Rightmove BMV Deal Finder — below-market-value property leads

Find below-market-value (BMV) properties on Rightmove in one run. The actor samples an area's live listings, builds a market median for every group of comparable properties (same bedrooms, same property type), and delivers only the listings priced at least N% below their group's median — sorted steepest discount first, each with the market context that justifies it.

This is the answer UK property sourcers pay from £14/month for, delivered as a pay-per-result scan: point it at a town, get back the mispriced listings with the numbers already done.

No personal data, ever. Built on the same privacy-first extractor as the Rightmove Scraper: no agent phone numbers, no contact routes, no coordinates — agencies appear as business names only.

Quick start (30 seconds)

1. Put a place name into location — a town (Manchester), area (Camden, London) or outcode (EN2), just like the Rightmove search box.
2. Click Start. The defaults do the rest: 12 pages sampled, deals at 15% or more below their group median.
3. When the run finishes, open the dataset's Overview tab — asking price, group median and discount side by side — or Export it as CSV/Excel/JSON.

A run at default depth finishes in under a minute. The run's status message tells you what happened at a glance: how many listings were sampled, how many comparison groups formed, how many deals cleared the bar.

Who this is for

• BMV property sourcers. The daily grind — pull an area, compare every listing to its comps, shortlist the underpriced ones — becomes one run per area. The output is the shortlist.
• Buy-to-let investors screening areas. Run several towns and compare where discounts cluster. Run the rent channel to spot below-market rents — the other half of a yield calculation.
• Flippers hunting mispriced listings. Sort is steepest-first; the top of the dataset is where the margin lives. The auction flag tells you which leads need cash.
• Deal packagers. Each row carries the evidence — group, sample size, median, discount — so a lead sheet is an export, not a spreadsheet session.

A real run, for scale: Manchester at defaults with a 20% threshold sampled 149 listings, formed 7 comparison groups, and delivered 18 deals — the steepest 65% below its group's median (an auction lot, which is exactly the kind of thing the flags are for).

What you get

Each deal is one dataset item: the full listing plus four scoring fields.

{
  "propertyId": "169700001",
  "url": "https://www.rightmove.co.uk/properties/169700001",
  "title": "2 bedroom flat for sale",
  "displayAddress": "Chase Side Avenue, Enfield, EN2",
  "priceGbp": 150000,
  "currency": "GBP",
  "priceFrequency": null,
  "priceQualifier": "Offers Over",
  "bedrooms": 2,
  "bathrooms": 1,
  "propertyType": "Flat",
  "channel": "buy",
  "tenureType": "LEASEHOLD",
  "displaySize": "678 sq. ft.",
  "summary": "A well presented two bedroom apartment...",
  "firstVisibleDate": "2026-06-12T10:14:02Z",
  "listingUpdateReason": "price_reduced",
  "listingUpdateDate": "2026-08-10T09:06:33Z",
  "addedOrReduced": "Reduced on 10/08/2026",
  "agencyName": "Ian Gibbs, Enfield",
  "featured": false,
  "auction": false,
  "imageUrls": ["https://media.rightmove.co.uk/property-photo/example.jpeg"],
  "bucket": "2-bed flat",
  "bucketSize": 34,
  "bucketMedianGbp": 200000,
  "discountPct": 25
}

Field notes, so you know exactly what you are buying:

• bucket is the comparison group the deal was scored in — bedrooms plus property type, so a 2-bed flat is only ever compared to other 2-bed flats.
• bucketSize is how many priced listings the median was computed from. Bigger is steadier; groups under 5 listings are skipped entirely rather than scored on noise.
• bucketMedianGbp is the group's median asking price in the sampled area, and discountPct is how far below it this listing sits.
• auction matters here more than anywhere: steep discounts are often auction lots. Check it before you get excited.
• priceQualifier (Guide Price, Offers Over) and addedOrReduced carry the listing's own pricing signals — a fresh reduction landing below median is a stronger lead than a stale one.
• agencyName is a trading name and branch only; displayAddress is the address exactly as the agent published it. No contact data, no coordinates — by design.

