A site selection checklist built on location data

Before you visit a candidate site, check eight things with data: how far customers can really travel to it, who lives inside that reach, how many competitors already serve them and how good they are, which anchors bring people past, how traffic and transport reach it, whether there is charging and parking, how fast the area is changing, and how it compares with your best existing branches. What data cannot tell you (the rent, the lease, the frontage, the rules) is what the visit is for.

This checklist is for founders opening a second location, franchise developers and expansion managers screening dozens of addresses. Each check says what to measure, how to read it and which block measures it, so the shortlist you take to viewings is already filtered.

1. Define the reach first

Every other check depends on the area you measure. Draw what customers can reach: a 10-minute walk for a cafe on a high street, a 10 or 15-minute drive for a supermarket or a clinic in the suburbs. Use the Travel area block rather than a radius, because rivers, rail lines and motorways bend real catchments. Keep the same reach for every candidate, or the comparison means nothing.

2. Count the people inside it

The Demographics block gives the residents inside an area, men and women, and nine age groups, so a nursery can look at young children and a gym at working-age adults. Population figures exist in some countries only, among them France, Canada, India, Thailand, Egypt and Australia, and not yet the United Kingdom or the United States. Where they are missing, use proxies: offices, schools or apartment buildings counted with Nearby places.

3. Count the competition, and judge it

Count places of your kind inside the reach, and split them into chains and independents. Then look at their ratings and how many opened recently. A city-wide figure gives the backdrop. For example, xMap's places database lists 246 gyms within 10 km of the centre of Toronto, 29% of them chains, rated 4.6 out of 5 on average, with 14 opened in the twelve months before November 2026. A new gym there walks into a well-rated field; the question is whether a given neighbourhood has fewer gyms per resident than the city as a whole.

246Gyms listed

72Chains

4.6Average rating

14Opened in the last year

4. Look for anchors

Some neighbours bring your customers past the door: a supermarket for a pharmacy, offices for a lunch spot, schools for a tutoring centre, a station for almost anything. Count the anchors that matter to you within a few hundred metres, with Nearby places set to give each candidate a count.

5. Check how people arrive

• By road: the Traffic Flow block measures the speed and jam factor of the roads beside each candidate when a flow runs. Run it at your busiest hours.
• On foot and by transit: count stations and bus stops nearby.
• Charging and parking: the EV charging block counts public chargers and fast chargers within the distance you choose.

6. See how fast the area changes

Openings in the last year say whether rivals are arriving. A site that looks quiet today may sit in a street where three competitors opened this year. The opening dates in xMap's places database, where a place has one, make this visible; a flow with Only new then tells you about each new arrival after you sign.

7. Compare against your own best branches

The most useful benchmark is not the city average but your own sites that work. Run the same checks on your three strongest and three weakest branches. If your best ones all have more than a certain number of residents per competitor inside a 10-minute walk, a candidate far below that needs a strong reason.

8. Score, then shortlist

Put every check in one row per candidate and let a scoring step weigh them. An xMap LLM block can score each site from 0 to 100 against instructions you write (for example, weight residents per competitor most, penalise jammed roads at 8 am) and give a reason. A score is a sorting aid, not a decision: read the reasons.

What data cannot check

• The rent, service charges and lease terms.
• How visible the frontage is from the pavement, and which side of the road it is on.
• Planning rules, licences and opening hours allowed.
• The condition of the unit, its loading access and its neighbours' upkeep.
• Local knowledge: a market day, a planned road scheme, a street that feels unsafe after dark.

Running the checklist with an AI employee

1. Upload candidate addresses to My data.
2. Travel area: 10 minutes by car (or on foot) of each.
3. Demographics inside each area, where the country is covered.
4. Nearby places counting competitors and anchors around each candidate.
5. Traffic Flow and EV charging around each.
6. xMap LLM to score and explain; Make a report to send a PDF to the committee.

The committee receives one page per run with every candidate scored and explained, and the viewings list shrinks to the sites worth a visit.