Where to build student housing

What it does

Every month: the universities of your city, how many student residences are within 1 km of each, the 10 with the fewest, a memo on each by an AI agent (who lives around, cafes, shops and stations) and a score; strong sites go for your approval and become HubSpot deals, every site is saved to a sheet.

In one sentence: Monthly on the 1st at 08:00, in Toronto, find universities in the area, count the student dormitories within 1 km of each, sort them by nearby_count and keep the top 10, let the AI agent answer, score and rank them with xMap AI, split them by fit score ≥ 75, wait for approval, then add row in Google Sheets and create deal in HubSpot.

Why it is useful

Student housing pays where demand is high and beds are few. This flow finds those universities, writes an analyst-style memo on each and puts only the strong ones in front of you.

Who it is for

Real estate. Agents, developers and landlords who sell, lease and build, and need to know an area better than anyone. Every use case for real estate

Best use cases

• A student housing developer
• A property investment fund
• A co-living operator

What each run gives you

• A memo and score per university
• An approval request for strong sites
• A deal in HubSpot
• A sheet of every site

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 advanced: 11 blocks and 2 tools.

The flow, block by block

1. On the 1st of every monthTrigger · ScheduleStarts the flow on a timetable.
2. My cityWhere · Area of interestSets where the flow looks: countries, cities or specific places, or areas you draw on a map.
3. 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.
4. Student residences around eachxMap 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.
5. The fewest nearby 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.
6. Write the site memo with the AI agentxMap AI · AI agentAn AI agent: for each incoming message it thinks, uses the blocks you link to its Tools port (data, xMap AI, lookups, your tables, other flows, apps), remembers the conversation and writes an answer in {{reply}}.
7. Who lives around itxMap data · DemographicsA tool the AI agent uses when it needs itWho 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).
8. Cafes, shops and stations around itxMap data · Nearby placesA tool the AI agent uses when it needs itPlaces 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.
9. Score each sitexMap AI · xMap LLMTell the AI what to do in plain words.
10. Strong site?Logic · BranchSplits items in two.
11. Approve the siteLogic · ApprovalStops the run until someone says yes.
12. Create the deal in HubSpotApp · HubSpotPowerful CRM that offers tools for sales, customer service, and marketing automation.
13. Save every site screenedApp · Google SheetsCreate, edit, and collaborate on spreadsheets online

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.