In the fast-paced gaming industry, providing seamless access to support services is imperative. However, players often face a multitude of issues, ranging from account management to game inquiries and payment concerns. This complexity called for a solution to streamline issue identification and resolution.
To address this challenge head-on, we harnessed the power of Artificial Intelligence (AI) to craft an advanced Machine Learning (ML) data model. This model is designed to identify the six most prevalent issue types (intents) for a selected product, leveraging a rich database of historical case data.
ML Data Model Development: We applied cutting-edge AI techniques to meticulously design and develop the ML data model.
Weekly Data Harvest and Analysis
A scheduler orchestrates a weekly data harvesting process, extracting historical case data from the Salesforce/Analytics database.
Issue Type Profiling
Our data model thoroughly scrutinizes the gathered historical cases, pinpointing the most frequently encountered issue types (intents) for each product.
The implementation of this visionary solution led to a paradigm shift in player satisfaction and issue resolution efficiency. Players now navigate a streamlined selection process, with the most pertinent issue types prominently displayed at the forefront of the selection page. This optimization resulted in a significant reduction in player journey time, ultimately leading to heightened satisfaction levels and enhanced operational efficiency. For a deeper exploration of this case study or to discover how similar solutions can be customized for your gaming enterprise, please don’t hesitate to reach out to us. We’re eager to share more insights and explore potential collaborations with you.