The random walk with choice is a well known variation to the random walk that first selects a subset of $d$ neighbours nodes and then decides to move to the node which maximizes the value of a certain metric; this metric captures the number of (past) visits of the walk to the node. In this paper we propose an enhancement to the random walk with choice by considering a new metric that captures not only the actual visits to a given node, but also the intensity of the visits to the neighbourhood of the node. We compare the random walk with choice with its enhanced counterpart. Simulation results show a significant improvement in cover time, maximum node load and load balancing, mainly in random geometric graphs.