by most votes JIRA Service Desk 2015 ShipIt 30 2015 40,000 Customers 2014 Game of Codes 2014 200 votes 180 votes 120 votes 80 votes Need Help?
  18. 18. SHIRT VOTE Full screen images giving you an up close and personal look at the shirt Description with all the detail you would need JIRA Service Desk 2015 Vote Designed to promote JIRA Service Desk and give a great way for users (both inside and outside Atlassian) able to pro… Ability to vote for the shirts you love 200 votes
  19. 19. Agenda Reporting Insights Prediction The Problem
  20. 20. How do you tell if a product is causing customer pain?
  21. 21. Things to Consider: Actionable You can tell what has caused customer pain to go up. Representative When the number goes up customer pain goes up. Trackable Easy to see current status when needed
  22. 22. In App How to create tickets? 1 2 support.shirtvote.com
  23. 23. 60Support tickets in a month
  24. 24. 90Support tickets in a month
  25. 25. 40Support tickets in a month
  26. 26. Things to Consider: Actionable You can tell what has caused customer pain to go up Representative When the number goes up customer pain goes up Trackable Easy to see current status when needed
  27. 27. Tickets Over Time 50 56 62 68 74 80 January February March April May June July
  28. 28. Customer Growth Over Time 0 200 400 600 800 January February March April May June July August
  29. 29. Contact Index Support Tickets =Active Users Contact Index
  30. 30. Contact Index 60 550 10.9%=
  31. 31. Contact Index Over Time 5 6.4 7.8 9.2 10.6 12 January February March April May June July August
  32. 32. Things to Consider: Actionable You can tell what has caused customer pain to go up Representative When the number goes up customer pain goes up Trackable Easy to see current status when needed
  33. 33. = 60 Support Contacts Data Conclusion
  34. 34. Android App I can't view shirts When I open the app to view the list of shirts, it comes up with an error
  35. 35. = 15 Voting on Shirts Data Conclusion = 27 Viewing Shirts = 12 Adding Shirts = 6 Searching for shirts
  36. 36. Things to Consider: Actionable You can tell what has caused customer pain to go up Representative When the number goes up customer pain goes up Trackable Easy to see current status when needed
  37. 37. Agenda Reporting Insights Prediction The Problem
  38. 38. TURNING DATA INTO INSIGHTS Service Enablement has built a partnership with development through turning data into insights.
  39. 39. Bug Ranking Rollouts Support Insights
  40. 40. Bug Ranking Too much time was being wasted deciding which bugs we should solve first. We needed a system to consistently and objectively rank bugs, agreed on across the business.
  41. 41. VIEW SHIRTS BUG VOTING ON SHIRTS BUG
  42. 42. How do we gauge interest in a Bug? Votes and WatchersLinked Support cases
  43. 43. 10 reports20 reports VIEW SHIRTS BUG VOTING ON SHIRTS BUG
  44. 44. Active Users License Tier Customer Size
  45. 45. 10 customers20 customers VIEW SHIRTS BUG VOTING ON SHIRTS BUG 1 active users avg 3 active users avg
  46. 46. 10 customers x 3 active users avg 20 customers x 1 active users avg VIEW SHIRTS BUG VOTING ON SHIRTS BUG 20 active users total 30 active users total
  47. 47. Severity The impact of a bug on the end user, system or business. How bad is it?
  48. 48. Major Performance problems or breaks minor functionality Severity Minor Inconvenience such as a display problem or an inconsistency Critical Causes application outage, or breaks core functionality 8 4 2
  49. 49. 30 active users impacted20 active users impacted VIEW SHIRTS BUG VOTING ON SHIRTS BUG Causes outage Minor feature not working
  50. 50. 30 active users impacted20 active users impacted VIEW SHIRTS BUG VOTING ON SHIRTS BUG Critical Severity Major Severity
  51. 51. Recency How many customers have reported the problem in the past 90 days?