How much does it cost to find BMV deals?

$1.99 per 1,000 deals delivered, pay-as-you-go — you pay for deals, not for the market sample behind them. A typical run delivers 10–50 rows, so a full area scan costs roughly $0.02–$0.10. No subscription, no charge for failed runs.

The price is all-inclusive — platform usage is covered, with no separate compute or proxy charges. Datacenter proxies are sufficient, and a default-depth run finishes in under a minute. Compare that to the £14+/month sourcing tools doing the same arithmetic.

Free-plan runs are limited to 25 items — more than a typical scan delivers anyway, so the free plan is a genuine trial here.

Not technical? Let your AI assistant set it up

Copy this into ChatGPT, Claude or any AI assistant, fill in the one line, and follow the conversation:

Help me set up the "Rightmove BMV Deal Finder" actor on Apify
(https://apify.com/lowlanddata/rightmove-bmv-deal-finder). Guide me one step at a time.

What I want to find: [E.G. "houses priced well below market in Sheffield, up to 250k"]

Guide me to:
1. Propose my input values: location (as I'd type it on rightmove.co.uk),
   channel buy or rent, an optional priceMinGbp/priceMaxGbp band,
   bedroomsMin/bedroomsMax, discountThresholdPct (15 is a sensible start),
   and samplePages (12 by default; more = steadier medians).
2. Create a free Apify account (apify.com), open the actor page, paste the
   values into the Input form, and start a run.
3. Read the results with me: what bucket, bucketMedianGbp and discountPct
   mean, and why I should check the auction flag on the steepest discounts.
4. Set up a daily Schedule in the Apify Console with the same input, plus an
   email or Slack integration so new deals reach me automatically.
5. Show me how to export results as CSV/Excel, or read them from the API if I code.
6. If the results are what I wanted, remind me at the end to leave a quick rating
   on the actor page, and to report anything broken or missing on its Issues tab.

Input

Field	Description
location	Place as you would type it on Rightmove. Required. First suggestion wins.
channel	buy (default) or rent.
priceMinGbp	Only properties priced at least this many pounds (per month for rentals).
priceMaxGbp	Only properties priced at most this many pounds (per month for rentals).
bedroomsMin	At least this many bedrooms.
bedroomsMax	At most this many bedrooms.
radiusMiles	Widen the search this many miles around the location.
discountThresholdPct	A listing must be at least this far below its group median to count as a deal. 5–60, default 15.
samplePages	Result pages sampled to establish the market medians. 2–42, default 12. More pages = steadier medians.
maxItems	Upper bound on deals delivered (default 100, free plan 25).
proxyConfiguration	Proxy settings; keep Apify proxy enabled.

One sample serves both sides of the comparison: the same listings that build the medians are the candidates scored against them, so a run never charges you twice for the same area. If the sample is too thin to form even one comparison group, the run fails with a readable message — widen the area or raise samplePages — and costs you nothing.

Use it from your code

Run the actor and get deals straight back with one HTTP call — well within the sync window, since runs finish in under a minute:

curl "https://api.apify.com/v2/acts/lowlanddata~rightmove-bmv-deal-finder/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -X POST -H "Content-Type: application/json" \
  -d '{"location": "Manchester", "discountThresholdPct": 20}'

Node.js:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });
const run = await client.actor('lowlanddata/rightmove-bmv-deal-finder').call({
  location: 'Manchester',
  discountThresholdPct: 20,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("lowlanddata/rightmove-bmv-deal-finder").call(
    run_input={"location": "Manchester", "discountThresholdPct": 20})
items = client.dataset(run["defaultDatasetId"]).list_items().items

Schedules, webhooks and the Make/Zapier/n8n integrations all work out of the box — this is a standard Apify actor.

Use it with AI agents (MCP)

Claude, Cursor and other MCP-capable agents can run this finder as a tool through Apify's hosted MCP server: the agent picks the area, starts the scan and reads the deals — no glue code.

