Quantic Foundry collects data through an online survey (Gamer Motivation Profile) with a sample of over 350,000 players. Their data is primarily based on behavioral data from two specific games: Ultima Online and Everquest. While their survey demonstrates strong psychometric properties, there are legitimate concerns about the representativeness of their sample across different player segments and game genres.
Key Difference: Solsten’s use of machine learning and adaptive assessment is distinct from Quantic Foundry’s static surveys and limited data sources. This suggests a more sophisticated, efficient, and broadly applicable data collection process that results in detailed, actionable, unique, and evolving player profiles across various game types.
Motivational Models
Solsten’s approach is grounded in psychometric research and uses adaptive psychological assessments to measure over 250 traits, including personality, values, and intrinsic motivations. Solsten captures the underlying psychological drivers of player behavior, rather than simply describing observed preferences. The adaptive psychological assessment that this data is derived from is scientifically valid, and rigorously developed and maintained to ensure effectiveness across different gaming contexts.
On the other hand, Quantic Foundry’s motivational model consists of 12 motivations grouped into three clusters: Action-Social, Mastery-Achievement, and Immersion-Creativity. However, some of these constructs, such as “Destruction,” “Competition and Community,” and “Design” are not intrinsic motivations — they are behavioral preferences, preferred gameplay styles, or gameplay tendencies.
Since motivations are meant to explain and understand behaviors, conflating the two can be problematic for developers seeking to understand the core drivers of player engagement. Quantic Foundry’s model is based on analyzing behavioral data from a small handful of games, and may have limited applicability to other game genres and audiences.
Key Difference: Solsten’s motivational model is more psychologically grounded, focusing on intrinsic motivations rather than observed behaviors. This approach provides a more adaptable and universally applicable framework for understanding player motivations across different game contexts, giving Solsten a distinct advantage over Quantic Foundry in this area.
Scope of Services
Solsten provides a wide range of services, including adaptive psychological assessments, unique profile creation, and resonance prediction. Solsten’s data goes far beyond demographics and motivations to include affinity data about brands, media, interests, and services, which is highly valuable for marketing teams and for discovering partnership opportunities. Solsten also offer a robust games user research department that provides comprehensive, scientifically-grounded research that optimizes games at every stage.
Quantic Foundry primarily offers player motivation surveys and audience profiles, with less clarity on additional services like consulting or ongoing support.
Key Difference: Solsten’s extensive data offerings and suite of AI-powered, psychology-driven tools and services provides a broader scope than Quantic Foundry, allowing Solsten to impact all aspects of game development and optimization.
Actionability of Insights
Solsten emphasizes the actionability of insights, highlighting an ability to predict and measure future outcomes, such as player LTV, community impact, and resonance. Solsten provides specific examples of how the data provided can be used to inform game design, such as procedural level generation, dynamic difficulty adjustment, and personalized offering models. All of this information is accessed on Solsten’s web-based software.
Quantic Foundry provides detailed player motivation profiles benchmarked against their database, along with game recommendations tailored to different preferences. Their outputs come in the form of a downloadable report and static online dashboard.
Key Difference: Solsten’s focus on predictive analytics and concrete applications provides an edge over Quantic Foundry in terms of the actionability of insights. The interactivity and depth of the software’s capabilities is also superior to Quantic Foundry’s static reports.
Technology and Tools
Solsten’s technology stack revolves around an AI-powered in-game adaptive assessment, player clustering, and predictive analytics. Solsten highlights the robustness and scalability of the machine learning models, which continuously learn and improve over time. Solsten also provides APIs and integration options for game developers to leverage insights directly within their games. This unlocks vast segmentation opportunities. For example, developers can see detailed psychological and motivational data on their highest LTV audience, which can then be used to market to likeminded individuals.
Quantic Foundry uses an online survey platform for data collection and statistical analysis tools like factor analysis for model development. However, they do not feature data reporting and integration capabilities.
Key Difference: Solsten’s emphasis on advanced AI technology and seamless integration with game development pipelines sets them apart from Quantic Foundry in terms of their technical capabilities.
Return on Investment
Quantic Foundry may offer a lower initial cost, but their limited insights often result in minimal impact on game performance. Developers frequently find themselves unable to translate Quantic Foundry’s broad categorizations into meaningful design improvements.
Solsten’s comprehensive approach, while potentially requiring a larger initial investment, consistently delivers substantial returns. By providing deeply actionable insights and ongoing support, Solsten empowers developers to make data-driven decisions that significantly boost player engagement, retention, and monetization.