Beyond recall: exploring how players build brand knowledge through virtual in-game product experiences

Abstract

The objective of this research was to identify the barriers to and enablers of in-game brand learning in order to create a theoretical understanding of how in-game brand learning can be optimised. This was achieved by exploring how different types and frequencies of in-game advertising affect a player’s brand learning and developing an understanding of how they experience the game as well as the advertising contained within it. Employing constructivist grounded theory, the study’s findings are based on deep, rich data gathered through interviews and observations of 20 participants who played a sports video game for approximately 2 hours and a content analysis of the in-game advertisements they encountered during gameplay. Drawing from Keller’s consumer based brand equity model, Csikszentmihalyi’s concept of flow, and Lang’s limited capacity model of mediated message processing, the study develops a holistic, contextualised understanding of the barriers to and enablers of brand learning in console/PC video games, revealing four key insights. First, increased ad exposure does not necessarily increase brand learning. Second, deeper learning occurs with unfamiliar brands. Third, a player’s experience of the game has the most significant effect on brand learning. Finally, players are more likely to filter out advertisements that are not related to their in-game objectives and goals. The findings of this research demonstrate the need to consider factors beyond placement type and frequency when investing in and measuring the effectiveness of in-game advertising and suggest how advertisers can optimise in-game advertising in order to enhance consumer brand learning beyond basic brand recall. They also provide policymakers with a better understanding of how players process in-game advertising and how the medium might be used in order to guide the development of policies in this relatively new area of advertising.