Claude Code:

$claude mcp add apify --transport http "https://mcp.apify.com?actors=lowlanddata/rightmove-bmv-deal-finder"

Cursor or Claude Desktop (add a custom connector / MCP server with this URL):

https://mcp.apify.com?actors=lowlanddata/rightmove-bmv-deal-finder

Sign in with your Apify account when prompted — runs are billed to it. Setup details per client: Apify MCP docs.

Prompts that work once connected:

• "Scan Leeds for properties at least 20% below market and tell me which ones aren't auctions."
• "Compare BMV deal counts in Hull, Bradford and Stoke and tell me where discounts cluster."
• "Find below-market 2-bed flats within 5 miles of Liverpool and summarize the top five."

Is it legal to scrape Rightmove for BMV deals?

The finder works entirely on public listing data — asking prices, bedrooms, property types — which is public commercial information, and it inherits the Rightmove Scraper's structural guarantee: no personal data enters your dataset in the first place. Agent phone numbers, contact routes and exact coordinates are never read into the output; the agency appears as a business name only. UK GDPR sets strict rules on personal data, and the cleanest answer to those rules is a dataset that contains none.

The medians are computed by the actor from that same public sample — no third-party valuation data, nothing beyond what any Rightmove visitor sees. Requests are paced, load on the site is kept negligible, and no anti-bot protection is bypassed.

Is there a Rightmove API for finding underpriced properties?

No — Rightmove publishes no public listings API, and no API anywhere hands you "listings below their local market median". This actor is the practical route: one HTTP call (run-sync-get-dataset-items) returns the deals with the market context attached, on demand, on a schedule, or as an MCP tool for AI agents.

Does Rightmove block scrapers?

Rightmove serves its listings openly to ordinary requests — and this actor stays inside that welcome: paced requests, standard datacenter proxies, load kept negligible. No CAPTCHA fights, no bot-wall cat-and-mouse — which is also why a scan reliably finishes in under a minute and holds up on a daily schedule.

How do I monitor an area for BMV deals?

Set your location and threshold, then add a daily Schedule in the Apify Console with an email or Slack integration on the runs — every morning the mispriced listings land in your inbox, steepest first, with the median maths already done. The run's status message doubles as the digest line: deals found, sample size, group count. New listings priced wrong tend to be corrected or snapped up fast, so a daily cadence is the difference between sourcing and archaeology. The AI-assistant prompt above walks a non-technical user through exactly this setup.

FAQ

How do I find below market value property? Compare each listing's asking price to what comparable properties ask in the same area — same bedrooms, same type — and shortlist the ones sitting well below. That is precisely what one run of this actor does: sample the area, build the medians, deliver the listings 15% (or your threshold) below their group.

What does BMV mean? Below Market Value — a property priced under what comparable properties go for. Sourcers and investors hunt BMV deals for built-in margin: instant equity on purchase, or headroom on a flip.

How does the market median work? The run samples up to samplePages pages of the area's live listings, groups them by bedrooms + property type, and takes the nearest-rank median asking price of each group with at least 5 priced listings. Every deal row carries its group's median and sample size, so you can judge the evidence yourself.

Why do auction properties show up as big discounts? Auction guide prices are set low to attract bidding, so they often sit far below the local median — the steepest discount in a run is frequently an auction lot. Every row carries the auction flag, so filtering them out (or in — some sourcers want exactly those) is one column.

Are the discounts against sold prices or asking prices? Asking prices. The median is built from what sellers in the area are currently asking, not from Land Registry sold data. That makes it a live mispricing signal, not a valuation — a listing 25% below its peers is a lead to investigate, never a verdict.

Is a big discount always a good deal? No. Steep discounts usually have a reason: auction terms, shared ownership (where the price is for a share, not the whole property), cash-only sales, short leases, condition. The auction flag is in every row and the summary text usually says the rest. Treat the dataset as a shortlist for due diligence, not a buy list.

