Universities at semester end, for student moves and storage
Campuses ranked by the students around them, for moving and storage.
What it does
Before each semester ends: universities in your city with the students living around them, ranked by xMap AI for a student moving and storage campaign, emailed with a map.
In one sentence: Monthly on the 1st at 08:00, in Boston, find universities and colleges in the area, count who lives around, work out new fields, score and rank them with xMap AI, sort them by fit score and keep the top 10, then show them on a map and email the list to you.
Why it is useful
Semester end brings thousands of small moves at once. Campaigns near the right campuses catch them.
Who it is for
Home services & trades. Cleaning, plumbing, electrical, pest control, moving and repair businesses filling their vans, winning contracts and planning around the weather. Every use case for home services & trades
Best use cases
- A moving company
- A storage company
- A student services app
What each run gives you
- A map
- An email
The time it saves
Monthly on the 1st at 08:00. Doing the same work by hand takes about 60 minutes each time; it runs about 1 time a month, so it saves about 1 hours a month (an estimate). It is medium: 9 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.
- UniversitiesxMap 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.
- Who lives aroundxMap 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).
- Students nearbyLogic · Calculated fieldAdds fields worked out from the others: a number, a text or a yes/no.
- Score each campus with xMap AIxMap AI · xMap LLMTell the AI what to do in plain words.
- Best 10 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.
- Show them on a mapAction · Show on a mapShows the results as points on a map, with the area of interest.
- 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.
- Location intelligence: Using where things are, and what is around them, to make business decisions.
- 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.
More for Home services & trades
- Office towers for window and facade cleaning: The biggest office buildings scored for window and facade cleaning.
- Where to launch laundry pickup: Young, busy blocks with few laundries, to launch pickup.
- New apartment buildings for cleaning contracts: New apartment buildings with the property manager, for cleaning contracts.
- Busy restaurant kitchens for deep cleaning: The busiest kitchens graded for deep cleaning, to the sales team.
- Franchise territories by households: Your city split into franchise territories with similar populations.
- Hotels and apartment complexes for pool cleaning: Hotels and apartment complexes scored as pool cleaning clients.