20-22 September , 2016 | London

Day One Agenda

08:15 - 08:55 Registration & Networking Coffee

08:55 - 09:10 Gaming IQ Welcome

09:10 - 09:50 Successes, Struggles and Lessons Learned in Growing a Data Science Team to get Great Business Impact at King

Vince Darley, Chief Scientist,King
  • How can you bring science and art together into a great product?
  • Don’t get distracted by the wrong metrics; focus on your real customers
  • Is machine learning and predictive analytics really that important?
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Vince Darley

Chief Scientist
King

09:50 - 10:30 Massive Analytics for The Division

Alzbeta Kovacova, Analytics Manager,Massive Entertainment
  • Lessons learned from The Division launch
  • Measuring impact of game features and testing hypotheses
  • Helping game design to position and create new DLCs
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Alzbeta Kovacova

Analytics Manager
Massive Entertainment

10:30 - 11:00 Networking Coffee Break

11:00 - 11:40 Leveraging Machine Learning to Enhance the Bread and Butter Tasks

David Armstrong, Head of Business Intelligence,Radiant Worlds
  • Cluster analysis using K-Means
  • Predictive churn/retention using classification trees
  • Demographic Predictions based on in-game behaviour
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David Armstrong

Head of Business Intelligence
Radiant Worlds

Analytics is evolving, in terms of tools, techniques and the attitude, culture and use of it within studios and publishers. Let’s discuss, as a group, the future of analytics from the perspectives of:
  • Models and techniques – where should we be focusing our time (and budget)?
  • Tools and software – are there new solutions on the market which we could use?
  • People and culture – possibly the biggest aspect of this, how do we continue to develop internal relationships and nurture a data-driven culture?
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Christoph Safferling

Head of Game Analytics
Ubisoft Blue Byte

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Vince Darley

Chief Scientist
King

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Joel Graham

Head of Analytics (RuneScape)
Jagex

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Volodymyr Kazantsev

Head Of Data Science
Product Madness

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Marc Canaleta

CTO
Social Point SL

12:20 - 13:40 Networking Lunch

13:40 - 14:20 Case Study: Business Intelligence at Miniclip

Paul Bugryniec, Head of Business Intelligence,Miniclip
  • Paid and Organic traffic
  • What is K?
  • Methods of calculating K and areas to cover in future and unique challenges
  • LTV calculation and prediction
  • Working with Marketing teams
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Paul Bugryniec

Head of Business Intelligence
Miniclip

14:20 - 15:00 Starting from Nothing: Building Data into a New Project

Kirsti Laurila, Senior Data Scientist,Rovio Entertainment Ltd
  • Description of how analytics is involved in building a new consumer service from scratch
  • Impact of having analytics as a part of a new project from the day one
  • Challenges of building (scalable) analytics without any data
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Kirsti Laurila

Senior Data Scientist
Rovio Entertainment Ltd

15:00 - 15:30 Networking Coffee Break

Roundtable A

15:30 - 16:20 Machine Learning and Automation: What, When and Worth It?

Roundtable B

15:30 - 16:20 Developing and Nurturing a Data-Driven Internal Culture

Roundtable C

15:30 - 16:20 Predictive Analytics: What Can We Really Predict?

16:20 - 17:00 Trials and Tribulations Exploring the Development of Spotify’s Data Platform

Fabian Alenius, Product Lead, Data Infrastructure,Spotify
  • Challenges associated with operating one of Europe's largest data platforms
  • The cloud - there and back again
  • How to extract value from data
  • Lessons learned working with data at Spotify over the last 5 years
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Fabian Alenius

Product Lead, Data Infrastructure
Spotify

17:00 - 23:59 Chairman's Summary & Close of Day One