What discount threshold should I use? 15% (the default) is a sensible sourcing bar: enough margin to matter, loose enough to produce leads in most areas. Raise it to 20–25% in cheap, high-volume markets to cut noise; drop it toward 10% in expensive, tight markets where genuine mispricing is rarer and smaller.

How many sample pages do I need? The default 12 balances speed and stability. More pages mean more listings per group and steadier medians — worth it in large cities with many property types. In small towns, more pages may not exist; if a run reports few groups, widen radiusMiles instead.

Why did my run find zero deals? Usually a healthy market plus a strict threshold. Check the run's status message: if the sample and group counts look solid, lower discountThresholdPct; if groups are scarce, widen the area or raise samplePages. A zero-deal run still tells you something — nobody in that area is visibly mispricing.

Can I find below-market rents too? Yes — set channel: "rent" and the same maths runs on monthly rents. Useful from both sides: a below-market rent to negotiate as a tenant, or — for investors — evidence of what comparable properties actually ask, the other half of a yield calculation.

Can I limit deals to my budget? Yes — priceMinGbp/priceMaxGbp and bedroomsMin/bedroomsMax narrow the search before sampling, so both the medians and the deals reflect exactly the slice of the market you can buy in.

What does the bucket field mean? The comparison group the deal was scored in, e.g. 2-bed flat — bedrooms plus property type. Listings missing either value can't be fairly compared and are left out of scoring entirely.

Can I run it on a schedule? Yes — any input works on an Apify Schedule. Daily is the sweet spot for sourcing: mispriced listings get corrected or taken quickly. Pair the schedule with an email or Slack integration and the deals come to you.

Can I export to Excel or CSV? Yes — every dataset exports as CSV, Excel, JSON or XML from the Apify Console or API. The Overview table (price, group, median, discount, link) is built for exactly that export.

How is this different from the Rightmove Scraper? The Rightmove Scraper delivers listings; this actor delivers an answer. It runs the sampling, grouping, median maths and threshold filtering for you and charges only for the deals — the raw-data actor is the right tool when you want every listing.

Does it include agent phone numbers or contact details? No — by design, and it never will. Agencies appear as trading names only, and coordinates are never collected. The dataset is safe to store, share and pipe into a CRM without a privacy review.

Does it work with Make, Zapier or n8n? Yes — it is a standard Apify actor; all platform integrations, webhooks and schedules apply.

Why did my run stop at 25 results? That is the free-plan sample cap — though a typical scan delivers 10–50 deals, so on the free plan you are usually seeing the full result anyway. Any paid Apify plan removes the cap.

Related scrapers

The same privacy-clean Rightmove data, cut different ways:

• Rightmove Scraper — the parent: full listings as structured JSON, every filter, every field.
• Rightmove Price Reductions — sellers already cutting: a reductions-only feed with the old-to-new price move parsed.
• Rightmove New Listings Alert — only what's new since your last run, deduplicated, built for schedules.

Troubleshooting

The actor fails fast with the reason in the run's status message:

• "No (bedrooms, property type) group reached 5 priced listings - the area sample is too thin to define a market price. Widen the area or raise samplePages." — the area sample was too thin to compute any median. Widen the area (radiusMiles), raise samplePages, or loosen the price/bedrooms filters. The run delivered nothing and costs nothing.
• "Rightmove does not know the location ..." — type the place as the Rightmove search box suggests it, e.g. Camden, London instead of an abbreviation.
• "priceMinGbp must not be higher than priceMaxGbp." — swap the two values.
• "Rightmove blocked the run before any results could be fetched. This is usually temporary - retry in a few minutes." — a temporary block on the first request; a retry usually lands on a clean proxy session.
• Zero deals, healthy sample — not an error. Check the status message's group count, then lower discountThresholdPct or accept that the area is priced tight today.

Support

Found an issue or missing a field you need? Open an issue on the actor's Issues tab — reports get fixed, this actor is actively maintained.

Working well for you? A rating on this page takes ten seconds and helps other sourcers find this — it is also the clearest signal of what we should build next.