Hoodly is a market map for picking where to open a cafe or restaurant. It overlays foot traffic, transit, business churn, neighbourhood demographics, development pipeline, and zoning context on an interactive map, city by city.

How does the per-address site report work?

Pick a specific address on the map and pay $15 CAD via Stripe Checkout. Within minutes you receive a PDF report by email containing a 6-axis composite score, the 5 nearest competitor cafes and restaurants with names and ratings, neighbourhood demographic profile, foot-traffic estimate, nearby development applications, business-improvement-area and zoning context, and an analyst-written narrative interpretation.

What data does Hoodly use?

Toronto Open Data (business licences, DineSafe, development applications, pedestrian counts, BIAs, zoning, heritage register), Statistics Canada 2021 Census, TTC and GO Transit GTFS feeds, OpenStreetMap via Overpass, and a curated establishment database deduplicated via PostGIS.

Which cities are supported?

Live and serving paid reports: Toronto, with Montréal and more Canadian metros in active development. Operator data has been captured for 78 North American cities. See the supported cities page for the current list.

How is privacy handled for venue data?

Public-mode venue data is aggregated to spatial cells (1 km, 400 m, 200 m at successive zoom levels) and never below a 3-venue privacy floor within any FSA+LDU postal-code bucket. Individual venue addresses are not exposed in public mode.

Frank Nguyen, a data engineer focused on retail and geospatial analytics. Contact frank@feepfoop.com for custom work, location scoring, foot-traffic studies, or data-engineering contracting.

How do I choose a location for a cafe in Fredericton?

Start with the free Fredericton map: look at where cafes already cluster, where pedestrian volume is genuinely measured rather than assumed, and where recent business churn suggests sites that keep failing. A cluster of healthy peers is usually a better signal than an empty block — an isolated corner is the worst-measured position, not a safe gap. Once you have a shortlist, pull a $5 per-address report on each finalist and compare the composite scores.

What does a Fredericton site report include?

A 5-page PDF for one specific Fredericton address: a 0–100 composite score with a plain verdict, a 6-axis weighted breakdown, the five nearest competing cafes and restaurants with names, ratings and distances, the cuisine mix within 400 m, development applications within 500 m, business churn for the surrounding block, the neighbourhood demographic profile against Fredericton’s 2021 Census baseline, and a written analyst interpretation. It costs $5 CAD and arrives by email in about 60 seconds.

Is Fredericton a saturated market for cafes?

Citywide, Fredericton runs about 798 residents per cafe and 1,383 per independent cafe. City-level saturation is close to meaningless on its own, though — the number that decides your lease is the neighbourhood one, and it varies by an order of magnitude across Fredericton. The map shades every neighbourhood against the citywide baseline so you can see which side of it a specific block sits on.

Where does the Fredericton data come from?

City of Fredericton open data, Statistics Canada 2021 Census, local transit schedule data, OpenStreetMap, and a curated establishment database. Venue data on the public map is aggregated to spatial cells and never shown below a three-venue floor, so no individual business is identifiable from the free map.

Where to Open a Cafe or Restaurant in Fredericton

Peak peds / hour

3,000+ flagship

1,500–2,999 major

800–1,499 strong

400–799 solid

200–399 moderate

80–199 light

61% on-site counts · 37% refreshed from nearby data · 3% old counts (faded dots)

TTC transit

Line 1 · Yonge-University

Line 2 · Bloor-Danforth

Line 4 · Sheppard

Streetcar / LRT

Subway station

GO Transit · GTA-wide

Lakeshore West / East

Kitchener / Milton / Barrie / RH / Stouffville

GO Rail station

Future transit

Under construction

Proposed

Source: OpenStreetMap

Vehicles / hour

quietbusyarterial

Cap at ~5,500 veh/hr (DVP/Gardiner peak)

Bikes / hour

250+ flagship corridor

100–249 major route

50–99 notable

20–49 some

5–19 light

Developments — by type

Rezoning (OZ)

Site plan (SA)

Consent (CD)

Subdivision (SB / PL)

Zoning amendment (ZBA)

Minor variance (MV)

Condominium (CO)

Solid ring = approved · faded = proposed.
Source: City of Toronto Open Data.

Business churn (food/bev)

≤15% · stable

15–22%

22–30%

30–40%

40%+ · graveyard

insufficient data (<10 in cohort)

Per BIA · closure within 24mo of issue, cohort 1–3y ago.

Existing patios (CaféTO)

Curb lane café

Sidewalk café

Private property patio

1,525 active patios · Toronto Open Data.

Heritage register

Listed / designated property

12,327 properties (zoom in to see). Source: Toronto Heritage Register.

Liquor permits (5y)

0 · residential

1–25

25–75

75–200

200–400

400+ · entertainment district

Special-occasion + hours/premise extensions, municipally endorsed by City of Toronto. Toronto Open Data.

DineSafe — % with issue (12mo)

<5% · clean

5–10%

10–18%

18–28%

28%+ · high issue density

insufficient data (<3 establishments)

Conditional Pass or Closure inspection result. Toronto Public Health, daily refresh.

Residents per restaurant

<100 · saturated

100–230

230–500 · median

500–1,000

1,000–2,500

2,500+ · underserved

no restaurants / no data

Population (2021 census) ÷ deduped restaurant count, per 158 neighbourhoods.

Opportunity finder · DEV

80–100 · prime

60–80 · strong

40–60 · workable

20–40 · weak

0–20 · cold

Cell border = position

Isolated · no peers — worst measured, not a safe gap

Emerging · some peers, room to grow

Established · real cluster — best measured

Saturated · category near the city’s top — may be full

Residents per cafe

<300 · saturated

300–700

700–1,400 · median

1,400–3,000

3,000–7,000

7,000+ · underserved

no cafes / no data

Population (2021 census) ÷ deduped cafe count, per 158 neighbourhoods.

Foot traffic — peds / hour

3,000+ flagship

1,500–2,999 major

800–1,499 strong

400–799 solid

200–399 moderate

80–199 light

300m cells, value = nearest intersection

Toronto Open Data · latest count —

Old counts refreshed from nearby recent data where available · faded cells = no refresh possible

OSM walkability proxy

70+ high

40-69 medium

20-39 low

<20 very low

OpenStreetMap-derived score from footways, crossings, POIs, and transit stops. Proxy layer, not measured pedestrian counts. Color = score: green is most walkable, orange is most car-dependent.

Zoom in past street level for individual cell scores.

Venue density

Cafés

Restaurants

Bubble size + label = venue count per cell — resolution sharpens as you zoom in. Click a cell for indie/chain split and top cuisines. Counts only — never venue names or addresses.

Aggregated from OpenStreetMap data · cells under 3 venues are merged or hidden to protect small businesses.

Extra layers