The Retail Gravity Equation: How Close Is Too Close to Competitors?

Conventional wisdom tells retailers to avoid their competitors. The fear is cannibalization; if two coffee shops open too close together, they’ll split the same customers rather than attract more. But the reality is more nuanced.

Retail works like a gravity model: consumers flow toward areas of high retail density, and competition plays a role in shaping those flows. The key isn’t avoiding competitors, but understanding when clustering attracts more customers than it diverts.

Our data at AiCRE Labs shows a surprising pattern: retailers often perform better when located near competitors, up to a point. The effect follows an S-curve. At first, proximity increases visits. Then it plateaus. And beyond a threshold, returns diminish as too many similar stores saturate the market. The trick is knowing where that curve bends.

Take barber shops. A standalone location on a suburban street might rely on local awareness and marketing to draw customers. But place that same barber in a well-established economic district, even next to direct competitors, and market share spikes. Customers in high-density retail clusters aren’t just looking for one option. They’re looking for a category.

The effect varies by industry. Coffee shops see stronger gains from clustering than specialty boutiques. Gyms and fitness studios benefit more from complementary neighbors (like smoothie bars) than direct competitors. And some categories, like grocery stores, are nearly always harmed by over-clustering.

Traditional site selection strategies miss this. They often rely on heuristics—“We need to be at least two miles from another location”—without accounting for real-world patterns. Our model, built on tens of millions of data points, predicts the true optimal distance. For some retailers, it’s 500 feet. For others, it’s five miles.

For landlords, this insight is critical. The wrong mix of tenants leads to vacancies, declining rents, and underperforming centers. The right mix turns a location into a destination.

So, should you open next to your biggest competitor? The answer isn’t always no. It’s: “What’s the optimal range for my category?” A data-driven approach moves beyond guesswork, revealing when competition is a threat—and when it’s an advantage.