  52. 52. Customers Impacted Per MonthCustomers 0 1 2 3 4 Jan Feb Mar Apr May June July View Bug Voting Bug
  53. 53. 30 active users impacted Major Severity 20 active users impacted Critical Severity VIEW SHIRTS BUG VOTING ON SHIRTS BUG 2 reports in last 90 days 10 reports in last 90 days
  54. 54. Severity How bad is the impact of the bug? User Impact Score Recency Is the bug getting better or worse? Impacted Users Number of users impacted by a bug
  55. 55. UIS Calculation impacted users
 x severity x recency =UIS
  56. 56. 30 active users impacted Major Severity 10 reports in last 90 days 20 active users impacted Critical Severity 2 reports in last 90 days VIEW SHIRTS BUG VOTING ON SHIRTS BUG
  57. 57. 30 (users) x 4 (severity) x 10 (recency) 20 (users) x 8 (severity) x 2 (recency) VIEW SHIRTS BUG VOTING ON SHIRTS BUG = 320 = 1200
  58. 58. 30 x 4 x 10 20 x 8 x 2 VIEW SHIRTS BUG VOTING ON SHIRTS BUG 3 UIS 12 UIS
  59. 59. KEY SUMMARY UIS BUG-4 BUG-3 Images not displaying 7 Shirts not showing in correct order 4 BUG-2 Can’t upload images 2
  60. 60. KEY SUMMARY UIS BUG-4 Images not displaying 7 BUG-3 BUG-1 Shirts not showing in correct order 4 Viewing shirts crashes application 3 BUG-2 Can’t upload images 2
  61. 61. KEY SUMMARY UIS BUG-4 Images not displaying 7 BUG-3 BUG-1 Shirts not showing in correct order 4 Viewing shirts crashes application 3 BUG-2 Can’t upload images 2 BUG-5 Voting on shirts reduces vote count 12
  62. 62. After Alignment on which bugs are the most important, bug master always grabs the issue with the highest UIS. Before Frequent disagreement on the highest bug priorities and what to work on next.
  63. 63. Bug Ranking Rollouts Support Insights
  64. 64. SHIRT VOTE JIRA Service Desk 2015 ShipIt 30 2015 40,000 Customers 2014 Game of Codes 2014 200 votes 180 votes 120 votes 80 votes
  65. 65. SHIRT VOTE JIRA Service Desk 2015 ShipIt 30 2015 40,000 Customers 2014 Game of Codes 2014 200 votes 180 votes 120 votes 80 votes Votes Title Date Sort shirts in the order that suits you best
  66. 66. FEATURE LIFECYCLE - THE OLD Feature is developed Code is reviewed and tests are run. Change is rolled out to entire customer base Bugs related to the feature that weren’t caught during review are fixed. Dev Review Rollout Fix
  67. 67. Gradual Rollouts - The Old 0 13 25 38 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 % of Customers With Feature Support Tickets
  68. 68. SHIRT VOTE JIRA Service Desk 2015 ShipIt 30 2015 40,000 Customers 2014 Game of Codes 2014 200 votes 180 votes 120 votes 80 votes Votes Date Title
  69. 69. SHIRT VOTE
  70. 70. Gradual Rollouts - The Old 0 13 25 38 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 % of Customers With Feature Support Tickets
  71. 71. Gradual Rollouts - The Old 0 13 25 38 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 % of Customers With Feature Support Tickets
  72. 72. Gradual Rollouts - The New 0 12.5 25 37.5 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 % of Customers With Feature Support Tickets
  73. 73. Gradual Rollouts - The New 0 12.5 25 37.5 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 % of Customers With Feature Support Tickets
  74. 74. Gradual Rollouts - The New 0 12.5 25 37.5 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 % of Customers With Feature Support Tickets
  75. 75. BIG BANG VS GRADUAL ROLLOUT 0 2.5 5 7.5 10 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Contact Rate - Gradual Contact Rate - Big Bang Tickets Created: Big Bang - 57 Gradual - 29
  76. 76. FEATURE LIFECYCLE Feature is developed Code is reviewed and tests are run. Change is gradually rolled out. Most bugs were caught during rollout, so this feature is ready to close off. Dev Review Rollout Close Tight feedback loop to ensure problems are caught early Feedback
  77. 77. Contact Rate Create a contact rate specifically monitoring tickets received from customers with the feature. Gradual Rollout Pro Tips Feedback Loop Work closely with the Development team to share feedback asap. Readiness Involvement with Development early in the cycle ensures the support team is ready for the change.
