fbpx

Background

Companies within the gaming industry are on the rise nowadays, with more than 2 billion players worldwide and more time spent by users playing games. But not all game companies can survive in the market. One opportunity that game companies have to build on the success of their games is by personalizing user touchpoints throughout the user journey. User personalization in games is defined as tailoring the communication and features inside and outside the game to meet the specific needs of each player. With user personalization, game companies can engage with their players to drive retention and increase revenue. There are some processes in creating personalized user experience; user analysis, user segmentation, hypothesis testing, and production. 

Users’ activities generate huge amounts of data on user game genre preferences, games played, user level, playing style, playing behavior, motivation, session frequency and length, purchasing behavior, and so on. Data science plays a vital role in helping game companies identify these data, which lets them build user personalization and increase their success. 

In this session, Data Science in The Gaming Industry, the audience will learn more about how data science helps gaming companies to survive and gain long-term benefits for their success. 

SPEAKERS

Merdyanto , Growth at TentuPlay

Growth enthusiast with product and data backgrounds. Just finished master’s degree in Industrial Engineering at Seoul National University of Science & Technology and Institut Teknologi Bandung (ITB). Merdy started his career at Gojek in 2016 optimizing Go Clean. Then he continued his career at Procter and Gamble (P&G) as a Customization Manager in 2017, where he got many certifications such as SAP, ENOVIA, count more. 

Dwi Gusti Nurdialit, Data Science Instructor at Algoritma Data Science School

Dwi graduated from Master’s degree in Universitas Gadjah Mada, majoring in Physics in September 2020. She is a data science enthusiast with a strong physics background and experience using Python and R. In Algoritma Data Science School, she has been involved in numerous data science training for Algoritma’s clients, including Digital Amoeba by Telkom Indonesia, Perusahaan Listrik Negara (PLN), Badan Tenaga Atom Nasional (Batan), and Direktorat Jenderal Pajak (DJP).

RUNDOWN

  • 15:30 – 15:35: Opening by Moderator
  • 15:35 – 15:40: Panelist Introduction by Moderator
  • 15:40 – 16:00: Presentation by Panelist 1
  • 16:00 – 16:20: Presentation by Panelist 2
  • 16:20 – 16:30: Photo session & Algoritma Introduction
  • 16:30 – 17:25: Talk Show and Q&A session
  • 17.25 – 17.30: Closing