Apify Zillow Price Cuts

Homes With a Recent Price Cut, as Rows You Can Query

A city or ZIP in, price-reduced homes out as structured rows, each carrying how much the price dropped, when it dropped, and how long the home has been listed.

When to use this skill

• You want price-reduced homes, the classic signal of a motivated seller or stale inventory.
• You are building a lead feed for agents or investors and want the price cut as numbers, not a badge to read off a page.
• You want a week-over-week feed of new price drops in a market, not a one-time snapshot to eyeball.
• You track a metro to spot where a buyer can negotiate, and need the change amount and days on market on every row.

Not for: a general search of everything for sale, rent, or sold. Use the companion apify-zillow-api skill, built on the same Actor for broad listing pulls. See references/actor-index.md.

What you get

One dataset row per reduced listing. resultType is forSale; branch on it and on the presence of priceChange.

Core fields:

• zpid, url, title, status
• price, priceValue, priceChange (the drop amount), priceChangeDate (when it dropped)
• daysOnZillow
• beds, baths, squareFeet, homeType
• street, city, state, zipcode, latitude, longitude
• brokerName, zestimate, taxAssessedValue, scrapedAt

Plus the resolution provenance on every row: searchLocation, regionId, regionName, regionType, regionAmbiguous.

The Actor ships a dataset view built for exactly this job: priceCuts, which surfaces the change amount, the change date, and days on market together.

Prerequisites

• Apify account (sign up at https://apify.com?fpr=9n7kx3&fp_sid=skillrepo).
• Authentication via apify login, or an APIFY_TOKEN environment variable (Apify Console, Settings, Integrations).

The Actor

• Store page: https://apify.com/johnvc/zillow-api?fpr=9n7kx3&fp_sid=skillrepo
• Actor ID: johnvc/zillow-api
• Pricing: pay per event, billed per listing returned. See the cost section below and references/gotchas.md for the live-price command.

Run it with the Apify CLI

Price-reduced homes in a metro, capped while you look at the shape:

apify actors call "johnvc/zillow-api" -i '{"locations":["Phoenix, AZ"],"statusType":"sale","priceReduction":true,"maxResults":50}' \
  --json \
  --user-agent apify-awesome-skills/apify-zillow-price-cuts \
  2>/dev/null

Price cuts by ZIP with a price ceiling, the shape for a buyer's lead list:

apify actors call "johnvc/zillow-api" -i '{"locations":["85008"],"statusType":"sale","priceReduction":true,"priceMax":600000,"maxResults":100}' \
  --json \
  --user-agent apify-awesome-skills/apify-zillow-price-cuts \
  2>/dev/null

A wider sweep across a whole metro for a weekly feed:

apify actors call "johnvc/zillow-api" -i '{"locations":["Dallas, TX"],"statusType":"sale","priceReduction":true,"autoShard":true,"maxUpstreamCalls":40,"maxResults":1000}' \
  --json \
  --user-agent apify-awesome-skills/apify-zillow-price-cuts \
  2>/dev/null

Confirm the live schema and prices before a large batch:

apify actors info "johnvc/zillow-api" --json \
  --user-agent apify-awesome-skills/apify-zillow-price-cuts \
  2>/dev/null

Read the rows back from a finished run:

apify datasets get-items <DATASET_ID> --format json \
  --user-agent apify-awesome-skills/apify-zillow-price-cuts \
  2>/dev/null

Every call carries the three flags this repo expects: --json (or --format json), --user-agent apify-awesome-skills/apify-zillow-price-cuts, and 2>/dev/null.

Run it from Claude or another AI agent (MCP)

The Actor is MCP-ready. Add the hosted server URL:

https://mcp.apify.com/?tools=actors,docs,johnvc/zillow-api

Then ask, for example: "Find homes in Phoenix with a recent price cut under 600000, and rank them by the size of the price drop." MCP setup docs: https://docs.apify.com/platform/integrations/mcp

Workflow

1. Set statusType: "sale" and priceReduction: true. That is the whole trick; every returned row is a listing whose price was reduced.
2. Start with one metro and maxResults: 50. Confirm priceChange and priceChangeDate are populated before you widen.
3. Add priceMax, bedsMin, or homeType to shape the lead list, all applied before billing.
4. Sort your results by priceChange for the biggest drops, or by priceChangeDate for the freshest ones.
5. To build a week-over-week feed, save this input as an Apify task and attach a schedule. Each run is the current set of reduced listings; diff runs downstream to see what is newly reduced.
6. Turn on autoShard for a whole-metro pull past 820 results, and cap it with maxUpstreamCalls.
7. Read daysOnZillow with care; it resets on a relist, so a low value can hide a long true time on market.

Inputs

• locations (array): plain city, ZIP, county, neighborhood, or state names, resolved automatically to the correct Zillow region.
• statusType (enum, required): use sale for price cuts.
• priceReduction (boolean): set true to return only reduced listings.
• priceMin, priceMax, bedsMin, bedsMax, bathsMin, sqftMin, homeType (filters, applied before billing).
• timeOnZillow (string): narrow by how long listings have been up.
• maxResults (integer, default 200): the primary spend cap.
• autoShard (boolean, default false), maxUpstreamCalls (integer, default 40): whole-metro sweeping and its ceiling.
• ambiguityPolicy (enum largest, error, all, default largest).

Cost

Billing is pay per event: one listing_returned event per delivered listing row. Confirm live prices with the info command above rather than trusting a number copied here.

A search is billed for at least 10 listings, so a metro with only a handful of reduced homes still bills the 10-listing minimum for the page it fetched. Filtered-out listings that never reach the dataset are not billed. Price cuts are a genuine subset of for-sale inventory, so counts per metro are moderate; keep maxResults sized to the market.

Suggested confirmation thresholds: mention the estimate under about $5, warn the user over about $5, get explicit confirmation over about $20. Present cost as "around $X", never as a guarantee.

Honest limits

• priceChange and priceChangeDate are present because the listing was reduced. They describe the most recent change, not the full price history; the source exposes no per-listing price-history endpoint.
• This is a snapshot per run, not a delta between runs. To see what is newly reduced week over week, schedule the run and diff the outputs yourself. A row does not tell you it is new since your last run.
• daysOnZillow resets when a home is relisted, so it understates true marketing time, and it does that most on the stalest inventory, which is exactly the inventory this skill surfaces. Never present it as listing age.
• zestimate is Zillow's own estimate, not an appraisal. It is context next to the reduced price, not a valuation.
• Public listing data only. No seller contact details; the motivation is inferred from the price cut, not from any private field.

Troubleshooting

• Rows returned but priceChange is null: confirm priceReduction: true is set. Without it the search returns all for-sale listings, most of which were never reduced.
• Zero rows, no error: this market has few reduced listings right now, or your filters removed them. Widen priceMax or the location.
• regionAmbiguous on an error row: the location matched several regions. Set ambiguityPolicy: "all" or qualify the name.
• Errors are in-band dataset rows with resultType: "error"; branch on resultType, not on run status.

See references/gotchas.md for cost guardrails and error recovery, and references/actor-index.md for the Actor routing table.

Related Actors

• Zoopla Property API: https://apify.com/johnvc/zoopla-property-api?fpr=9n7kx3&fp_sid=skillrepo
• Realestate.com.au Property API: https://apify.com/johnvc/realestate-au-property-api?fpr=9n7kx3&fp_sid=skillrepo
• Google Maps Places API: https://apify.com/johnvc/google-maps-places-api?fpr=9n7kx3&fp_sid=skillrepo