  78. 78. Agenda Reporting Insights Prediction The Problem
  79. 79. Hiring Allows you to forecast the number of Supporters you need to hire Customer Experience Helps to tell the customer experience story Development Negotiations Assists with negotiating Development priorities Goal Setting Sets goals to track the success of the team. Why is prediction Important?
  80. 80. Baseline Forecast of support contact assuming current trends continue Initiatives Changes impacting product that are expected to impact support contact How do you predict?
  81. 81. Baseline Forecast of support contact assuming current trends continue Initiatives Changes impacting product that are expected to impact support contact How do you predict?
  82. 82. Complex Modelling • Prophet • ARIMA BASE FORECASTING Basic Modelling Average Yearly Contact Index 0 3 6 9 12 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec FY16 FY17
  83. 83. BASE FORECASTING 0 3 6 9 12 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec FY16 FY17 Average Complex Modelling • Prophet • ARIMA Basic Modelling Average Yearly Contact Index
  84. 84. BASE FORECASTING 0 3 6 9 12 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average Complex Modelling • Prophet • ARIMA Basic Modelling Average Yearly Contact Index
  85. 85. Contact Index Support Tickets =Active Users Contact Index
  86. 86. Support Tickets Support Tickets = Forecast Contact Index x Active Users
  87. 87. BASE FORECASTING 0 20 40 60 80 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tickets
  88. 88. Baseline Forecast of support contact assuming current trends continue Initiatives Changes impacting product that are expected to impact support contact How do you predict?
  89. 89. Contact Decrease Bugfix, feature improvement, support policy changes. Contact Increase Rollouts, infrastructure change. Initiative Types
  90. 90. CONTACT DECREASE 0 20 40 60 80 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ticket Forecast Shirt voting bug due to be fixed in February.
  91. 91. CONTACT DECREASE 0 20 40 60 80 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ticket Forecast Post Bug Fix Shirt voting bug due to be fixed in February.
  92. 92. Contact Decrease Bugfix, feature improvement, support policy changes. Contact Increase Rollouts, infrastructure change. Initiative Types
  93. 93. SHIRT VOTE JIRA Service Desk 2015 ShipIt 30 2015 40,000 Customers 2014 Game of Codes 2014 200 votes 180 votes 120 votes 80 votes Search for the shirts that interest you Search
  94. 94. The best predictor of future behaviour is past behaviour DR PHIL
  95. 95. Gradual Rollouts - The New 0 12.5 25 37.5 50 Rollout% 0% 25% 50% 75% 100% Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 % of Customers With Feature Support Tickets
  96. 96. CONTACT INCREASE 0 22.5 45 67.5 90 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ticket Forecast Search feature due to be Rolled out in May and June
  97. 97. CONTACT INCREASE 0 22.5 45 67.5 90 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ticket Forecast Post Rollout Search feature due to be Rolled out in May and June
  98. 98. INITIATIVES COMBINED 0 22.5 45 67.5 90 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Baseline Forecast Final Forecast Including both positive and negative contact changes
  99. 99. Hiring Allows you to forecast the number of Supporters you need to hire Customer Experience Helps to tell the customer experience story Development Negotiations Assists with negotiating Development priorities Goal Setting Sets goals to track the success of the team. Why is prediction important?
  100. 100. Insights Making things actionable is fundamental to creating change In Summary Prediction You need to look to the future to prepare your support team and ensure they can provide legendary support Reporting Have a Trackable, Representative and Actionable way to gauge customer impact.
  101. 101. Thank you! MATT SAXBY | SERVICE ENABLEMENT TEAM LEAD | ATLASSIAN MATT HUNTER | SERVICE ENABLEMENT TEAM LEAD | ATLASSIAN
  102. 102. What do you think? Ask a question to win one of 10 Service Desk Shirts

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