Market research data — collected on demand, not resold
A market research data provider sells you what it already collected. Quantic AI collects what you actually asked: it searches a market across three engines, maps the players' sites and scrapes pricing, catalogs and reviews into one dataset — sized to your question and billed per successful page.
$2 free every month · No card required · Every row carries its source URL
# "meal-kit brands in the UK — plans, weekly price, reviews" search("meal kit delivery uk", 3 engines) → 12 brands after dedupe · $0.0015 map(brand sites) · find /pricing, /menu → 12 sites mapped · $0.006 scrape(pricing pages, extract: plan, price) → 34 rows · source URL + timestamp each
How it works
A market question in, a table out
1 · Frame the market
"Boutique gyms in Milan with membership prices", "meal-kit brands in the UK", "no-code database tools and their entry plans". Quantic AI turns the framing into real queries across Google, Bing and DuckDuckGo via the SERP API.
2 · Identify the players
Organic results from three engines are merged and deduplicated into a defensible competitor set — including News and Maps verticals where the market is local or fast-moving.
3 · Read every player
Each site is mapped — pricing, product and about pages surface in one call — and the relevant pages are scraped with your schema through the scraping API: plans, prices, features, review scores.
4 · Analyze, cite, repeat
The dataset lands as CSV or JSON with source URL and timestamp per row — citable in a deck without a screenshot folder. Rerun monthly and the snapshot becomes a trend line.
Market research data collection, method included
Analysts get asked two questions about any number: where is it from and when. Here both answers ship inside the dataset — every row carries the page it came from and the moment it was read, and page metadata keeps the source's own publish date where it declares one.
That's a collection method you can put in an appendix: queries used, sources found, pages read, fields extracted. No black-box "proprietary panel" — a pipeline someone else can rerun and get the same market.
Web scraping for market research — minus the scraping
Every guide on web scraping for market research ends the same way: pick a framework, maintain selectors, rotate proxies, handle blocks. That's a data-engineering project bolted onto a research question. The AI web scraping service swallows that whole layer — discovery, collection and structure are the product, not your sprint.
If your team does want the controls, the same pipeline is callable as REST APIs and MCP tools — start no-code, drop to code when the study becomes a product.
On-demand collection vs a typical data provider
| Quantic AI dataset | Typical research provider | |
|---|---|---|
| Scope | your market question, exactly | their report catalog |
| Freshness | collected when you ask | collected for the last edition |
| Format | raw rows, CSV/JSON | PDF narrative, charts |
| Provenance | source URL per row | methodology page, aggregated |
| Price | cents per run, pay per success | per-report or annual license |
What does a market scan cost?
With Quantic AI (planned): a 300-row market dataset — brands, plans, prices — is 300 × $0.03 ≈ $9 plus metered pipeline; premium fields bill only when found. On the raw APIs the same scan meters at about $0.10 — if the pipeline is your code.
Building the dataset yourself? Two collectors cover most of the raw material: the Google News API for dated coverage per country, and the Google Maps scraper API for who exists in a market and where. See all 100 collectors →
Sources and standards
What this product implements or is measured against, so you can verify a claim yourself:
What is market research data?
It's the factual layer under market decisions: who the players are, what they sell, at what prices, how customers review them, and how all of that moves over time. It can be bought as pre-packaged reports or collected fresh from the public web — which is what this pipeline does.
What is a market research data provider?
A company that collects, organizes and sells market information — from survey panels to web-collected pricing and catalog data. Traditional providers sell what they already gathered; Quantic AI inverts that and gathers what you ask for, when you ask, from live public pages.
What methods does this replace?
The desk-research part: assembling competitor lists, visiting each site, copying prices, features and reviews into a sheet. Surveys, interviews and panels remain human work — but the observable web layer of a market study becomes a prompt instead of a week.
Is web scraping legal for market research?
Collecting public web data for analysis is generally lawful in most jurisdictions, and aggregated market statistics are a well-established use. Copyright, site terms and privacy law still apply to specific sources and personal data — get advice for your market and use case.
How fresh is the data?
Collected at request time — every row carries its source URL and collection timestamp, and page metadata includes publish dates where sources declare them. Rerun the same prompt next month and you have a time series instead of a snapshot.
What does a market dataset cost?
With Quantic AI, planned pricing: $0.03 per delivered row — a 300-row market dataset lands around $9 plus metered pipeline usage, with premium fields billed only when found. Prefer code? The raw APIs meter the same scan at roughly $0.10 in unit prices.
Size the market before lunch
Start with $2 free every month — or join the Quantic AI waitlist for the full prompt-to-dataset service.
Get my free API keyReady-made collectors for this data
Prefer a semantic endpoint to a scraper you maintain? These run with a query, not a URL list — structured rows out, billed only per delivered result.
Specialist data collectors
Rarer sources, same shape: a semantic query in, structured rows out, billed only per delivered result.
Structured data collectors
Specialist sources as a semantic API — a query in, typed rows out, billed only per delivered result.
More structured sources
Registries, forecasts and public records as semantic APIs — typed rows out, billed only per delivered result.
Reviews and marketplaces, as collectors
What customers wrote and what shelves cost, as semantic endpoints — a domain, an ASIN or a keyword in, typed rows out, billed only per delivered result.
Web intelligence collectors
Three endpoints that read a site instead of a search engine: the documents it publishes, how it presents itself to AI crawlers, and what it is built on. A domain in, typed rows out, billed only per delivered result.
Italian classifieds, as a collector
Subito.it — cars by exact mileage, year and fuel, homes by mq and locali, everything by price, comune and seller. A keyword or a category in, typed rows out, billed only per delivered ad.
Stays, venues and delivery, as collectors
A destination or a city in, typed rows out: Airbnb stays with the price breakdown, Tripadvisor restaurants and hotels with coordinates, DoorDash restaurants with exact review counts. Billed only per delivered row.
Fashion retail, as collectors
Keyword searches on ASOS, Zalando and Nike with the current price, the reference or original price and the discount stated as data — the rows a price monitor needs, without a browser.
Directories of software, businesses and doctors, as collectors
Capterra categories with the vendor behind each product, G2 search results, BBB businesses with phone and address, Healthgrades doctors with NPI — one row per entity, deduplicated on the directory’s own id.
Courses, launches, quotes and startup jobs, as collectors
Coursera and Udemy course search with exact review counts, Product Hunt leaderboards with the live score, MarketWatch quotes at full precision, Wellfound startup jobs with salary as posted, Rotten Tomatoes grids with both scores.