In Part II, Chapter 6 highlighted concerns about the methodological robustness of Strategic Housing Market Assessments (SHMAs), which serve as a key source of evidence for local housing policy in the UK. Building on that discussion, this chapter explores the potential of Google Trends relative search volume (RSV) data to improve the analysis of factors affecting house prices—an important input for forecasting housing needs. Specifically, the chapter examines 14 districts as case studies to analyze the relationship between online search activity related to local real estate markets and house prices. The regression model incorporates RSV as a proxy for public attention to the housing market, alongside control variables such as population, mortgage interest rates, average income, and new housing supply. The results suggest that RSV data can be used to quantify area-specific interest in housing markets and, when combined with conventional indicators, can enhance the analysis of house price dynamics and support more informed estimates of housing needs.