Understanding pedestrian movement is a tenet of urban design, crucially linked to the viability of urban spaces. As such, a subset of this discipline focuses on the frameworks for modelling and simulating such behaviours. Designers traditionally employ pedestrian simulations to achieve this. However, these tools, such as Mass Motion and Legion, miss a key consideration: humans are social beings. Pedestrian movement is strongly influenced by the social characteristics of space and the social nature of others. This research investigated a novel, socially driven pedestrian simulation tool developed by the authors, called Kova PedSim (formerly H.I.V.E.), a Grasshopper3D plug-in which integrates social behaviours as a key algorithm to simulate human movement. The authors conducted a series of experiments using Kova PedSim which compared the performance of socially driven pedestrian simulations and traditional ones to quantify the benefits of such an approach. The presented work showcased the importance of embedding social characteristics into digital workflows. Using Kova PedSim, designers gain access to previously undiscovered metrics, allowing them to leverage new data-driven insights. This enables the opportunity to evolve beyond using pedestrian simulations as simply analytical tools and rather as generative workflows to meaningfully embed humanistic dimensions within the design process.