We applied advanced network optimisation techniques, combining fuel sales data, retail performance, and geospatial analytics to assess site efficiency. Through customer footfall analysis and traffic flow mapping, we identified stations that were high performers and those that were underutilised. Our team also conducted competitor benchmarking, evaluating nearby service stations and alternative fuel options to understand customer movement patterns.

Using these insights, we recommended which stations to upgrade, relocate, or consolidate, ensuring better fuel sales, improved in-store retail performance, and enhanced overall efficiency. We also created a predictive demand model to identify ideal locations for future expansion, ensuring that new sites were positioned to capture maximum traffic. Through geo-analytics and footfall analysis, we identified optimal locations for future expansion and recommended closures for underperforming sites. Our models factored in local demographics, competitor presence, and economic trends to provide a clear roadmap for optimising the store network. We also integrated real-time store monitoring dashboards, giving decision-makers continuous insights into performance.