Who it's for
- Analysts and strategists sizing a category in a specific city.
- VCs and corp-dev teams building quick competitive maps for a memo.
- Founders validating a market before they commit to entering it.
Map every business in a category and city into a structured dataset.
The problem
Mapping a local market by hand is slow and lossy. You search a category in a city, scroll listings, copy names and numbers into a sheet, chase down websites, and still end up with gaps and inconsistencies. Commissioning a custom data project is overkill for a single industry-and-city slice.
biz collect turns one geographic slice into a structured dataset. A radius search returns every matching business with consistent fields - website, phone, web-enriched contact data, ratings, hours - so you can analyze a market instead of assembling one.
The workflow
Pick the category and geography you want to map - for example, dental clinics in Zurich, or accounting firms across eastern Switzerland - and choose a radius that covers it.
POST to /v1/search with the location, keyword(s), radius, and a language code where relevant. You receive a job_id immediately; larger geographies run as async jobs.
Poll GET /v1/jobs/:id until the job finishes. Polling is free, so even a broad search does not add credit cost while it runs.
Receive a structured list of businesses with website, email, social, outgoing links, ratings, reviews, and hours - rows that are ready to analyze rather than clean.
Pipe the JSON straight into Pandas, load it into BigQuery or Snowflake, or take a CSV export into Excel to count, segment, and visualize the market.
Fields & endpoints
POST /v1/search (radius + language)Location, keywords, radius, and language code define exactly which slice you map.
Async jobsLarger geographic searches run asynchronously so a broad map does not time out.
ratings, reviews, opening hoursSignals you can segment and compare across the market.
website, outgoing linksUseful for understanding a market's online footprint and partnerships.
CSV export / stable JSONPipe into Pandas, BigQuery, or Snowflake without per-export field mapping.
Example
Suppose an analyst wants to understand the dental-clinic market in Zurich before a go-to-market decision. They run one biz collect radius search for dental clinics across the city, poll the job, and receive a structured list of clinics with ratings, hours, websites, and contact data.
Loaded into Pandas, that becomes a quick market map: how many clinics exist, how ratings are distributed, which have a website, where the clusters are. What used to be a multi-day scraping-and-cleaning chore becomes a single query plus analysis. Coverage reflects what is publicly available, so treat the map as a strong sample rather than a census.
Everything you need to ship this workflow:
Local market research
Pick a category and geography, POST a radius search with location, keywords, radius, and a language code, poll the job until it completes, then analyze or export the structured list of businesses it returns.
Yes. Larger searches run as async jobs: you POST once, get a job_id, and poll until results are ready. Polling is free, so a broad map does not multiply credit cost while it runs.
The output is stable JSON (with CSV export on the Business plan), so you can pipe it straight into Pandas, load it into BigQuery or Snowflake, or open it in Excel to count, segment, and visualize the market.
It reflects what is publicly available via Google Places search plus website enrichment, so treat it as a strong, structured sample of the market rather than a guaranteed census of every business.
Yes. Searches spend credits based on result pages times unique keyword queries, and polling is free, so the cost of a market map maps directly to the result pages you pull.
Still have questions? Talk to us.
Related guides to take your business-data workflow further.
Sign up free with 200 signup credits, no credit card. POST a search, poll the job, and wire the structured JSON straight into your stack.