This article discusses the use of z-scores in geospatial analytics to measure and rank locations. It explains how to calculate an index score by standardizing features, weighting variables, capping values, compiling variables, and yielding a final score that can be easily interpreted by business users. The article also explores advanced visualization techniques using BigQuery and CARTOframes, allowing for the creation of heat maps and interactive maps that provide valuable insights into location-based data. By following the steps outlined in this article, data scientists and analysts can simplify the process of measuring and ranking locations, providing actionable insights to inform business decisions.