4011 documents in the collection
The report examines the evolution of game engine usage on Steam from 2012 to 2024, focusing on three engine categories: tier‑1 public engines (Unreal Engine and Unity), other third‑party engines (GameMaker, Godot, Ren’Py), and proprietary in‑house engines. Data from over 13,000 Steam titles reveal that Unity remains the most common engine for new releases, accounting for more than half of all games launched in 2024. However, Unreal Engine has steadily captured a larger share of units sold, surpassing Unity in 2024 with 31% of sales versus Unity’s 26%. Custom engines still dominate high‑volume titles, yet their share has fallen from 70% of releases in 2012 to just 13% in 2024, and from over half of units sold in 2014 to less than 50% in 2024. Unreal Engine’s adoption accelerated with UE5, which now powers 72% of all Unreal projects in 2024 and is behind several high‑profile releases such as *Black Myth: Wukong* and *Palworld*. Smaller engines like Godot have shown modest growth, primarily in indie and niche genres. The methodology relies on VGI’s tagging of Steam titles and sales estimation algorithms, covering games that have sold at least 1,000 units. The report projects continued migration from custom engines to Unreal by 2030, while Unity is expected to face increasing competition from Godot and GameMaker in lower‑budget segments.
The study examines how Apple’s iOS 14.5 and 14.6 privacy updates have reshaped mobile game advertising costs, focusing on 13.5 billion programmatic ad impressions from January to September 2021 across iOS and Android. Games are split into Casual (lower retention, lower lifetime value) and Core (higher engagement, higher lifetime value). CPI trends are measured weekly for three periods: pre‑iOS 14.5, iOS 14.5 to 14.6, and post‑iOS 14.6. Results show a divergent impact: Casual CPI fell 38% on iOS after the updates, narrowing the gap with Android (which rose 16%). Core CPI surged 78% on iOS, while Android Core CPI increased 36%. The rise in Core costs reflects intensified competition for the smaller pool of tracked, high‑value users who opt into tracking. Casual costs declined because many casual players are less likely to opt in, reducing demand for identifiable users. The analysis recommends that marketers allocate budgets toward ROAS‑optimized campaigns, diversify across traffic sources to mitigate volatility, and adopt machine‑learning spend‑optimization tools. The methodology relies on Moloco’s proprietary taxonomy to classify titles and aggregates CPI data across the programmatic ecosystem. The findings apply globally, covering both iOS and Android platforms during 2021, and highlight the need for adaptive strategies in a post‑IDFA advertising landscape.