Sample site: a suburban shopping centre (illustrative data)

More children and 35–44s live here, and fewer over-55s

More adults 35–44 (20% more) and children 0–14 (10% more) live here than in the surrounding area, and fewer seniors 65+ (25% fewer) and adults 55–64 (15% fewer).

Residents within 3 km

59,200

Median age

35.3

Against 37.9 in the surrounding area

Residents in your target ages, weighted

23,800

40% of all residents

Figure 1

Share of all residents, by age group

Within 3 kmSurrounding area, 9 km

Each bar is the group’s share of all residents. The tag on the right: how much more or less common the group is here.

Children 0–14

Here: 21.0%

Surrounding area: 19.0%

10% more

Teens and students 15–24

Here: 12.5%

Surrounding area: 12.5%

same

Young adults 25–34

Here: 16.0%

Surrounding area: 14.5%

10% more

Adults 35–44Some pull

Here: 16.0%

Surrounding area: 13.5%

20% more

Adults 45–54Core

Here: 12.5%

Surrounding area: 13.0%

5% fewer

Adults 55–64Core

Here: 10.0%

Surrounding area: 12.0%

15% fewer

Seniors 65+Core

Here: 12.0%

Surrounding area: 15.5%

25% fewer

0%5%10%15%20%25%

Residents in your target ages: each adult age group counted by how strongly your concept pulls it. Core counts in full, Good fit two thirds and Some pull a third. If your concept leans towards women or men, that counts too. Children are left out: their parents are the customers. Who it speaks to: Core regulars: adults 45–54, adults 55–64 and seniors 65+.

Over-55s are less common here than in the surrounding area

Together these groups are 22.0% of residents here, against 27.5% in the surrounding area.

Figure 2

Share of all residents in each group

Within 3 kmSurrounding area, 9 km

The line between the dots is the gap.

Seniors 65+Core 12.0% here15.5% surrounding area 25% fewer

Adults 55–64Core 10.0% here12.0% surrounding area 15% fewer

0%5%10%15%20%

Adult groups here your concept barely targets

• 16.0%Young adults 25–34Share of all residents, against 14.5% in the surrounding area. Your concept barely speaks to them.
• 16.0%Adults 35–44Share of all residents, against 13.5% in the surrounding area. Your concept barely speaks to them.

Somewhat more noodle and soup places per resident than the surrounding area

4 noodle and soup places within 3 km: one for every 14,800 residents, against one for every 19,500 in the surrounding area. Somewhat more for the number of residents, so give people a clear reason to pick you.

With only 4 on the map within 3 km, one opening or closing changes this a lot. The surrounding area's count is the steadier guide: 21 within 9 km.

Figure 4

Noodle and soup places per 10,000 residents

This site 0.68

Surrounding area 0.51

Food and drink places within 3 km

46

One per 1,290 residents, against one per 1,320 in the surrounding area

Noodle and soup places within 3 km

4

One per 14,800 residents

What brings people past, within 1 km

• 1 stationNearest: Sample Station, 600 m north-westCommuters pass at the morning and evening rush. Resident data does not count them.
• 14 officesTheir staff are weekday lunch trade that resident data misses. The map misses many offices, so there are likely more.
• 3 schoolsNearest: Sample Primary School, 500 m south-eastParents at drop-off and pick-up, and students after school.
• 2 supermarkets and mallsNearest: Sample Shopping Centre, 100 m eastEveryday shopping trips bring people past.
• 1 hotel or hostelNearest: Sample Motel, 800 m south-westVisitors are not counted as residents.

Source: OpenStreetMap contributors (ODbL). The map misses some places, so treat these counts as a floor.

Three ways to close the gap

Written for your concept from the findings above. Pick one, test it, and count what changes.

1. 1

   Bring the rent down to about $5,600 a month

   Why: Rent is 11.8% of sales at 70% of your guess, above the usual range. About $5,600 a month keeps it within 11%.

   • Ask the landlord for about $5,600 a month, and show them the rent line in this report.
   • Ask for rent-free months while you fit out the shop.
   • Ask for a stepped rent in year one, starting lower while you build the lunch trade.
   • Show the landlord that $6,000 needs 90 customers a day to keep rent within 11% of sales.
2. 2

   Re-pitch for the 35–44s and families who live here

   Why: Adults 35–44 are 16.0% of residents here, against 13.5% in the surrounding area. Seniors 65+ and adults 55–64 are less common.

   • Add a child-size bowl with a mild broth, priced below your $20 average.
   • Open for early dinner from school pick-up time, for parents from the 3 schools within 1 km.
   • Set two tables near the front for families, with space for a high chair.
   • Show the child-size bowl on your sign and your listing, then count walkers with children in the street test.
3. 3

   Stand out from the 4 noodle and soup places nearby

   Why: There is one for every 14,800 residents here, against one for every 19,500 in the surrounding area. With only 4 on the map, one opening or closing changes this a lot.

   • Visit Sample Noodle Bar (0.4 km) and Sample Soup Kitchen (0.9 km) at weekday lunch, and note what people order.
   • Pick one bowl none of them serves, and make it your signature.
   • Offer a fast lunch bowl for staff from the 14 offices within 1 km.
   • Name your signature bowl in one line on your sign and your listing.

Written by AI from the numbers in this report. AI is never allowed to tell you to open or not.

Break-even is 49 customers a day, and rent is above the usual range

From your own figures. Each number is an estimate to check, not a forecast.

Figure 6

Customers a day: break-even against your own guess

4984120

49 a day to break even84: 70% of your guess120: your own guessYour cushion above break-even

Even at 70% of your own guess (84 a day), you cover break-even.

