A flat near the office, found before the family lands

The challenge

Every new arrival wants a flat near the office, inside a budget, and they land in two weeks. Tessa spends her evenings refreshing listings, and the good flats are gone by morning. Last month, three families waited in a hotel for a week.

How the flow works

With xMap Flows, Tessa built Nest. Nest is an AI employee: a flow of 6 blocks.

1. Every morning at seven,

   Every morning at 7 (Schedule)

2. Nest draws the area within twenty minutes by bike of each client’s office,

   20 minutes by bike (Travel area)

3. finds the apartments for rent inside it, within budget,

   Apartments for rent (Regional data sources)

4. keeps the ones listed since yesterday,

   Listed since yesterday (Only new)

5. ranks them by price per square metre,

   Best price per metre (Sort and limit)

6. and sends Tessa the best ten before breakfast.

   The best ten, to Tessa (Email)

What it solves

• Evenings on listings: solved by Regional data sources and Sort and limit
• Flats gone by morning: solved by Schedule and Only new
• Families stuck in hotels: solved by Travel area and Email

The result

Today, Nest finds forty-two new flats for her clients. A two-bedroom in Fremont, fifteen minutes from the office by bike, was listed at midnight. Tessa books the viewing at eight, and the family from Bangalore signs on Friday, the day they land.

Tessa used to hunt for flats at night. Now she wakes up to them.

An illustrative scenario: the figures are modelled to show what the flow produces, not a customer's results.

The flow, block by block

1. 1

   Every morning at 7

   Schedule

   Starts the flow on a timetable.

2. 2

   20 minutes by bike

   Travel area

   The area you can reach within a travel time (15 minutes by car) or a distance by road (10 km), on foot, by bike or by car, from each incoming place or from places you pick.

3. 3

   Apartments for rent

   Regional data sources · Regional data

   xMap’s regional datasets: pick a country, then a dataset, such as real estate transactions in Saudi Arabia, property for rent or for sale listed right now in the United States, Japan and the United Arab Emirates, or Road traffic history in the United Arab Emirates (cars counted hour by hour since 2021).

4. 4

   Listed since yesterday

   Only new

   Lets through only the items this flow has not found before, so a daily flow sends only what is new.

5. 5

   Best price per metre

   Sort and limit

   Puts the items in order, and can keep only the first ones: the 10 best rated, the 20 nearest, the highest fit scores.

6. 6

   The best ten, to Tessa

   Email

   Sends one email per run with all the items, or one email per item.

Templates to build it

Ready-made flows with the same blocks. Open one, change the city and the kind of place, and run it.

• Shop space for rent near stations in TokyoNew shop and restaurant space for rent near Tokyo’s stations, every Monday, best value first.
• New homes for sale near the best-rated schoolsNew homes for sale near the best-rated schools in your city, every Monday.
• New homeowners in Miami-Dade every morningHomes with a new owner in Miami-Dade, every weekday morning.
• Rivals within 10 minutes’ drive of each storeThe new rival shops within 10 minutes’ drive of each of your stores.
• Properties that sold this week in Los Angeles, with the priceThe properties that sold this week in Los Angeles, with the price, every Monday.
• Who lives around new placesThe new cafes in your city with the people living around each.

Industries

Learn how it works

• Drive time vs radiusTwo ways to draw the area around a site, and when each is good enough.
• Route planningPutting a day's visits into a good order, for one rep or several.
• Travel area: within N minutes or N km by roadThe area people can really reach from each store or site, by car, on foot or by bike.
• Find property for rent or for sale near your placesShops, restaurants, offices and homes listed now on public property sites in the United States, Japan and the United Arab Emirates, with price, size and price per m2: three datasets in Regional data.
• Regional data sourcesCountry datasets such as property transactions, property listings in the United States, Japan and the United Arab Emirates, and road traffic history in the United Arab Emirates.

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