Areas with few halal restaurants
Blocks with many people and few halal restaurants.
What it does
When planning a halal restaurant abroad: blocks of the city with many residents and the fewest halal restaurants within 2 km, ranked, with a note by xMap AI.
In one sentence: Monthly on the 1st at 08:00, in Toronto, count who lives around, count the halal restaurants within 2 km of each, work out new fields, sort them by per_place and keep the top 20, write a report with xMap AI, then email the list to you.
Why it is useful
Demand for halal food is often far from supply. The gaps are ranked.
Who it is for
Restaurants & cafes. Owners and operators of restaurants, cafes and food brands watching competitors, reviews and the next branch. Every use case for restaurants & cafes
Best use cases
- A halal restaurant group
- A food franchise
- A halal food brand
What each run gives you
- An email
The time it saves
Monthly on the 1st at 08:00. Doing the same work by hand takes about 180 minutes each time; it runs about 1 time a month, so it saves about 3 hours a month (an estimate). It is medium: 8 blocks.
The flow, block by block
- On the 1st of every monthTrigger · ScheduleStarts the flow on a timetable.
- My cityWhere · Area of interestSets where the flow looks: countries, cities or specific places, or areas you draw on a map.
- People in every block of the cityxMap data · DemographicsWho lives in an area: the number of residents, men and women, and nine age groups, from xMap’s population grid (hexagons of about 0.1 km², about 100 countries).
- Halal restaurants within 2 kmxMap data · Nearby placesPlaces around a point from xMap’s own places database (300M+ places, refreshed every month): pick the types of place (more than 5,000, such as Restaurant, Cafe, Pharmacy, Hospital or Gas station, or a whole group of them) and how far to look.
- People per halal restaurantLogic · Calculated fieldAdds fields worked out from the others: a number, a text or a yes/no.
- Best 20 firstLogic · Sort and limitPuts the items in order, and can keep only the first ones: the 10 best rated, the 20 nearest, the highest fit scores.
- Write the notexMap AI · xMap LLMTell the AI what to do in plain words.
- Email me the listAction · EmailSends one email per run with all the items, or one email per item.
Every block can be changed after you use the template: the city, the type of place, the score, where the results go.
Use it now
Answer a few questions, enter your work email, and it runs in your own account, kept running until you pause it. Use this template.
How to set it up
- Build your first flow in ten minutes: From a blank page to a flow that emails you a ranked list every morning.
- Ask the map a question: How many of a kind of place, how many people for each, and where the gaps are, answered on the spot.
- Count what is around each of your places: Competitors, footfall magnets or services within a distance of each site.
- Compare sites side by side: Two or three spots measured the same way, one column each, the best of every row marked and the best site and why.
- Site selection: Choosing where to open a store, branch, clinic or facility.
- How to score candidate store sites: Compare sites on residents, competitors and neighbours, with an AI score and a reason.
- Competitor mapping: Knowing where competitors are, what opens and how they are rated.
More for Restaurants & cafes
- Where to open my next cafe: Areas with many residents and few cafes, scored for your next cafe.
- Weekly competitive intelligence for my cafes: Weekly competitive intelligence: every rival around your branches profiled, with a strategy note.
- Where to open a delivery kitchen: Where to open a delivery kitchen: people per restaurant in every block of the city.
- Event venues to partner with: Event venues and hotels to partner with, with the manager and a pitch.
- Restaurants for my wine distribution: Restaurants and wine bars with the sommelier, into HubSpot.
- Restaurants hiring chefs: kitchens to equip: Restaurants hiring chefs, read as new kitchens, with the owner.