We will present the data from our localization user surveys, share best practices and potential pitfalls and explain how we have used the feedback to improve our localization program and increase the support of our stakeholders.We will introduce our set-up (What did we ask the players and how?), share our major findings (What were the survey results?) in words and numbers, and how different aspects of localization were affected. We will give insight on the action points we took as a consequence and how successfully we involved our stakeholders.
We are looking forward to discussing our lessons learned, pros and cons of player surveys, and your own experiences, input and ideas for further improvements.

Building up on the knowledge we previously shared at Game Global, the presentation will focus on a case study on FIFA and other Franchise specific titles to highlight how much you can improve the quality by creating specific MT engines with the data of the game.
We will share some details in terms of processes to prepare the engines, but especially a quality comparison between text translated with a generic engine and a text translated with a specific engine.

In this presentation we will introduce our EA Data Analytics team focus: how to approach machine learning strategies, player data and data infrastructure in order to radically change Localization towards a data driven business strategy.
We will discuss how to develop a data strategy as well as the connection between game development and localization.