Cannibalization Analysis

Cannibalization analysis is a spatial modeling technique used in retail and franchise planning to quantify the revenue impact that opening a new location has on nearby existing stores within the same network. When a brand expands into a market where it already has a presence, some of the new store's sales will inevitably come from customers who previously shopped at another branch rather than from genuinely new demand. Understanding and predicting this overlap is essential for making profitable expansion decisions.

Cannibalization models typically combine trade area definitions, gravity models, and customer origin data to estimate the share of demand that a proposed site would capture from sister locations. Analysts first define the trade areas of all existing stores using drive-time isochrones or customer address data. They then overlay the proposed new store's projected trade area and calculate the degree of geographic overlap. The higher the overlap, the greater the expected cannibalization. Sophisticated models also factor in brand loyalty, trip purpose, and competitive alternatives—if no competitor fills the gap, customers may simply redistribute among brand-owned outlets rather than switch to a rival.

The primary output is a cannibalization rate, expressed as the percentage of the new store's projected revenue that is diverted from existing stores. Analysts also track net incremental sales—the portion of the new store's revenue that represents truly new demand. A healthy expansion target typically has a cannibalization rate below 20–30 percent, though acceptable thresholds vary by industry and strategic goals. Some brands deliberately accept higher cannibalization to increase market density and defend against competitors.

Cannibalization analysis is used extensively in retail site selectionSite SelectionSite selection is the analytical process of evaluating and choosing optimal physical locations for new stores, facili..., franchise territory planning, and restaurant network strategy. Quick-service restaurant chains, grocery retailers, and convenience store operators rely on it to balance market coverage against revenue dilution. It also informs decisions about store closures and relocations—if two underperforming stores heavily cannibalize each other, consolidating into one optimized location may yield better results.

Accurate cannibalization modeling requires granular customer data, realistic trade area definitions, and assumptions about consumer switching behavior that can be difficult to validate. Markets with highly mobile consumers, overlapping commute patternsCommute PatternsCommute Patterns analysis examines home-to-work travel behavior including origins, destinations, modes, distances, an..., or strong destination-driven trips add complexity. Models must also account for the dynamic nature of retail—competitor openings, road network changes, and shifting demographics can alter cannibalization patterns over time. Cannibalization analysis remains an indispensable safeguard in retail expansion strategy. By quantifying the internal competitive dynamics of a store network, it enables brands to grow market share without undermining existing investments, ensuring that each new location contributes genuine incremental value.