How 49 a day is worked out, and every number behind this section

1. Fixed costs per month: $20,000
2. Each customer leaves $13.60 after food cost ($20.00 less 32%)
3. $20,000 ÷ $13.60 = 1,471 customers a month
4. ÷ 30.3 open days a month = 49 a day

Fixed costs per month	$20,000
What each customer leaves after food cost	$13.60
Customers a day to break even	49
Sales per month to break even	$29,412
Times each seat fills per day to break even	1.2
Rent as a share of sales at 70% of your guess	11.8%
Rent as a share of sales at your full guess	8.2%

Figure 7

Rent as a share of sales at 70% of your guess

11.8%

0%8%11%20%

US full-service median 5.7% (National Restaurant Association, 2024)A common rule of thumb elsewhere: 7 to 10%

Figure 8

Rent takes the takings of your first 3.6 trading days each month

12345678

Takings that go to rentTakings you keep for food, wages and the rest

Above the usual range. Rent is 11.8% of sales at 70% of your guess, and 8.2% at your full guess. The takings of your first 3.6 trading days each month go to the landlord.

What would bring rent into the usual range

• $5,600Rent a month that stays within 11% of sales at 70% of your guess. Yours is $6,000.
• $4,070Rent a month that stays within 8%.
• 90 a dayOr keep this rent. At 90 customers a day (about $54,600 a month in sales), it is 11% of sales.

Regulars you would need

To break even with regulars who come twice a month, you need about 740 regulars. That is about 1 in 32 of the roughly 23,800 residents in your target ages.

Figure 10

Regulars needed, out of every 100 residents in your target ages

3.1% of residents in your target ages would need to become regulars. A moderate share. Shoppers, workers and visitors can make up part of it.

Real customers could differ a lot from these residents

How far real customers could differ from the residents counted here. Kind of spot: shopping centre or mall.

• Shopping centres pull shoppers and staff from well beyond the residents counted here. Who walks past at lunch may look very different from these resident figures.
• OpenStreetMap shows 1 station within 1 km. It brings in people who do not live here.
• If your food draws a particular community from across the city, your pool is wider than these residents. This data has no ethnicity breakdown, so it cannot see that pull.
• Counts are WorldPop 2020 resident estimates on a 100 m grid. They count where people live, not who eats out.

Check it on the street over 3 days

Three short sessions: lunch, evening and weekend. Then compare who walks past with the residents in this report.

Figure 11

Tally sheet for day 1: weekday lunch, 11:30 to 13:30

Time	Under 25	25–44	45–64	65+	With children	Looks like a worker	Stopped or looked in
11:30
11:45
12:00
12:15
12:30
12:45
13:00
13:15
Total
Residents here	33.5%	32.0%	22.5%	12.0%

The sheet is wider than your screen. Scroll it sideways, or print it.

1. Stand where you can see the door you would use. Count everyone who walks past in each 15-minute slot.
2. Guess age bands by eye. It does not need to be exact; you are looking for the mix.
3. After each session, ask 10 people the questions below. Note their answers word for word.
4. Compare the mix you counted with the residents row at the bottom of each sheet. A big difference is the most important thing this kit can tell you.
5. On day 2, also spend 30 minutes counting at Sample Station at the evening rush. Commuters are the customers the resident data misses.

Tally sheets for days 2 and 3

Figure 12

Tally sheet for day 2: weekday evening, 17:00 to 19:00

Time	Under 25	25–44	45–64	65+	With children	Looks like a worker	Stopped or looked in
17:00
17:15
17:30
17:45
18:00
18:15
18:30
18:45
Total
Residents here	33.5%	32.0%	22.5%	12.0%

The sheet is wider than your screen. Scroll it sideways, or print it.

Figure 13

Tally sheet for day 3: weekend midday, 11:00 to 14:00

Time	Under 25	25–44	45–64	65+	With children	Looks like a worker	Stopped or looked in
11:00
11:15
11:30
11:45
12:00
12:15
12:30
12:45
13:00
13:15
13:30
13:45
Total
Residents here	33.5%	32.0%	22.5%	12.0%

The sheet is wider than your screen. Scroll it sideways, or print it.

What to have settled before you sign a lease

• RentRent takes the takings of your first 3.6 trading days each month. Bring the rent down to about $5,600 a month. Yours is $6,000.
• Street countRun the 3-day count. Compare who walks past with the residents row on each tally sheet.
• CashPlan for about $72,000 to get through 6 slow months. What you have set aside covers about 2.5 months.
• Fix to testRe-pitch for the 35–44s and families who live here. Test it for a month and count what changes.
• Places like yoursVisit Sample Noodle Bar and Sample Soup Kitchen at their busiest time.

Where every number comes from

Residents

WorldPop 2020 modelled estimates of who lives on a 100 m grid, by age and sex (CC BY 4.0). They count where people live, not who eats out. The model misses housing built since and is least reliable for small circles.

Surrounding area

Everyone within 9 km, including this site's 3 km. The resident and place comparisons use it.

Residents in your target ages

Each adult age group counted by how strongly your concept pulls it: Core in full, Good fit two thirds, Some pull a third. The fit compares their share of residents here with the surrounding area.

Places nearby

OpenStreetMap contributors (ODbL). The map misses some places. The site map is drawn from each place's distance and direction.

Money checks

Your own figures. Rent is judged against 70% of your own sales guess. Rent lines: Up to 8% is within the usual range. 8% to 11% is at the top of it. Over 11% is above it. For comparison, the US full-service median is 5.7% (National Restaurant Association, 2024). A common rule of thumb elsewhere is 7 to 10%.

Words

AI wrote the summary, the fixes and the street questions from these numbers. It never sets the numbers, and it is never allowed to tell you to open or not.