1 · Get the data
Data extraction
Structured data from any public website, as a one-time dataset or a recurring collection.
You get: clean files, ready to use
Explore extractionWebsite scraping for every industry
Name any website and the data you need. We build the scrapers, keep them running when sources change, check every delivery and send clean data in the format you use. You review a free sample first.
| source | product | price | in_stock | quality check |
|---|---|---|---|---|
| Store A | Wireless keyboard (compact) | 45.00 | true | ✓ |
| Store B | Wireless ergonomic mouse | 27.49 | true | ✓ |
| Store C | Over-Ear ANC Headphones | 184.00 | true | ✓ |
Services
1 · Get the data
Structured data from any public website, as a one-time dataset or a recurring collection.
You get: clean files, ready to use
Explore extraction2 · Track the changes
Prices, listings, terms and availability tracked over time, with alerts when something changes.
You get: alerts and a change history
Explore monitoring3 · Plug it in
Fresh data delivered straight into your systems on a fixed schedule, with a stable structure.
You get: an API, database or Sheets feed
Explore data feeds4 · Get the answers
Competitor, market and media data turned into clear summaries your team can act on.
You get: reports and dashboards
Explore intelligenceUse cases
One clean dataset of every product or listing across the sites in your market.
Same products, every competitor store, with the exact time each price changed.
Fresh records land in your sheet, database or app every morning, in the same structure.
Every mention across the outlets you care about, summarized by publication and topic.
If the data is on a public website, we can scope it. Don’t see yours? Tell us the websites
Before & after
Websites are built for people, not spreadsheets. Compare a real-looking product page with the record we deliver: the facts pulled out, standardized and checked before they reach you.
The website shows a promotional product listing with mixed text, symbols and marketing copy. The clean record contains only the facts: record ID, product name, price 45.00, previous price 49.00, currency USD, in stock, observation time, source URL and a passed quality check.
Sample Data
Before any project, download a sample delivery. It shows the file structure, the quality checks and the data dictionary you get with every dataset. Values are synthetic; the format is the real thing.
| source | match_key | price | prev. | change | observed (UTC) | qa_flag |
|---|---|---|---|---|---|---|
| Store A | KB-WL-1042 | 45.00 | 49.00 | −8.16% | Nov 2, 09:00 | |
| Store B | KB-WL-1042 | 47.99 | 47.99 | 0.00% | Nov 2, 09:02 | |
| Store C | KB-WL-1042 | 44.50 | 46.00 | −3.26% | Nov 2, 09:04 | |
| Store A | MS-ER-2201 | 29.99 | 29.99 | 0.00% | Nov 2, 09:00 | |
| Store B | MS-ER-2201 | 27.49 | 31.99 | −14.07% | Nov 2, 09:02 | |
| Store C | MS-ER-2201 | — | 28.50 | — | Nov 2, 09:04 | missing_price_and_stock |
| Store A | HD-NC-3310 | 189.00 | 199.00 | −5.03% | Nov 2, 09:00 | |
| Store B | HD-NC-3310 | 179.99 | 179.99 | 0.00% | Nov 2, 09:02 | |
| Store C | HD-NC-3310 | 184.00 | 189.00 | −2.65% | Nov 2, 09:04 | |
| Store A | MN-27-4K01 | 329.00 | 349.00 | −5.73% | Nov 2, 09:00 | |
| Store B | MN-27-4K01 | 339.99 | 329.99 | +3.03% | Nov 2, 09:02 | price_increase |
| Store C | MN-27-4K01 | 319.00 | 319.00 | 0.00% | Nov 2, 09:04 |
How It Works
Share the sites, fields and refresh schedule. We confirm what can be collected and flag any source concerns up front.
Check real records from your sources against your needs. Ask for changes until the structure is right.
Approve the quote, format and schedule. We run the collection, check each delivery and handle source changes.
Our Standards
Clear rules, written down before collection starts, so you know what you’re getting and how it was gathered.
We collect publicly available information. We don’t bypass logins or paywalls, and we don’t collect personal data unless you have a lawful basis and it’s agreed in writing.
During scoping we review each source’s terms and robots.txt, and collect at a polite rate. If a source raises concerns, you hear about it before any collection begins.
Each value keeps its source URL and collection timestamp, so anyone on your team can verify it.
Missing fields, duplicates and unexpected changes are flagged in every delivery, with the reason.
If a delivery fails the quality checks we agreed on, we fix it and redeliver at no extra charge.
Datasets built for you are delivered only to you and are not resold.
Resources
Plain-language answers to the questions buyers ask first: what it costs, what’s legal and which approach fits. See all 6 guides ↗
Buying guide
The five factors that drive price, and how to get an accurate quote.
Compliance
Public data, terms of service, personal data and key court cases.
Buying guide
Who does what in each approach, and how to choose.
Project planning
A worked example and a copy-ready brief template.
About
Furnish Data is a founder-led web data service. You work directly with the founder, from the first scoping call through every delivery. No account managers, no ticket queues.
We take on a small number of projects at a time. That keeps response times short and means your pipeline gets real attention when a source changes.
Our goal is simple: data your team can use without cleaning it first, and a clear answer whenever something changes.
FAQ
Most public websites, yes, including JavaScript-heavy pages, catalogs, listings and directories. During scoping we check each source’s feasibility and terms, and tell you up front if a source can’t be collected reliably or appropriately.
Collecting publicly available, non-personal data is widely practised, but the rules depend on the source and how the data is used. We review each source’s terms and robots.txt during scoping and raise any concerns before collection. This isn’t legal advice; for sensitive use cases, check with your counsel.
Pricing depends on the number of sources, record volume and refresh frequency. You get a fixed quote after reviewing your free sample, before you pay anything.
A small set of real records from your sources, in your chosen format, with a data dictionary and a quality summary. You can ask for changes before approving it.
CSV, Excel, JSON and Google Sheets are standard. Delivery to email, cloud storage, a database or an API endpoint is agreed during scoping.
Each run is checked. If a source changes and fields go missing, the delivery is flagged, the scraper is updated, and you’re told what happened. How we handle source changes
You’ll hear back within one business day. The sample date is agreed during scoping and depends on how many sources are involved.
Contact
Send the sites you want data from, the fields you need and how often you need them. We’ll reply within one business day with questions or a sample plan. No commitment until you approve the sample.
hello@furnishdata.com