Focus group discussions (FGDs) differ from other qualitative data collection techniques because they offer unique insights into how collective sense-making occurs in real time in social settings. However, systematic qualitative tools to analyze interaction in FGDs and the richness of data it yields remain scarce. In this article, we propose a seven qualitative indicator model, adapted from previous studies on FGD data quality, to assess group interaction. We apply the model to FGDs ( n = 12) conducted via the instant messaging application WhatsApp as part of a study on access to social protection programs in Colombia conducted during the COVID-19 pandemic. Our findings show that the proposed indicators can assess meaningful interaction as it unfolds in asynchronous online FGDs. Unlike existing tools that examine interaction in online FGDs quantitatively and through a dichotomous understanding (either absent or present), our proposed model seizes the idea of varying types of meaningful interaction: stance-only, basic interaction, and complex interaction. Our results suggest that complex participant interactions can emerge in online FGDs conducted via WhatsApp, therefore situating messaging apps as promising data collection sites for including hard-to-reach and highly mobile populations in research. The proposed qualitative indicators model is a useful tool for assessing interaction in FGDs and provides insights into whether and how collective sense-making occurred.