Enhancing Gaming Experience with AI Analytics: A Case Study on King
Technology Category
- Analytics & Modeling - Big Data Analytics
- Cybersecurity & Privacy - Intrusion Detection
Applicable Industries
- Agriculture
- Telecommunications
Applicable Functions
- Maintenance
Use Cases
- Intrusion Detection Systems
- Time Sensitive Networking
About The Customer
King is a leading interactive entertainment company for the mobile world. It is best known for its globally popular game, Candy Crush. Apart from Candy Crush, King has 17 other games in production, including the Bubble Witch franchise, Farm, Pet Rescue, and other minor games. Lukasz Korbolewski, the product owner for business intelligence at King, leads the incident management team. The team is responsible for investigating incidents, assessing the losses incurred, and using data to find the root cause of these incidents. The team's primary goal is to minimize the impact of these incidents on revenue.
The Challenge
King, a leading mobile gaming company, was facing challenges in managing business incidents in real time. The company's most popular franchise, Candy Crush, along with 17 other games, were in production. The incident management team, responsible for investigating incidents and assessing the losses incurred, needed a tool to detect and address these incidents promptly. The goal was to minimize the impact on revenue by spotting incidents as soon as possible. The team was also tasked with monitoring 18 Key Performance Indicators (KPIs) for each game, which amounted to a significant number of metrics. The challenge was not only to monitor these metrics but also to differentiate them based on the platform, build, and country. The existing tools were not sufficient for this task, as they were not adept at detecting subtle anomalies in business KPIs.
The Solution
King adopted Anodot's AI Analytics to proactively address business incidents. Anodot's tool helped King minimize the average time to detect incidents and provided accurate alerting on anomalies. The tool was capable of monitoring a large number of metrics and differentiating them based on various dimensions. It was also efficient in dealing with false positives, a crucial factor for King to avoid unnecessary alerts. Anodot's interface allowed the implementation of business logic for differentiating between an incident and an anomaly using simple settings. The tool was not only used for basic metrics like game starts and ends and transactions but was also expanded to monitor more complex metrics. With Anodot, King was able to decrease the time to detect incidents significantly and implement real-time anomaly detection.
Operational Impact
Quantitative Benefit
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