Abstract: This study presents a data-driven attribution model applied in the context of HECJ, employing a novelty technique based on panel data from online and offline channels, including detailed data on social media engagement. It aims to contribute to the extent knowledge in attribution models applied in the Higher Education customer journey (HECJ). Throughout a study case at a Brazilian HEI, a total of 185,631 customer journeys were organized into two data sets corresponding to Covid19 pre-pandemic and pandemic periods. The data are modeled in a graph-based attribution model. The research finds that channels as emails, online chat, call center, sales, and inbound marketing are driving more than 70% of conversions. Instagram, sales promotion, online advertising, and instant messages grew 38% in the pandemic period. The HECJ gets longer, from 3.8 months in the pre-pandemic to 7.8 months on average during the pandemic period. This research provides a practical guide based on the proposed model application that permits a more accurate evaluation of marketing channels in the context of HECJ.