This paper introduces a novel approach for analyzing traffic demand variability of 5G/6G mobile backhaul networks across urban, suburban, and rural areas within the wider Riyadh region of Saudi Arabia, emphasizing the tidal-effect phenomenon that influences Quality of Service (QoS) requirements throughout the 24-h of the day. By dividing the region into distinct cells based on geographic and demographic characteristics, we systematically evaluate how traffic patterns fluctuate spatially and temporally, driven by time-dependent user activity patterns and area-specific characteristics. The proposed spatiotemporal traffic demand analysis method serves as a decision-making tool for Mobile Network Operators (MNOs), enabling them to assess the adequacy of existing infrastructure, including cell towers, antennas, bandwidth, frequency spectrum, and redundancies. Furthermore, our proposed method provides actionable insights into optimizing resource allocation, ensuring that network capacity aligns dynamically with fluctuating user demands while minimizing unnecessary capital and operational expenditures. Simulation results demonstrate the importance of understanding spatiotemporal traffic demand variations in maximizing the utilization of network resources. Such that, by identifying peak demand periods and locations, MNOs can proactively allocate resources to enhance performance and coverage where needed the most. Therefore, maximizing Return on Investment (RoI) and enhancing the scalability and future-readiness of mobile backhaul networks for supporting advanced 5G/6G applications.