The gaming industry has seen considerable growth over the past years and has outperformed even the Box-Office ($42.5b) and Music ($20.2b) combined last year to emerge as the most prominent form of entertainment. Analysts predict gaming to generate more than $260 billion in revenue by 2025. Quality data management and analytics have the prima donna influence in aiding gaming companies to make critical business decisions by gaining better knowledge about the players and providing vital insights to marketing, game development, and design. Analysing the data unravels information about players’ psychology, demographics, and behaviour, all of which can shore up business intelligence and decision-making. Data analysis can even help companies prevent disruption due to system errors and quickly react to system breakdowns. For example: With more than a million new installations per day, a mobile gaming company used to push special offers automatically and in-app cross-promotions across various channels. These ongoing special offers and cross-promotions resulted in app purchases and hence were important for the company to achieve the revenue objectives. But a glitch during the mobile update resulted in the promotions and offers not being shown to users. Thus, the company lost opportunities to cross-sell and upsell to new and existing players. As the company had over a million new installations each day, the system glitch and lack of promotions due to it resulted in less app purchases resulting in around 15% loss in revenue. If the gaming company had used data analytics to immediately track dip in app purchases using automatic alerts or intuitive Business Intelligence dashboards, then this could have prevented the loss. Efficient and timely tracking of data around promotional metrics, installations, and revenue could have averted this revenue loss for the company. From the above example, we can see how data analysis can enable gaming companies to attain business objectives. Still, complications begin to surface when they must process data about multiple events and combine it with other data like player payment/marketing data to get insights to uncover opportunities for revenue maximization. It is challenging for gaming companies to collate the massive amount of varied data generated across different sources. Managing tedious data retrieval tasks like decompression, decryption, structure validation, error handling, auditing, etc., complicates data management. Read More to know how data analytics strategy, an effective data engineering strategy facilitates running, growing, and transforming the gaming business by ensuring clean, consistent, and reliable data.
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