Despite the importance of evaluating all mitigation options to inform policy decisions addressing climate change, a comprehensive analysis of household-scale interventions and their emissions reduction potential is missing. Here, we address this gap for interventions aimed at changing individual households’ usage of existing equipment, such as monetary incentives or feedback. We perform a machine learning-assisted systematic review and meta-analysis to comparatively assess the effectiveness of these interventions in reducing energy demand in residential buildings. We extract 360 individual effect sizes from 122 studies representing trials in 25 countries. Our meta-regression confirms that both monetary and non-monetary interventions reduce energy consumption of households, but monetary incentives, of the sizes reported in the literature, tend to show on an average a more pronounced effect. Deploying the right combinations of interventions increases overall effectiveness. We estimate a global carbon emissions reduction potential of 0.35 Gt CO2 yr-1, though deploying the most effective packages of interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation pathways with energy demand reductions.