A villa priced on real sales, the same afternoon

The challenge

When a seller calls, she has a day to name a price. She rings other agents and reads listing prices, which run far above what homes really sell for. Last spring she priced one too high, it sat for four months, and the seller left.

How the flow works

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

1. When she adds a seller to her sheet,

   A new seller in her sheet (Microsoft Excel 365 event)

2. Gauge pulls every villa sale recorded in that district in the last three months,

   Villa sales in that district (Regional data sources)

3. keeps the ones of a similar size,

   A similar size (Filter)

4. works out the middle price per metre,

   Middle price per metre (Custom code)

5. writes a short note on what the villa should fetch,

   A price note (xMap LLM)

6. and sends it to her inbox.

   Into her inbox (Microsoft Outlook)

What it solves

• A day to name a price: solved by Microsoft Excel 365 event and Microsoft Outlook
• Listings, not sales: solved by Regional data sources and Custom code
• Priced high, sat unsold: solved by Filter and xMap LLM

The result

Ten minutes after a seller calls, Layla has the note: eleven villas of that size sold in the district this quarter, at a middle price of about five thousand riyals a metre. She calls back the same afternoon, with real sales to show.

Layla no longer guesses a price. She shows the sales that set it.

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

   A new seller in her sheet

   Microsoft Excel 365 event · Excel event

   Starts the flow when something happens in Microsoft Excel 365: a new record, a message, a change.

2. 2

   Villa sales in that district

   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).

3. 3

   A similar size

   Filter

   Keeps only the items that match a rule.

4. 4

   Middle price per metre

   Custom code

   Your own JavaScript, for what the other blocks cannot do: change, add or drop fields, filter and reshape the items.

5. 5

   A price note

   xMap LLM

   Tell the AI what to do in plain words.

6. 6

   Into her inbox

   Microsoft Outlook · Outlook

   Runs an action in Microsoft Outlook.

Templates to build it

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

• High UV days: advice for my clinics' patientsOn high UV days, a short sun safety tip for each clinic's patients.
• Weather-driven promotions per storeA promotion idea for each store when heat or rain is coming.
• Roadworks and closures near my projectsRoad closures and roadworks near each of your sites, every morning.
• Heavy rain at my properties, with a checklistAn alert to facilities when heavy rain is coming at your properties.
• Heatwave stock alert for my outletsWhen a heatwave is coming, stock advice for your outlets on WhatsApp.
• Rain warning for my delivery hubsWhen rain is coming at a hub, a customer notice is ready for the ops team.

Industries

Learn how it works

• Location intelligenceUsing where things are, and what is around them, to make business decisions.
• Site selectionChoosing where to open a store, branch, clinic or facility.
• Lead scoringRanking prospects by how likely they are to buy.
• Build your first flow in ten minutesFrom a blank page to a flow that emails you a ranked list every morning.
• Enrich a list onceA CSV of addresses or companies back with phone, website, rating and an AI score.
• 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.

More stories from Real estate

• Every building site checked from space before paydayHamad is project director at a large property developer in Doha. He has twelve buildings going up at once, from Lusail to West Bay.
• Every tenant warned before the storm arrivesChloe manages eighty rental homes for owners across Perth, from Fremantle to the northern beaches. She works on her own.
• The tenant outgrowing its floor, seen in its hiringAino leads leasing for a large office landlord in Helsinki. Her buildings sit across Kamppi, Ruoholahti and Pasila.
• No guest drags a suitcase past a closed streetDaniela rents out four furnished flats in El Poblado, in Medellin, to visitors from all over the world. She runs it all from her phone.

All 137 stories →