This report provides a methodology and summary of results for assessing the temperature sensitivity of residential households across the National Energy Market (NEM), with the intention of providing insights as to whether there are sufficient grounds to base AEMO’s future consumption forecasts on greater disaggregation than they currently are. The approach aggregates the half-hourly electricity consumption of households across all NEM regions into several segments – Dwelling Type, Climate Zone, Dwelling Type x Climate Zone, Greater Capital City Statistical Area (GCCSA), GCCSA x Dwelling Type, and Dwelling Age – before linking these segments to the set of closest available weather station data and using linear regression to determine temperature sensitivity. The linear models also detrend the timeseries data to account for seasonal increases or decreases, so that temperature sensitivity can be calculated without bias introduced by the base increase or decrease to load due to large seasonal shifts (that is, the shift to heating more in winter, or cooling more in summer). The detrended temperature sensitivity is calculated for each of these segments per month and year, per shoulder and peak time interval, and per the three most extreme temperature days throughout summer and winter. The resulting coefficients can then estimate how much each segment might vary their consumption when temperatures fluctuate throughout a month.