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Location intelligence and site analysis

Location Intelligence Services

Location-based market and competitor analysis that turns coordinates into a ranked, defensible recommendation.

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Candidate sites against competitor distribution and catchment boundaries
  • Restaurants · 34
  • Cafés · 22
  • Retail · 26

Overview

From “where are things” to “where should we be”

Location intelligence is the step after mapping. A map tells you where competitors are; location intelligence tells you which of your candidate sites has the best combination of reachable demand, competitive pressure and accessibility, and by how much.

The method is deliberately transparent. Every candidate location gets a score built from named, weighted components, and you can see how each component contributed. If you disagree with a weighting, we change it and re-run, and you watch the ranking respond.

That matters because the output is usually used to justify a lease, a closure or an expansion budget. A black-box score does not survive that conversation. A documented one does.

Sample output

The same data, mapped

A static preview rather than an embedded map SDK, so the page stays fast. Interactive maps are built on request as part of a visualization project.

Candidate sites against competitor distribution and catchment boundaries
  • Restaurants · 34
  • Cafés · 22
  • Retail · 26

Scope

What the analysis covers

Components are selected for your category. Not every business is driven by the same factors.

  • Catchment definition

    Drive-time, transit-time and walking isochrones computed on the real road network.

  • Reachable population

    Residents, workers and households inside each catchment, apportioned properly rather than by centroid.

  • Demographic profile

    Age, income, household composition and other census attributes for each catchment.

  • Competitor mapping

    Every competing venue located, categorised and weighted by size or popularity.

  • Saturation index

    Competitive supply per unit of reachable demand, comparable across candidate sites.

  • Demand generators

    Offices, transit hubs, schools, hotels and anchors that drive footfall to a location.

  • Accessibility scoring

    Road access, transit proximity, walkability and parking availability.

  • Cannibalisation estimate

    For existing networks, how much a new site would draw from your own locations.

  • Gap analysis

    Areas with demand but thin supply, ranked by opportunity size.

  • Weighted site score

    A transparent composite score with the contribution of each component shown.

Output formats

Delivered the way your stack expects

Scored shortlist
A ranked table of candidate sites with component scores and total.
Site profiles
One page per candidate: catchment map, demographics, competitors and verdict.
Interactive map
All layers in a browser map so stakeholders can explore the reasoning.
Spatial layers
Catchments, competitor points and scored zones as GeoJSON or Shapefile.
Decision report
Method, weights, findings, recommendation and the risks in the recommendation.

Use cases

What clients use it for

Sample dataset

What you actually receive

Sample project data. Site D has the second-largest catchment but the weakest position once competitive saturation is taken into account.

Sample project · Candidate site scoring · weighted composite
SitePop. 10 minCompetitorsSaturationAccessibilityScore
Site A · Midtown96,400140.428.682.4
Site B · Riverside71,80060.217.479.1
Site C · Airport Rd48,20030.166.164.7
Site D · Old Town88,100220.718.961.2
Site E · Northgate39,60050.345.248.9

Delivered work

This service on a real project

Sample projects built on this service, with the numbers they produced and what each one settled.

POI DataLocation IntelligenceHeatmap Analysis

Restaurant Location Intelligence

Mapping a city's food and drink offer, measuring competitive density, and producing a ranked shortlist of neighbourhoods for a new venue.

Venues collected
3,180
Coverage recovered
+6%
Areas shortlisted
42 → 6

What it showed

  • Market Square, the area the operator had assumed was strongest because it felt busy, had the highest competitive density in the city and the highest incumbent ratings. Entering there would have meant competing with well-established venues for demand that was already fully served.
  • Riverside North had a third of the competitive density with over half the reachable demand of Market Square. It scored highest overall despite feeling quieter on a weekend visit, because much of its demand is workplace-based and shows up on weekdays.
Read the full case study
POI DataData CollectionMarket Research

POI Data Analysis

Building a comparable category census across five metro areas, and the standardisation work that made the comparison valid.

Raw records
94,200
Unique POIs
71,480
Category labels
14 → 1

What it showed

  • Ranked by absolute count, Metro A led by a wide margin. Ranked per capita, it placed third, and the two markets the team had considered marginal turned out to be the most densely served.
  • Chain share varied from 17.9% to 51.4% across markets that industry commentary had treated as broadly similar. That spread became the central finding of the research rather than a footnote.
Read the full case study

How it works

Five steps, every project

  1. Step 01

    Tell us what data you need

    Share your candidate locations, your category and what a good site looks like to you.

  2. Step 02

    We define the data scope

    We agree catchment definitions, scoring components and their weights before any analysis.

  3. Step 03

    We collect and process the data

    Competitors, demographics, networks and demand generators are assembled for each catchment.

  4. Step 04

    We validate the dataset

    Scores are tested against your existing locations, where you have them, as a sanity check.

  5. Step 05

    We deliver the final result

    A ranked shortlist, site profiles, map layers and a written recommendation.

Quoted on the number of candidate sites, catchment complexity and data availability in the market. Tell us how many locations you are weighing up and you get a fixed price against a written scope.

FAQ

Questions we get asked

What is location intelligence?

The practice of using location data to answer business questions: who can reach a site, who competes for them, and which option is strongest. It differs from mapping in that the output is a ranked, quantified recommendation rather than a picture.

Do I need to supply candidate locations?

No. If you have a shortlist we score it. If you do not, we run a screening pass across a whole city and return the strongest areas first, then score specific addresses within them.

How do you define a catchment?

By travel time on the real network: drive time, transit time or walking time, depending on how customers actually reach your category. Straight-line radii are only used when a network is unavailable, and we flag it when that happens.

Can you use our own sales data?

Yes, and it makes the model considerably stronger. Existing location performance lets us calibrate weights against observed outcomes instead of assumptions. Your data stays yours and is not reused on other projects.

How long does a study take?

A single-city shortlist of up to ten sites is typically two to three weeks. Multi-city or multi-format studies take longer, mostly because agreeing the scoring model deserves proper attention.

What if the data disagrees with our instinct?

We show you why, in components. Often instinct is picking up something real that the model does not include, in which case we add it. Sometimes it is picking up visibility rather than demand. Either way the disagreement is where the value is.

More services

Often combined with

Street View Data

Street-level imagery turned into measurable indicators for every segment of a network.

Learn More

Semantic Segmentation

Pixel-level image analysis that turns imagery into counted, measured classes.

Learn More

POI Data

Business and point-of-interest records with categories, coordinates and attributes.

Learn More

Keep exploring

Where to go next

Related services

Related case studies

Related reading

Next step

Have a specific data requirement?

Tell us the geography, the fields and the cadence you need for location intelligence. You get a scoped plan, a sample and a fixed price before any work starts.

Request a QuoteView Case Studies