Site Selection

Site selection is the systematic, data-driven process of identifying, evaluating, and choosing the best possible geographic location for a new retail store, restaurant, warehouse, office, healthcare facility, or other physical operation. It is one of the highest-stakes decisions a business makes—a well-chosen site can generate strong returns for decades, while a poor choice can result in years of underperformance and costly lease obligations.

A typical site selection workflow begins with market screening—ranking metropolitan areas, cities, or regions based on strategic criteria such as population size, growth rate, competitive intensity, and brand awareness. Within selected markets, analysts define target micro-markets or trade areas using demographic thresholds, traffic patterns, and competitive gaps. Specific available properties are then sourced from commercial real estate brokers and databases. Each candidate site is evaluated against a scorecard of quantitative and qualitative criteria, often supported by predictive sales models.

Site evaluation typically considers: trade area demographics (population, income, household composition, lifestyle segments); competitive environment (number, proximity, and format of direct and indirect competitors); accessibility and visibility (proximity to major roads, transit, parking availability, signage visibility); co-tenancy (presence of complementary traffic-generating businesses); real estate factors (rent, lease terms, building condition, zoningZoningZoning is a land use planning tool that divides geographic areas into zones with specific permitted uses, building st...); and modeled sales potential (predicted revenue based on analog stores, gravity models, or machine learning algorithms).

Modern site selection employs a range of analytical techniques including gravity and Huff models for trade area delineation and sales forecasting, analog analysis that identifies existing stores with similar characteristics to benchmark performance, regression models that quantify the relationship between site attributes and sales outcomes, and machine learning models that detect complex nonlinear patterns in large datasets. GISGISGeographic Information Systems (GIS) enable users to analyze and visualize spatial data to uncover patterns, relation... platforms provide the spatial analysis and visualization backbone, enabling analysts to layer and interact with dozens of data variables simultaneously.

Site selection is practiced across virtually every industry with a physical footprint: retail chains, restaurant groups, grocery operators, banks and credit unions, healthcare systems, fitness brands, automotive dealerships, and industrial logistics companies. The principles apply whether selecting a single flagship location or optimizing a network of hundreds of outlets across a country.

Site selection must balance quantitative rigor with practical constraints—the theoretically optimal location may not have available real estate, or lease terms may be prohibitive. Data limitations, especially in emerging markets or for new-to-market brands without analog stores, increase forecasting uncertainty. The long-term nature of real estate commitments means that analysts must also consider how trade areas will evolve over 5–10 year lease horizons. Site selection represents the ultimate application of location intelligence—synthesizing demographic, competitive, accessibility, and real estate data into a single decision that directly impacts business performance. Organizations that invest in rigorous, data-driven site selection consistently outperform those that rely on intuition, anecdote, or opportunistic deal-making.