BUILDING A DATA DRIVENCOMPANY

Maciej MrózCEO, Ganymede

WWW.GANYMEDE.EU

WHO WE ARE

• Online gaming company in Kraków, Poland

• about ~80 people and quickly growing

• big portfolio of free to play games, focused on social casino

• Not a large corporation• still try to keep things simple and

efficient

• cannot operate like a garage company any more

WHY FOCUS ON DATA?

• Happy and engaged players• that’s the only way to make money

in the long run!

• You can’t do focus tests with 100s of thousands of players

• We can build anything, but howdo we know what to build first?

• Data is our feedback loopand a guide for the future

IT’S MORE THAN „BIG DATA”

• It’s not about how much data you have

• worry about limits when you hit them

• Extracting value is the hard part

• It’s not just a set of tools ora department, it’s a way of thinking

ENTIRE COMPANYIS AFFECTED• Market research/greenlight

• Product development

• Operations• KPI optimization (retention,

monetization ...)

• user research

• community management

• user acquisition

• Portfolio management

• ...

DATA CULTURE

• Why are we doing this?

• What are our assumptions?

• How can we validate?

• What are target metrics?

• Quicker, smaller scale experiment?

DATA CULTURE

• What have we learned?

• If it seems similar to Lean Startup, it should

INCLUDE EVERYONE

• This is not just for data engineers and analysts

• Everyone has access to raw data

INCLUDE EVERYONE

• 90% of data analysis problems is simple• Basic SQL or scripting skills are often

enough

• Give people opportunity to just do it, and not wait for someone else

• Benefit of high tech talent density

TEAMS ARE IN CHARGE

• Beyond basic stuff, it’s up to gameteam to decide whatand how to track• tightly coupled game/ui design

• typically part of „Definition of Ready”

• team maintains their own dashboard with custom metrics

TEAMS ARE IN CHARGE

• Having data engineering/analytics skills embedded in the team is always beneficial

• this is what we want in the long run

• Basic tasks can be done by any developer

• just put these in the sprint backlog

EXPERIMENT!

• A lot of A/B testing• our own tools, but you can use anything

• it’s ok to try out different things

• you can test much more than button colors

• Make sure you learn something new about your players

• Experiment on real users, too!• numbers are not everything

COMMUNICATE

• Information should reach right people at the right time

• harder than it sounds, especially as company grows

• Sprint review

• Meetings of interest groups• product Owners, Analysts, Community

Managers, ...

COMMUNICATE

• Dashboards• we are working on improving these

• Confluence for knowledge base/product documentation

• Internal newsletter

BE SERIOUS ABOUT DATA

• It’s an investment, and long term one!

• Data engineering team• build and operate our data tools and

infrastructure

• set instrumentation standards

• design data schemas

• develop automated workflows

• ...

BE SERIOUS ABOUT DATA

• Dedicated analysts• shared across the company out

of necessesity

• for our biggest games, we are heading towards dedicated analyst per team

• Infrastructure• whether you go with cloud

or physical, it does not come free

AUTOMATION

• Repeatable tasks shouldn’t be a burden

• Standard KPIs across product portfolio

• it’s very important to share definitions and calculate them in exactlythe same way

AUTOMATION

• Common platform and instrumentation standards

• In exchange:• Dashboards with standard

KPIs,

• Reporting,

• A/B testing

• All from day one on every game

OUR TOOLS

• Different tools for different contexts

• We are using mostly open source• Hadoop ecosystem: Hive, Pig, luigi

• Python for complex processing

• SQL – still very useful, but often underestimated

• Custom dashboards for visualization

THIRD PARTY SOLUTIONS

• Can cover 80-90% of your needs almost instantly

• Should be default starting point

• pick one that offers raw data access (i.e. throughAmazon Redshift)

THIRD PARTY SOLUTIONS

• We still use some of them

• Our business is games, not analytics technology!

INFRASTRUCTURE

• Amazon EC2• Data collection (custom solution,

Python + scribe)

• Basic KPI calculation (Python, ephemeral instances)

• Amazon S3• Raw data storage (gzip compressed

JSON event logs)

INFRASTRUCTURE

• Hadoop cluster for complex analysis/warehousing

• used to be a single beefy machine for a long time

• way forward because of data volume

FUTURE DIRECTIONS

• CRM functionalities in gaming platform

• Predictive models• player life time value most obvious

choice

• plenty of other possibilities

FUTURE DIRECTIONS

• Standardizing our workflows on top of Hadoop

• maintainability and talent availability are issue with homegrown solutions

• for us data volume is too big to process in timely manner on single machine

DON’T GIVE IN TO HYPE!

• Start small and ignore the buzzwords

• You can achieve a lot on a desktop PC

• if you can import CSV into Excel you can do suprisingly much

• I suggest using Python or R – easierto validate/maintain in the long run

DON’T GIVE IN TO HYPE!

• Investment in data should have positive ROI

• Different things make sense at different scales!

CREATIVITY MATTERS!

• We are in this industry to build great experiences!

• If your game isn’t fun, do back to drawing board

• data can help you, but will never fix your problems

CREATIVITY MATTERS!

• Gut feeling and experience are still valuable

• It’s ok to experiment!• as long as you validate it afterwards,

learn from mistakes, and iterate

www.ganymede.eu

mmroz@ganymede.eu

@maciejmroz

THANK YOU!