Case Study: Leading Video Game Company achieves price optimization and 24-month demand forecasting with Grid Dynamics

Price Optimization for Video Games Using Machine Learning

Leading Video Game Company, a major publisher selling games across 70+ countries and multiple platforms and retailers, faced a complex price-setting challenge: hundreds of individual price points, frequent promotions, high price transparency, and uncertainty around new releases. To tackle this, the publisher engaged Grid Dynamics to build an omni-channel demand forecasting and price‑optimization platform using machine learning on a cloud ML platform with an open‑source tech stack.

Grid Dynamics implemented a production solution delivering weekly-resolution forecasts up to 24 months, what‑if promo analysis, and special handling for new releases; the six‑week pilot produced a working model and infrastructure on time before a major launch. The Grid Dynamics forecasts became the price management team’s primary decision‑support tool, were automated with regular retraining and reevaluation, and have been extended across additional franchises—measurable outputs include a 24‑month forecast horizon, one‑week resolution, and a six‑week pilot to production.