Building on 25 years of research, this paper provides an alternative approach for direct real estate investors seeking to add alpha to their broadly diversified property portfolios. First, one must simplify the landscape by grouping 128 different Combined Statistical Areas (“CSAs”) into eight distinct “clusters” of similarly performing metros. Once the clusters are defined, the problem of identifying and acting on trends becomes data-driven, quantifiable, and easier. By deemphasizing the conventional idea of geographic proximity, one then focuses on cities with economic and demographic profile “proximity” to identify correlations and actionable trends. This approach provides visibility into various performance tendencies occurring repeatedly in multiple locations and property types over numerous economic cycles. The ultimate goal is to achieve an optimally diversified portfolio to maximize returns while mitigating risk.