Retail location and catchment research

A useful retail location lets customers reach it for a particular shopping task and can generate enough additional sales to justify its costs. This overview guide tests that proposition before a site decision: define the trip and working boundary, assess Australian evidence and customer access, compare competing offers, then test the premises. A population count or a busy pavement cannot settle the decision alone.

Define the trip before drawing the catchment

A quick top-up shop, a planned weekly shop and a purchase needing specialist advice place different demands on a location. Write down the intended products, likely visit times and how customers would carry their purchases. Then inspect walking routes, public transport, road access and parking where relevant. A river, difficult crossing or indirect road can matter more than straight-line distance.

Draw an initial working catchment around plausible journeys, with a nearer core and a more uncertain outer area. Its boundary is a research assumption, not a claim that everyone inside will shop there or everyone outside will not. In a regional town, customers may travel farther for a broad range than for a routine item. In an inner-city centre, workers and visitors may matter alongside residents.

Use each source for the question it answers

For a retailer with nearby stores, aggregated customer origins can help refine the working boundary. First check what the origin field represents: a home address, delivery address or loyalty account may point to different places. Sales records show where identifiable buyers came from, not where all potential buyers live. Missing origins, loyalty participation and existing store locations can skew the pattern.

Detailed reconstruction of a catchment from existing customer records is a separate task from this overview. Treat customer-origin records as one possible check on a provisional boundary, not a complete count of potential customers.

For resident context, use ABS Census of Population and Housing products such as Community Profiles and QuickStats. The General community profile describes people, families and dwellings by usual residence, with areas available from national and state levels down to Statistical Area Level 2. It profiles residents, not every customer or passing visitor.

ABS Regional population, 2024–25 financial year reports that capital cities grew by 324,700 people (1.8%) and regional Australia by 94,700 (1.1%). These figures are based on Estimated Resident Population; the release defines capital cities as Greater Capital City Statistical Areas and areas as Statistical Area Level 2, so they do not identify demand at a specific site.

Recent Population Growth in Australia (2024–25 Financial Year)

Examine alternatives customers can actually use

Map stores that serve the same shopping task, including the retailer's own branches. Compare their range, hours, access and likely journey rather than counting every nearby shop as an equal competitor. A second store may reach new customers or mainly move purchases from an existing branch.

Inspect the proposed approaches when target customers would shop. Check the entrance, visibility, crossings, loading access and the effort of carrying goods back to transport or a car.

The City of Melbourne’s Pedestrian Counting System – Sensor Locations dataset provides sensor status, location and directional information. Related datasets include Pedestrian Counting System – 2009 to Present (counts per hour) and Pedestrian Counting System – Past Hour (counts per minute). Sensors can be removed or relocated, and an active status ('A') does not guarantee availability; check the notes. Counts record bi-directional movements through footpath zones, not shop entries, so compare like times and account for inactive periods.

Choose geographic units at the right scale

ABS Mesh Blocks are the smallest areas in the Australian Statistical Geography Standard. Most contain 30 to 60 dwellings, and they can be combined to approximate custom areas such as a working catchment. However, data at this level is limited for confidentiality reasons, and the ABS advises against analysing a single Mesh Block alone.

SA1s provide neighbourhood-scale Census geography and have populations between 200 and 800 people, with generally smaller populations in remote and regional areas. SA2s generally have populations between 3,000 and 25,000 and are designed to represent communities that interact socially and economically. These units offer different levels of detail, so choose one that suits the question and the available data.

The ABS says Mesh Block counts are available in TableBuilder, while Community Profiles and QuickStats can be found through its Search Census data tool. Match the product and geographic scale to the question, keeping in mind the confidentiality limits on small-area data.

Interpret area profiles and pedestrian counts

Small random adjustments are made to protect confidentiality, so totals in profile tables may differ slightly from sums of their component values. Treat small discrepancies as a feature of the data rather than as evidence of a change in the catchment.

Test whether the premises fit the offer

Build a site record covering required customer and supplier access, and the range the floorplan can hold. Include stockroom, storage, equipment, power and delivery needs; opening hours; rent, utilities and fit-out assumptions; lease flexibility; zoning and permits; and whether the premises can adapt as the business evolves.

The Australian Government’s business.gov.au advises checking whether an area is zoned for the business and whether the necessary permits can be obtained. It also recommends considering rent, utilities, fit-out costs, facilities and lease flexibility before choosing premises.

Separate essentials from desirable features such as nearby amenities. A promising catchment cannot compensate for premises that cannot support the intended service at a viable cost.

For an example retail needs list, business.gov.au gives a minimum area of 140 m2 and rent up to $3,000 per month, with flexible lease terms. These are example requirements, not market-wide cost benchmarks. Use your own rent, utilities and fit-out assumptions when testing whether plausible sales can carry occupancy costs.

Compare shortlisted sites for the same shopping task and time horizon. Use a range of sales assumptions and show how each depends on customer reach, visit frequency and purchases. Record what would change the decision: poor access, substantial overlap with an existing store, unsuitable space or occupancy costs plausible sales cannot carry. Where evidence is thin, a small trial may answer a specific uncertainty before a long commitment.

A low-commitment format can help test demand before taking on a more expensive space. Examples include renting a market stall for clothing sales, renting a commercial kitchen by the hour for food sales, or using a co-working space for a professional service.

Key Factors to Verify Before Finalising a Retail Site