This study presents a new model of intelligent pricing that concentrates on using data-driven decision-making (DdDM) as a new approach to hotel revenue management (RM). The study aims to assess the role of DdDM in leveraging hotel RM. The results were divided into three main parts. First, the findings indicated that (traditional data) observations, focus groups and structured interviews achieved the highest manager perceptions degrees, respectively. It is noted that (Digital data) electronic surveys, search engine queries and click stream approximately represent high degrees of perception, respectively. Eye-tracking data represents higher degrees of perception than facial electromyography one. Second, transactional, historical and marketing data approximately represent high degrees of manager perceptions, respectively. Also, hotel distribution sources revealed of the approximately perception to all sources. It was noted that hotel Res centers, integration with Res system, global distribution system and hotel website represent the highest degrees, respectively. Third, there was no significant relation between sources of data and using data-driven decision-making. On the other hand, the types of data, hotel distribution sources and managers' concerns about DdDM have positive and moderate relations with using DdDM. The results showed also, in line with expectations, a significant and positive correlation between using DdDM as an intermediate variable and pricing decisions.