One bad location is a mistake. Five bad locations is a pattern that kills a brand.
Every new unit is a bet — rent, fit-out, staff, months of ramp-up. Get one address wrong and you absorb the loss. Get it wrong systematically across a franchise, and you're not building a chain, you're funding parallel experiments with shareholder money.
Here's how we fix that: one call to learn what actually matters for your format, one real address analyzed as a trial, and — if it proves useful — a system built specifically around how your business picks locations.
Why this is more expensive than it looks
A solo café owner can afford to learn from a bad address — one bad lease, one bad year.
A chain can't. The 4th location sets the standard for the 5th. If selection today means "gut feeling" or "whoever liked the photos," that inconsistency compounds — and shows up eighteen months later in same-store numbers nobody can quite explain.
The real cost isn't the rent. It's the fit-out you can't recover, the staff hired for a unit that underperforms, and the brand damage when customers judge you by your weakest location.
Three steps, no commitment until you've seen it work
Step 1 — The call
We ask what actually drives a good location for your concept — not generic foot traffic, but the specific things that make a unit of yours profitable. Lunch-hour office density? Distance from your other locations? Parking for late-night traffic? You tell us, we listen.
Step 2 — The trial analysis (one real address, free)
Give us one address you're actually considering right now. We run it through a scoring logic built around what you told us in step 1 — not our generic public model, but a first pass at your criteria. You see exactly how it scores and why, before paying anything or signing anything.
Step 3 — Your own system (only if step 2 earns it)
If the trial is useful, we build you a personalized version: a tool tuned to your format, that you and your team can use yourselves to score any address you're evaluating, anytime — without calling us each time.
No long sales process. No buying something sight-unseen. You see it work on a real decision before you decide anything else.
This removes the risk on their side — which is exactly why it sells.
Why not a generic tool
A generic location tool scores "a café." It doesn't know your concept lives or dies on lunch-hour office traffic, that your franchise needs a 300m buffer from your own units, or that your unit economics only work above a certain density.
That's exactly why we don't start with a tool — we start with a conversation, then prove it on one address, before building anything permanent.
What we can configure (examples, not a promise)
| Business type | What changes the logic |
|---|---|
| Coffee shop / chain | Morning office traffic, competitor density in 200m |
| Bar / pub | Evening traffic, noise zones, nightlife clustering |
| Bakery / franchise | Residential walk-by traffic, repeat purchases |
| Casual dining | Evening traffic, parking, neighborhood income |
This is the table we start from on the call — then we adjust it based on what you tell us actually matters.
The full customization menu
The things that actually decide whether a HoReCa unit makes money — and that we can wire into your scoring. You pick from this list on the call, we switch it on.
Scoring logic
Daypart weighting
We score the hours you actually trade — breakfast, lunch, after-work, late night — weighted to match your revenue mix.
Cannibalization buffer
Minimum distance and catchment overlap versus your own units and your franchisees' — you set the radius.
Competitor vs. traffic generator
You define who counts as competition and who feeds you customers — a bakery next to specialty coffee can be a plus, not a minus.
Anchor weighting
Offices, universities, hotels, metro exits, tourist attractions — weighted by what actually builds your average ticket.
Hard format filters
Floor area, ground floor, gastro ventilation, terrace potential, alcohol-license context — as cut-off filters, not score points.
Calibration on your portfolio
We score your current units and match them against their real numbers — the model learns to predict your revenue, not the market average.
Expansion map
Instead of one address — every street in the city ranked by your formula: a target list you can hand to brokers.
Extended data collection
Hour-by-hour busyness curves
How busy the venues around a candidate address are, by hour and day of week.
Competitor menu & price scan
Competitors' dishes and prices within your radius, collected from delivery platforms — the local average ticket and the price gap you could take.
Review velocity tracking
How fast nearby competitors gain new Google reviews — a proxy for real customer flow, not claims.
Street change history
Street View 2019→2025 plus openings and closings: is the street gaining or losing food & beverage tenants.
Rent benchmarks
Median asking rent per street and district, from the listings history we collect daily.
Vacancy watchlist & alerts
We monitor your target streets — when a unit matching your format appears, it lands in your inbox already scored.
Everything on this list runs on data we already collect for Warsaw and Turin — it's a menu to switch on, not a roadmap.
The honest caveat
We're early — Nesso's scoring engine runs on real data today, but the chain-specific product is new. That's exactly why we built it this way: you don't commit to a system until you've watched it score a real address correctly, for your specific format.
Being early with us means more attention on your trial than you'd get from an established vendor running a thousand accounts on autopilot.
FAQ
See it score one of your real addresses before you decide anything.
Tell us what matters. One address to prove it. Then we talk about what's next.