The "Playtime" Payoff: Steam’s 40% Growth Strategy

Challenge

Steam commands a 75% market share, but optimizing its vast library required a shift from editorial picks to a personalized algorithm that could increase sales despite sparse data where many users purchase but never play their games.

Action

I utilized the SVD algorithm and matrix factorization to transform "hours played" into a 5-tier implicit rating system, filtering out outliers and free-to-play titles to focus recommendations exclusively on high-engagement, revenue-generating content.

Result

The model achieved a 78% precision rate on test data, leading to a projected 40% revenue growth rate and an estimated $477,510 in additional sales.