The financial consequences of opening a retail store in the wrong location are far steeper than most small business owners anticipate – and the data tools that could reduce that risk have historically been priced for enterprise retailers, not independent operators.
According to Carter Russ, Co-Founder & CEO of CenterCheck, the average cost of closing a failed retail location runs roughly $1 million when all exit expenses are accounted for. That figure includes inventory write-downs, lease break penalties, employee severance, and losses from selling unsold stock at a discount. For a small business owner who has invested personal savings into a second or third location, a single wrong site selection decision can be financially ruinous.
The Expense Stack Owners Miss
Most operators focus on the upfront investment rather than what it costs to close down Russ says. When a store underperforms and must close, costs compound quickly. Inventory that cannot be sold at full price must be marked down or written off. Leases typically carry early termination penalties. Employees may be owed vacation pay or severance. Money spent building out the space is rarely recoverable.
“It’s expensive to fail,” Russ says. “You have inventory write-down costs, often penalties for breaking a lease, markdown costs. You might have to let employees go and pay hazard pay, vacation pay. It’s about a million dollars on average to fail, which is an insane number.”
That figure carries particular weight in the current economic environment. Russ points to rising cost pressures across the consumer economy as evidence that businesses are operating with less room for error than at any recent point. “Everyone’s dollar goes less far than it used to,” he says, pointing to Spirit Airlines as an example of how a short window of rising costs – in that case, a few months of higher fuel prices – can be enough to sink even a familiar, long-running business.
For small and independent retailers, the buffer is thinner still. A single location that fails to generate sufficient revenue does not just drag on the business – it can destabilize profitable existing stores by consuming capital and management attention.
The Data Gap That Chains Don’t Have
Large retail chains employ data scientists, maintain proprietary customer databases, and model market capture across geographies before committing to a lease. That analytical infrastructure allows major chains to open hundreds of locations with relatively predictable performance outcomes.
Independent operators and small multi-unit owners have no equivalent. They rely on broker recommendations, personal observation, and general market intuition – the same qualitative inputs that characterized retail site selection decades ago.
Russ describes conversations with small business owners that illustrate the stakes. “We talk to local mom and pops all the time that are like, I’m starting my third store and I just really don’t want to get it wrong,” he says. “I have two successful stores. If I start a third one in the wrong space, it’ll bankrupt me or ruin me.”
The gap between what large chains can assess before signing a lease and what independent operators can access has always existed. But as the cost of failure rises, that gap becomes harder to absorb.
Why Errors Cost More Now
Online ordering has permanently altered shopping patterns, compressing the revenue potential of physical locations that cannot offer a compelling in-store reason to visit. At the same time, operating costs – labor, inventory, occupancy – have risen. The combination means that a store needs to perform closer to its potential from the outset, with less runway to build a customer base.
Russ says this makes the quality of the initial location decision more consequential than it has been in recent memory. A location that might have been marginally viable a decade ago – generating enough revenue to cover costs while building traffic – may no longer be sustainable under current conditions.
He also notes that the relationship between physical retail and online commerce adds complexity to how operators should evaluate market opportunity. A neighborhood that appears underserved by physical retail may already be heavily penetrated by e-commerce delivery, reducing the addressable customer base for a new store. Without data on how consumers in a given area are actually spending, that distinction is nearly impossible to assess from the outside.
Turning Transaction Data Into Estimates
CenterCheck is one example of this kind of tool. It pulls store-level transaction data from card networks and bank partners to estimate a location’s sales volume, customer demographics, and nearby competition.
Russ says the underlying shift is that this kind of data no longer requires the internal infrastructure that only major retailers could justify building. Platforms like his aggregate the data instead, making it available to operators evaluating a single lease rather than a national portfolio.
That distinction matters. Where broker walkthroughs and foot traffic offer a general impression of an area, transaction data reflects what people are actually spending nearby, and on what. The technology doesn’t remove the risk of opening a new location, but it changes what information is available before signing a lease.
About the Expert: Carter Russ is a Co-Founder and CEO of CenterCheck, a platform that estimates store-level retail sales performance using aggregated card and debit transaction data.
This article is intended for informational purposes only and does not constitute legal, financial, or investment advice. The views and opinions expressed herein reflect those of the individuals quoted and do not represent an endorsement of any company, product, or service mentioned. Readers should conduct their own due diligence and consult qualified professionals before making any investment decisions.
