As technology advances, more and more industries are adopting data analytics, and the entertainment industry is no exception. This article will explain how this industry can benefit from using Big Data and analytics. 

Data analysis in the entertainment industry

In today’s world, entertainment products and services are increasingly in demand. Although they are not essential services, the need for entertainment is only growing. The active technologization of this sector facilitates it. Today, experts highlight several strong technological trends that determine the vectors for the development of the global entertainment industry. In particular, we are talking about new generation 5G wireless networks, media and data science, artificial intelligence, augmented and virtual reality technologies, blockchain and robots.

Today, data analysis is becoming a necessity for the successful functioning of any company. Based on data analysis, we find relationships, determine dependencies on one factor, draw conclusions, and make forecasts. Data analysis allows you to notice patterns that a person will not see. And, in turn, knowledge about these patterns enables you to change our lives, and in all areas – from the state and telecommunications to the sales and entertainment industry.

More than ever before, entertainment businesses depend on data analysts to optimize and analyze overall performance. Data analytics offers solutions to manage, protect, transform and communicate information to make smarter decisions. With raw data, business analytics generates useful and understandable data that businesses use to reduce risk and cost and increase profitability. For example, developers and producers of video and online games, based on user behavior analysis, change the game’s scenario and design and develop effective promotions. Every day they can analyze 5 Tb of data (start and end of the game, situational user behavior, earned points).

How does it work?

Three key technologies for data analysis are machine learning, data mining, and data management. Machine learning is an aspect of AI that allows software to discover and automate business models. This aspect aims to store and analyze large volumes of data as quickly as possible and obtain results based on models.

Second, data mining takes these large chunks of data and uncovers trends, patterns, anomalies, or correlations between them, allowing companies to answer complex questions more easily and accurately.

Finally, data management offers an established standard for collecting, storing, and managing data quality before a company formally puts it into practice. Together, these technologies largely determine how a company evaluates its competitors. For example, in the hospitality industry, business data analytics gives companies a much more detailed view of what customers, customers, and guests want and how to resolve potential conflicts.

Game Analytics: goals and challenges

Only some games from the start have the necessary potential and balance to succeed. The situation in which gamers investigate graphics and then give up entertainment in the fifth minute of studying is not uncommon. The game analyst must, if not foresee this, then collect and analyze data and make recommendations for action for the development team. Analytics allows you to highlight complex nuances, focus on them, and correct them with the whole team’s efforts to increase the game’s attractiveness in the user’s eyes. For example, if the project does not attract the predicted number of users or many users quit the game after a certain level, the game analyst should find out the reasons for this.  As a result, it is worth indicating the following reasons for the participation of a specialist in the development process:

  • Launching a new project. 
  • Problems with audience retention.
  • The presence of a large number of negative reviews. 
  • Lack of demand for certain game content. 
  • Improvement of an existing product.