Score every candidate against your network strategy.
For retail chains, quick-service restaurants, and expansion teams sizing markets and selecting new sites at scale.
QSR candidate · Rotterdam-Zuid
Scoring criteria
The problem
Retail expansion is a layered decision. Manual scouting can't keep up with any of the layers.
Network expansion is a layered decision: which markets, which submarkets, which specific sites. Manual scouting site-by-site is slow and inconsistent. Off-the-shelf foot-traffic tools are expensive and US-centric. Internal GIS teams build one-off scripts that don't scale to a real expansion program.
Locata gives retail and restaurant operators a screening layer that scores every candidate consistently, surfaces tradeoffs between candidates, and integrates with the demographic and competitive intelligence you already have.
Qué hace Locata
Cuatro casos de uso, una plataforma.
El mismo backbone de puntuación aplicado a las decisiones que los equipos de retail toman cada trimestre.
Market entry scouting
For a new region: which sites cluster best on demographics, traffic, competition density, and brand fit? Score every candidate against a single, defensible set of criteria — not a different mental model per scout.
Network optimisation
Score existing and candidate locations together. Where does your network have gaps? Where is cannibalisation risk eroding new-store payback? Same scoring backbone, different question.
Real-estate pipeline triage
Score broker-submitted candidates against your network strategy in hours instead of weeks. Your real-estate committee meets fewer times because the candidates that reach it are pre-qualified.
Custom criteria per format
Drive-through QSR has different needs than urban grab-and-go. Same platform, different scoring prompt — and the same defensible reasoning per location across formats.
Datos que conectamos
Las fuentes detrás de cada puntuación.
Retail scoring leans heavily on demographic and competitive intelligence layers, complemented by parcel-level imagery and visual evidence for the candidates that surface to the top.
Consulta la lista completa de enriquecimiento para cadencia y cobertura.
Kadaster
Parcel ownership, lease length signals, transaction history.
BAG
Buildings, addresses, frontage, surrounding land use.
CBS demographics
Population density, age, income bands, household composition.
NDW traffic intensity
Roadside visibility and footfall proxy from traffic flow.
Competitor location data
Public chain footprints, density, recent expansions.
Street View
Frontage quality, signage feasibility, parking visibility.
Aerial / parcel imagery
Roof surface, parking layout, parcel envelope.
What a report looks like
Per-candidate scoring with the network logic intact.
Every candidate ships with its reasoning relative to the network strategy you're scoring against — not just an absolute score, but a contextual one. Pipeline-ready, real-estate-committee-defensible.
[ vista previa esquemática — capturas reales por cliente reservadas ]
Precios
Enterprise engagements.
Network-scale work is scoped per chain and per expansion program. Talk to us about scope, integration, and refresh cadence.
Cómo empezamos
How we start.
Most retail engagements open with one of two pilots: a market-entry scouting run on a defined region, or a network-optimization run across your existing footprint. Either is two to three weeks, fixed scope, fixed price.
- 01Week 1: network strategy + scoring prompt definition
- 02Week 2: scoring run across the candidate set
- 03Week 3: pipeline-ready dossier + integration handoff
FAQ
Retail & restaurants: preguntas frecuentes.
What is Locata for retail and restaurants?
Locata is an AI site selection platform for retail chains and quick-service restaurants. It scores every candidate against your network strategy — market entry, network optimization, real-estate pipeline triage, custom criteria per format — and integrates with the demographic and competitive intelligence you already have.Why pick Locata over Placer.ai or in-house GIS scripts?
Off-the-shelf foot-traffic tools like Placer.ai are excellent for US retail but optimised for US data. Internal GIS scripts don't scale to real expansion programs. Locata is European-data-native (CBS, Kadaster, BAG, competitor footprints), runs multi-model AI scoring instead of a single confidence number, and delivers per-candidate reasoning the real-estate committee can defend.Can Locata handle drive-through QSR versus urban formats?
Yes — same platform, different scoring prompts. Drive-through QSR weights traffic flow, manoeuvring space, and signage visibility; urban grab-and-go weights walking traffic, frontage quality, and dwell-time demographics. The scoring backbone is identical; the prompt and constraint set differ per format.What data does Locata use for retail site selection?
Kadaster (parcel ownership and transaction history), BAG (buildings, frontage, surrounding land use), CBS demographics (density, age, income bands, household composition), NDW traffic intensity, public competitor footprints, Google Street View, and PDOK aerial imagery for roof and parking layout.What does a Locata retail engagement cost?
Network-scale retail work is scoped per chain and per expansion program — typically enterprise engagements rather than a fixed rate card. Talk to us about scope, integration with your real-estate pipeline, and refresh cadence.How long until we get a pipeline-ready output?
Two to three weeks fixed-scope from kickoff. Week one is network strategy plus scoring prompt definition with your team, week two is the scoring run across the candidate set, week three is the pipeline-ready dossier plus integration handoff into your real-estate workflow.
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Ver Locata en candidatos de retail.
30 minutos, en línea. Trae un conjunto de candidatos de muestra — ejecutamos una puntuación en vivo con justificación completa por ubicación.