Competitive Intelligence

Competitive intelligence (CI) in the context of location analytics refers to the systematic collection, analysis, and application of information about competitors' physical presence, market positioning, and customer capture. Unlike general business intelligence, location-focused CI emphasizes the spatial dimension—where competitors operate, how their store networks overlap with yours, and what geographic advantages or vulnerabilities exist across a market.

Location-based competitive intelligence begins with building a comprehensive database of competitor locations, typically sourced from points-of-interest (POI) datasets, web scraping, business registries, or proprietary field surveys. Analysts then enrich these records with attributes such as store format, estimated revenue, opening date, and customer reviews. Spatial analysis techniques—including trade area overlap measurement, drive-time proximity calculations, and market share modeling—reveal how competitors position themselves relative to your own network and to unserved demand.

Common CI methods include competitive density mapping, which visualizes the concentration of rival outlets across a market; share-of-market analysis, which estimates how demand is split among competing brands in each trade area; and gap analysis, which identifies locations where competitor presence is strong but your brand is absent (or vice versa). Temporal analysis—tracking competitor openings, closures, and relocations over time—provides insight into rivals' strategic direction and expansion priorities.

Retailers, restaurant chains, banks, and service providers use competitive intelligence to guide site selectionSite SelectionSite selection is the analytical process of evaluating and choosing optimal physical locations for new stores, facili..., defend market share, and plan promotional strategies. A grocery chain might analyze a discount competitor's expansion pattern to preemptively secure sites in threatened markets. A quick-service restaurant brand might use CI to identify trade areas where its main rival has closed locations, signaling potential demand shifts. Real estate teams use CI to negotiate lease terms by benchmarking against competitor location quality.

Competitive data is inherently incomplete—revenue estimates are modeled rather than observed, and competitor intentions are inferred rather than confirmed. Data freshness is another concern, as competitor networks change rapidly through openings, closures, and rebranding. Analysts must also define the competitive set carefully; indirect competitors and emerging formats (such as dark stores or ghost kitchens) may be harder to track but equally important. Competitive intelligence provides the spatial context that transforms raw market data into strategic advantage. By continuously monitoring the competitive landscape, brands can make proactive rather than reactive location decisions, ensuring their network remains well-positioned against evolving threats and opportunities.