British high streets have endured significant economic and cultural challenges both in the leadup to and as a consequence of the COVID-19 pandemic. The volatile and challenging socio-economic environment has been brought about by the lingering effects of the 2008 recession, high business rates, competition from online retailers, and the impact and implications of the global pandemic. The changes to the high street retail landscape have been recorded using new sources of data that can supplement traditional data sources such as local government retail surveys. New sources of data such as consumer data, property portal data and mobility data are more spatially and temporally granular. As a result, local governments, the retail sector and stakeholders can use these emerging forms of data to create more easily updateable measures of high street composition and performance. This thesis utilises the Local Data Company’s Britain-wide database on retail location, type and vacancy. The data ranges between the start of 2017 and June of 2021, containing around 800,000 records of occupiers. The analysis within this thesis starts by describing the composition and vibrancy of British high streets in the lead-up to the pandemic. Next, the thesis provides an evaluation of the impact of the COVID-19 pandemic and the subsequent shift towards remote working on the viable resilience of commuter towns. This section is followed by an exploration of the short-term impacts of the COVID-19 lockdown restrictions on the resilience of Britain’s high streets. Finally, the application of new forms of data in informing local government high street regeneration policy is studied as part of a knowledge exchange with the London Borough of Camden. This thesis contributes to our understanding of how the circumstances of different British high streets can be monitored and mapped, with the goal of improving understanding of vibrancy, resilience, and potential for regeneration.