Holding Effective Data Meetings

1. Holding Effective Data Meetings Ben Weber Director of BI & Analytics April 30, 2015

2. Analytics Summit Goals Learn how to build an effective data team Discover new techniques and tools for mining data insights Learn how to effectively interact with game teams to act on data insights

3. Questions What data to share with game teams? When and how to share data? How to operationalize your data?

4. Barriers to Using Data Little communication between the data and game teams Automated reports not providing actionable data Data team is not working on actionable issues Team structure separates game developers from analysts

5. Daybreak’s Approach Integrate analysts into game teams Develop consistent reporting across the portfolio and teach teams how to use the data Frequently meet with game teams to identify areas of opportunity

6. Overview Team Structure Sharing Data Meetings Acting on Data

7. BI Team Structure Centralized Roles – Director of BI & Analytics – Data Architect – Ecommerce Analyst Embedded Analysts – H1Z1 – PlanetSide 2 – DC Universe Online Database Operations

8. Centralized Analyst Role Performs data analysis across the portfolio Supports the marketing and exec teams by building portfolio-wide KPIs and reports Types of Analysis – User acquisition funnels – Email campaign ROI – Ad-hoc analysis for centralized teams

9. Embedded Analyst Role Co-located and considered part of the game team Supports the producer and creative director with game design and marketplace insights Types of Analysis – Game balance – In-game retention funnels – Ad-hoc analysis for the game team

10. What Data to Share? All game-specific KPIs are provided to all members of the team Ad-hoc analysis is first shared with the leads and communicated to relevant team members Portfolio KPIs are shared across the company

11. Reports Automated Reports – Daily KPIs – Hourly KPIs – Monthly KPIs – Self-Service Portal Data Pipeline – Vertica, Tableau Server, and Excel

12. Meetings Analytics 101 Data Scrum Meetings Data Insights Meetings Monthly Business Reviews

13. Analytics 101 Goal – Explain our automated reports to game teams Attendees – Everyone! Agenda – Define all of those fun acronyms – Provide context for each of the metrics being tracked – Team members ask questions and provide feedback

14. Data Scrum Meetings Goal – Meet with game team weekly to track KPIs Attendees – Game team leads, brand manager, eComm team Agenda – Discuss KPI trends and targets – Identify ad-hoc analysis to perform – Evaluate the impact of promotional events

15. Data Insights Meetings Goal – Share insights from portfolio or game-specific analysis – Scheduled as necessary – Example: item drop rates in a game are too high Attendees – Game team leads Agenda – Explain the results of the analysis – Indentify how to respond to the findings

16. Monthly Business Reviews Goal – Monthly meeting to review game performance Attendees – Senior management and game team leads Agenda – Review KPIs for the past and current months – Present substantial data insights – Try to get executives to become data evangelists

17. Acting on Data Insights How can we get game teams to act on data insights? Interaction Approaches – Hand-off the results – Own a data model – Share a data model – Show ROI results

18. The Hand-Off Approach Overview – The data team performs an analysis and hands-off the results to the game team – The game team decides how to use the data Examples – DCUO Character Traits – PlanetSide 2 Starter bundles – PlanetSide 2 Implant Drops

19. Improving Hand-Offs Hand-offs can be improved by incorporating the game team earlier and following up Approach – Share preliminary data insights – Schedule a “Data Insights” meeting – Perform additional analysis – Deploy the change – Schedule a follow up “Data Insights” meeting

20. Owning a Data Model Overview – The data team develops a model that provides input to an in-game mechanism – On a daily or weekly basis, the game team ingests a targeted user list Examples – DCUO Nudge System – PlanetSide 2 Tutorial Targeting

21. Improving Owned Models Issues – Manual data hand-off – Multiple failure points – Model is a black box to the game team Recommendation – Automate as much of the process as possible and allow game teams to run competing approaches

22. Sharing a Data Model Overview – The data team builds and validates the models – The game team implements the models in-game Examples – EverQuest Landmark Recommendation System – PS2 Nudge System

23. Landmark’s Recommendation System

24. Improving Shared Models Work with the game team to make lots of parameters available for the models Implement fall-back approaches in case the models fail Use a modular approach for implementing the model rules and parameters

25. Showing ROI Results Overview – The data team performs analysis that does not require work from the game team – The results are shared with the game team and used to plan for future campaigns Examples – A/B testing email campaigns – Advertising on PSN

26. Summary Meeting Types – Analytics 101 – Data Scrum Meetings – Data Insights Meetings – Monthly Business Reviews Interaction Approaches – Hand-off the results – Own a data model – Share a data model – Show ROI results

27. Questions What data to share with game teams? – All the KPIs and more detailed analysis as needed When and how to share data? – Regularly through automated reports, scrum meetings, and data insights meetings How to operationalize your data? – Meet early with preliminary data, develop an action plan, and follow up with more data

28. Thank You Ben Weber Director of BI & Analytics Daybreak Game Company DaybreakGames.com @bgweber

29. Holding Effective Data Meetings Ben Weber Daybreak Game Company