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Data Science and the Games industry

Data Science and the Games industry

I gave a series of talks in 2014 on Data Science in various verticals. This is one from the Game industry.

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springcoil

July 07, 2014
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Transcript

  1. How can Data Sciences benefit How can Data Sciences benefit

    the Game Industry the Game Industry? ? Peadar Coyle Data Science Consultant
  2. What opportunities are there? What opportunities are there? I think

    there are two interesting areas that spring to mind. 1) Marketing analytics 2) Data Science experiments for PR and Marketing purposes (internal marketing and external marketing). Overall the biggest challenge is growth and cultural change.
  3. Marketing Analytics Marketing Analytics 1) Uses gamers play data to

    optimize marketing communications across channels. - Customer segmentation modelling 2) Building Personalization Engine Rules for 1:1 communications with individual gamers. To help reduce customer churn. 3) Predicts gamers likelihood to churn or to respond to up-sell offers.
  4. Personalization emails Personalization emails 1) Everyone is different. 2) Novice

    gamers need different levels of interaction than non- novice gamers. For example I suspect novice gamers may respond to encouraging emails. Experienced gamers may need to hear about Downloadable Content Activision have about 6 million email templates...
  5. Customer Churn Customer Churn One can build a model of

    customer segmentation There are different kinds of churn - customers not using a product versus customers not using a product that is inbuilt There are (or should be) key metrics such as net play time, frequency of play time. Also another interesting thing to measure is 'time to first downloadable content' - I am sure there are some intriguing models here. I hypothesize if you spend money on in game content you are more likely to play the game.
  6. Why these models? Why these models? Better models, allows us

    to make better decisions. I am passionate about using agile software development methods, with lots of feedback to create 'data products'. These can be reports, automated reports, interactive models, data visualizations or data journalism. A data product to me is simply something which covers up data analysis and presents it in a way to allow decisions to be made. Fundamentally our goal is to help customers have a better gaming experience.
  7. Finally: Data Science and PR Finally: Data Science and PR

  8. Thank You Thank You Any questions?