Worldwide, soil contamination due to industrial activities is a major issue. One method for remediation of contaminated sites is in situ chemical oxidation, where an oxidizing agent is injected into the contaminated soil. Normally, monitoring wells are established in the remediation area for tracking the oxidizing agent. However, wells only provide point information of the injectant spread. This issue can be addressed using cross‐borehole resistivity and induced polarization tomography, by mapping the electrical properties in the entire remediation volume and by deriving, through petrophysical relations, the hydraulic properties of the medium. Here we present a proof‐of‐concept study, performed over one year as part of a larger remediation project, where resistivity and time‐domain induced polarization data were acquired among 10 boreholes, before and after two rounds of injection of oxidizing agents. The time‐lapse resistivity models, obtained through a focusing inversion scheme that favours compact time‐lapse changes, clearly show the oxidizing agent spread as highly conductive anomalies and confirmed by water conductivity measurements in boreholes. The time‐lapse inversions also show spatial variability in the injectant spread, with some areas not reached. The induced polarization data quality decreased significantly just after the injection rounds, because of the decrease in resistivity and induced polarization signal level, so that induced polarization time‐lapse inversions were not feasible. However, the induced polarization data were used for background characterization and to estimate permeability. In particular, there is a good match between the imaged low‐permeability zones and the areas in which the injectant did not spread, identified by the time‐lapse resistivity inversions. Furthermore, geological samples confirm the presence of fine‐grained sediments in the estimated low‐permeability zones. While time‐lapse resistivity tomography may be used for documenting the injectant spread, induced polarization permeability estimates prior to injection can be used to better tailor the remediation in terms of dimension and location of injection filters.