Understand an area · Use case

How long will a property take to sell or rent in this area?

Casafari Area Insights shows how long properties stay on the market in an area, by price band. ma_get_time_on_market_distribution returns, for each band, the average days_on_market and months_on_market plus properties_count, for sale or for rent. To check one home, comps_get-comparables from Comparables & Valuation adds average_time_on_the_market for its comparables.

Products: Area Insights, Comparables & Valuation

#Short answer

ma_get_time_on_market_distribution groups properties into price bands. For each band it returns:

• lower_bound and upper_bound (the price limits).
• The average days_on_market and months_on_market.
• properties_count (the number of properties in the band).

The bands with the shortest time on market show where properties move fastest. For a single home, comps_get-comparables returns statistics.average_time_on_the_market for its comparable set.

#Steps

#Resolve the area

1. Call ma_get_location_typeahead with an English place name, for example Porto, and keep the location_id. Call ma_get_current_datetime if you need "the last 12 months" as concrete dates.

#Call ma_get_time_on_market_distribution with type_group, business_type, price_range and date_range (start of the last active period)

2. Call ma_get_time_on_market_distribution with a request_data object.
   • Required: type_group (apartment or house), business_type (sale or rent) and custom_location_boundary (location_ids or a circle).
   • Optional: price_range to set the overall price window, and date_range, which filters properties by the start date of their last active period on the market.
   • Other filters: bedrooms_range, total_area_range, construction_year_range, conditions and exclude_outliers (default true).

#Cross-check one property with comps_get-comparables: statistics.average_time_on_the_market and days_on_market_from/to filters

3. Call comps_get-comparables around the home.
   • Required: comparables_count (1 to 50), location_boundary (a circle with a target_point and distance in km, or a polygon), operation and comparables_types.
   • Read statistics.average_time_on_the_market (average days on market).
   • Use days_on_market_from and days_on_market_to (1 to 10,000) to narrow the set.

#Example: apartments for sale in Porto in the last year

Prompt to the assistant: "At what price do apartments for sale in Porto sell fastest? Use properties whose last active period started in the last 12 months."

The assistant calls ma_get_location_typeahead (Porto), then ma_get_current_datetime, then ma_get_time_on_market_distribution:

{
  "request_data": {
    "type_group": "apartment",
    "business_type": "sale",
    "custom_location_boundary": {"location_ids": [PORTO_LOCATION_ID]},
    "date_range": {"min": "YYYY-MM-DD"},
    "exclude_outliers": true
  }
}

The response has this shape:

{"result": [{"lower_bound": <int>, "upper_bound": <int or null>, "days_on_market": <int>, "months_on_market": <number>, "properties_count": <int>}]}

To check a specific 2-bedroom apartment, the assistant then calls comps_get-comparables:

{
  "comparables_count": 20,
  "location_boundary": {"circle": {"target_point": {"address": "Avenida dos Aliados, Porto"}, "distance": 1}},
  "operation": "sale",
  "comparables_types": ["apartment"],
  "bedrooms": 2
}

It reports which price band has the lowest days_on_market, and where the home's estimated_prices.fair_market_price falls among the bands. The figures come from the live calls; these docs publish none.

#How to read the result

#Bands with low days_on_market and high properties_count are liquid

A band with few days on market and many properties is a liquid segment: buyers are active and there is enough evidence to trust the average. A band with few properties gives a less reliable average. An open upper_bound (null) marks the top band.

#Use the result to set a price that sells within your client's deadline

If the client must sell within a set number of months:

1. Find the bands whose months_on_market fits that deadline.
2. Compare them with the comparables' estimated_prices: fast_sell_price, fair_market_price and out_of_market_price.
3. Pricing near fast_sell_price inside a liquid band supports a quick sale. Pricing near out_of_market_price invites a long wait and later cuts.

#Limits

Availability:

• ma_get_time_on_market_distribution and comps_get-comparables are available to Casafari clients with MCP access, using their Casafari account.
• Self-serve access for new users is coming soon.
• The REST equivalent POST /market-analytics-api/distributions/time-on-market (page) is for Casafari client accounts.

Coverage and data:

• In comps_get-comparables, the cadastral-reference target point is Spain only. Elsewhere, use an address or coordinates.
• The Area Insights tool descriptions name no specific market.
• The docs do not publish the exact formula behind days on market.

Pricing and quotas:

• The sources give no figures for pricing or quotas. Ask Casafari.

#Apartment and house groups only

type_group in the distribution accepts only apartment or house. For other property types, comps_get-comparables accepts a wider list of comparables_types, one type group per request.

#date_range filters by the start of the last active period, not by sale date

date_range selects properties whose last active period on the market started within the range. It does not select by the date a property was sold or rented. So recent periods include properties still on the market.

#Questions

All use cases