The Problem
A major casual gaming producer had successfully completed its first third-party partnership and was looking to expand both its partnership pipeline and its ad sales efforts. To pursue either effectively, the team needed objective data about who their players were beyond gameplay metrics alone, specifically what products, services, and brands they engaged with in their everyday lives.
Without this visibility, the team had no credible foundation to bring to prospective brand and advertising partners, and no reliable way to assess which partnership opportunities would offer genuine value to their audience.
The Approach
Designed and fielded a large-scale survey among existing players:
– Recruited over 21,000 players through in-game notifications distributed across day parts.
– Developed a structured survey covering reward type interest, earning activity willingness, purchase behaviors, retailer and restaurant visitation, and digital subscription usage.
– Segmented findings by key player types to surface behavioral and lifestyle differences between players within the core ecosystem and those who also engage with outside gaming platforms.
The Results
» Established detailed demographic and behavioral profiles of the core player base, giving the team a data-backed story to bring to prospective brand and ad partners about who they would be reaching.
» Mapped the consumer categories and retailers most relevant to players, with grocery and food, a dominant national online retailer, and streaming services emerging as the strongest targets for partnership and advertising conversations.
» Identified reward preferences and earning behaviors, equipping the team with insight into how to structure partnership offers that would genuinely resonate with players.
» Profiled players active outside the core ecosystem, expanding the range of partners the team could credibly approach with audience-fit data in hand.
Did You Know...
Comparing how different groups of respondents answer the same questions can reveal meaningful differences that aggregate data masks entirely. A single dataset becomes far more valuable when you take the time to look at how distinct audience segments diverge in their behaviors and preferences.
