Most retail location decisions come down to two things: how busy does the street feel, and can we afford the rent?
Those two inputs aren't wrong. They're just incomplete. And the gap between "incomplete" and "correct" is where failed locations live.
Brokers aren't hiding this from you deliberately. They're optimising for a lease, not for your unit economics over five years. The seven factors below are what a rigorous site decision actually requires and what most expansion teams aren't evaluating systematically before they sign.
1. Footfall - but at the right level
Area-level footfall numbers are almost useless for a site decision. What matters is street-level pedestrian volume and specifically, how much of that volume passes your frontage, not just the neighbourhood.
In our pilots across Dutch cities, neighbouring streets in the same city centre showed a 42% vs 31% capture rate difference. That's not a rounding error. It's the difference between a viable and an unviable unit - at the same rent.
The question isn't "is this a busy area?" It's "how much foot traffic actually reaches this address?"
2. Rent efficiency
Rent is only expensive or cheap relative to the footfall it buys you. A unit at €5,000/month on a high-traffic street may be better value than one at €3,000/month on a quieter one.
Rent efficiency - rent per pedestrian, per day - is the metric brokers won't quote you. Calculating it manually requires combining footfall data with listing prices. Most teams skip it. The ones that don't avoid a recurring mistake: paying premium rent for mediocre exposure.
3. Permit fit
This is the factor that causes expensive mistakes, and the one that's most reliably invisible at street level.
Zoning classifications determine what you can legally operate at a given address. A permit class of "Retail" blocks food and beverage - even if the street has eight restaurants and visually reads as an F&B street.
In one of our Haarlem analyses, a unit on a street with eight restaurants scored 0% for F&B - not because of competition, but because the zoning blocked it entirely. A five-year lease on that unit for a restaurant business category would have committed €300,000 in rent before a single customer walked in.
Permit fit is binary. It either works or it doesn't. Check it first.
4. Competitor density - by category
Total competitor count is a blunt instrument. What you need is same-category saturation relative to demand.
A street with 76 fashion stores is hostile to a new fashion business category, even if the footfall score is high. The same street may be wide open for sports and fitness, with zero same-category competitors and strong demographic alignment.
Competitor density only tells you something useful when it's measured against demand for that specific category.
5. Demographics
Footfall tells you how many people pass. Demographics tell you whether they're your customers.
A high-income neighbourhood with strong single-household density looks different from a family-oriented suburb with similar footfall. Neither is better in the abstract - it depends entirely on your business category.
For a boutique fitness studio, the relevant demographic is women aged 20-40 within cycling distance, not total population. Generic demographic data gives you the city picture. What you need is catchment-level alignment with your specific customer profile.
6. Category gap - demand vs supply
Every city has retail categories that are systematically under-served. These aren't obvious from walking the street, because what's missing, by definition, isn't visible.
Category gap analysis looks at the balance between consumer demand signals and existing supply for a given category. A high-demand, low-supply combination is the analytical definition of a whitespace opportunity.
Sports and fitness appeared as a whitespace in three of the four cities, despite being invisible to operators relying on street observation alone. If you're choosing a business category and a location simultaneously, this is the factor that should lead the conversation.
7. Area vitality
A location can score well on all six factors above and still be a poor long-term bet if the surrounding area is in decline.
Area vitality captures trajectory, not just current state: new residential developments nearby, vacancy trends on the street, anchor tenant mix, seasonality patterns. A street with high footfall today but rising vacancy and no growth pipeline is a different risk profile from a lower-footfall street with a 96/100 residential development score within 500 metres.
You're signing a lease for three to five years. The location you sign into today is not the location you'll be operating in by year three.
Why most teams still get this wrong
Each of these factors can, in theory, be researched manually. The problem isn't knowledge - it's data access and time.
Gathering accurate street-level footfall, live permit data, category-specific competitor counts, and demographic catchment profiles for even a shortlist of three locations takes weeks of research across disconnected sources. Most retail expansion teams compress that process under deadline pressure and rely on the two inputs they can get quickly: how busy it feels and what the rent is.
That's how you end up with a location that looked right and performed wrong.
Umut Aykut Celik
Co-Founder, Shareloc
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You now have the framework. The hard part is the data.
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