Compare rental supply
Benchmark advertised monthly rents against room counts, living space and location. Separate net rent from additional costs before comparing offers.
All use casesNewhome
SWISS REAL ESTATE / MANAGED DATA
Newhome
property data.
Every offer has context.
Keep it in your dataset.
Turn rental and sale listings into useful Swiss property research. Prices, spaces, locations and source evidence, structured around your market.
A LOCAL MARKET, READY FOR ANALYSIS
From individual offers
to a useful market view.
Define the municipalities, property types and offer segments that matter. Build a consistent dataset for research without losing the detail behind each listing.
Study sale inventory
Explore asking prices alongside property type, living area, plot size and renovation year. Keep price-on-request offers out of numeric averages.
Follow listing changes
Track observed price revisions and availability statements across agreed refreshes. Preserve the evidence and flag changes that need review.
SOURCE FACTS, NOT GUESSED VALUES
The data.
With its meaning intact.
Two public listing references checked on 11 October 2026, plus a proposed monitoring model. These are selected source observations, not a live inventory feed.
The full rental picture.
A public Zurich apartment reference, checked in the browser. The monthly gross rent stays connected to its net rent and additional costs.
- immocode / property_number
- Keep the portal identifier separate from the advertiser's property reference.
- net / additional / gross
- Preserve each advertised rent component, the currency and monthly payment basis.
- rooms / living_area / floor
- Retain decimal rooms, square metres and the source floor label without inferring bedrooms.
- source_values / quality_flags
- Keep conflicting source statements visible instead of choosing an unsupported answer.
Observed public listing / 11 October 2026Source reference
{
"record_type": "rental_reference",
"immocode": "6193804",
"property_number": "9642.02.0001",
"country": "CH",
"location": {
"postal_code": "8048",
"municipality": "Zurich"
},
"property_type": "Apartment",
"rent": {
"net": 2810,
"additional_costs": 190,
"gross": 3000,
"currency": "CHF",
"period": "month"
},
"rooms": 3.5,
"bedrooms": null,
"living_area": {
"value": 75,
"unit": "m2"
},
"floor_label": "Ground floor",
"availability_label": "Now",
"construction_year": {
"details_table": 2020,
"description": 2021,
"resolved": null
},
"quality_flags": [
"construction_year_conflict"
],
"interface_language": "en",
"description_language": "de",
"source_url": "https://www.newhome.ch/en/renting/properties/apartment/apartment/city-zuerich/3.5-room/detail/6193804",
"observed_on": "2026-10-11",
"evidence": "public_browser_observation",
"independently_verified": false
}Dated source observation, not a live feed or independently verified property record.
The details table gives construction year 2020, while the description says newly built in 2021. Both are retained as source claims, not independently verified property facts. No listing photos or contact details are reproduced.
Research scope: Zurich apartment rentals and houses for sale in Zurich canton. These examples do not establish nationwide coverage or a production collection success rate.
QUALITY IS MORE THAN A VALID JSON FILE
Keep the nuance.
Flag the uncertainty.
A listing can disagree with itself. Useful property data preserves those differences, so your analysis does not turn a source ambiguity into a confident answer.
- Conflicts stay visible
- Retain table and description values separately when they differ. Flag the field for review rather than quietly selecting a construction year or move-in date.
- Different measures stay separate
- Rooms are not bedrooms. Living area and plot size use square metres; building volume uses cubic metres. Preserve the original labels and units.
- Language is part of the record
- An English interface can contain a German advert. Keep source text and field provenance available; translation and AI enrichment are separately scoped.
- Search scope defines the comparison
- A municipality, a canton and a radius search cover different markets. Record the filters and separate promoted placements from the requested result set.
A MANAGED WORKFLOW FOR YOUR RESEARCH
Scope it carefully.
Deliver it consistently.
Start with a representative pilot. Confirm the permitted access route, field quality and refresh requirements before expanding the collection.
- 01 / DEFINE
Your market and permissions
Agree rent or buy, locations, property categories and intended use. Review authorized access, licensed data or permitted exports before production work.
- 02 / VALIDATE
Records with useful context
Deduplicate by source identity, enrich only the required fields and check prices, units and conflicting statements. Missing values stay explicit.
- 03 / DELIVER
A format that fits your workflow
Scope JSON, CSV, TSV or an agreed API delivery. Include observation times, quality flags and run status for dependable downstream analysis.
Newhome's terms reserve content rights and address unauthorized republication. Public visibility alone does not grant reuse rights. Production access and permitted use must be reviewed for the project. Read Newhome's terms.
Researching individual pages across many websites?
Our self-service Scraping API is a separate workflow for public pages. Content-only requests do not use AI. It does not include CAPTCHA or login bypass, and does not grant Newhome access or reuse rights.
DETAILS WORTH GETTING RIGHT
Practical questions.
Specific answers.
Is the displayed rent the net or gross monthly amount?
The checked rental detail page separates net rental fee, additional costs and gross rental fee. We preserve all three labels and values where available. A search-card price alone is not enough to invent the missing breakdown. Unspecified charges remain unknown, not zero.
How are conflicting values in the same advert handled?
We retain the conflicting statements and their source locations, add a quality flag and leave the resolved field empty pending review. Our checked examples contain a construction-year conflict and an availability conflict. Structured fields are not automatically treated as more truthful than the description.
Can 3.5 rooms be used as a bedroom count?
No. Rooms and bedrooms are different attributes. Decimal room counts are kept as published; a bedroom field stays unknown unless the source explicitly provides it. Living area, plot area and building volume also remain separate, with square-metre or cubic-metre units.
What is the difference between an Immocode and a property number?
The checked rental advert exposes both: an Immocode identifying the Newhome advert and a separate property number supplied with the offer. We retain both without assuming either proves a unique physical home across platforms. Cross-source matching needs its own rules and review.
How do you handle price on request, language and missing fields?
A price-on-request label is retained with a null amount, never zero. An English interface may contain a German description, as our checked examples do. We preserve source labels and language, normalize agreed fields and distinguish missing values from extraction failures. Translation is optional and stays traceable to the original.
Can a missing listing be marked sold or rented?
Not on that evidence alone. We first check whether the run completed and whether the advert remains inside the same search scope. Listing absence, retrieval failure and a confirmed status are separate states. Observation dates do not establish the original publication date or marketing duration.
Does this include photos, floor plans or private contacts?
Not by default. The examples contain selected listing facts only. Images, floor plans, advert text reuse and any personal data require separate rights and scope review. We do not promise login-only access, unrestricted republication or an official Newhome API partnership.
How do you agree coverage, refreshes and delivery costs?
We review the locations, categories, fields, intended use and permitted access route first. A representative pilot establishes field availability and record quality. Refresh frequency, JSON or tabular delivery and any enrichment are priced against that agreed scope, not an assumed complete Swiss inventory.
MANAGED NEWHOME DATA
Tell us which market
you need to understand.
Share your locations, listing segments and the questions your dataset needs to answer. We will review feasibility and a representative sample before confirming scope.
- Regions, municipalities and property types
- Rental, sale or change-monitoring records
- Required fields, refreshes and delivery format
Projects are accepted individually, subject to feasibility and available capacity. An enquiry does not reserve a solution or confirm delivery. Pricing and terms are agreed directly with our team.
A real person reviews your brief. This form does not start paid collection.
ScrapingBuddy is independent and is not affiliated with newhome.ch AG. The hero is an invented illustrative scene, not a listing photo. Rental and sale examples are dated public-page observations, not independently verified property facts; monitoring is a proposed schema. Coverage and permitted use require project review.