Places and points of interest (Google Places)
In a RepVector build, this dataset counts the establishments and employers that make up a territory's commercial base.
What this dataset is
Named places matching a text search near a location, with address, primary type, rating, rating count, operating status and website. Broad coverage of both consumer and commercial premises. It is published by Google and can be queried at point and place level, refreshed live. Each row is an individual entity — an organisation, site or practitioner — so results can be filtered, routed and turned directly into a call list.
Why it is useful
- Identifies how many organisations of a given type operate in the market before you spend a day driving it.
- Reveals employer concentration, which predicts whether a few accounts control most of the volume.
- Provides an independent cross-check on directory and registry counts.
Questions it helps answer
- How many establishments of this type exist inside the territory?
- Is this market fragmented across many small accounts or dominated by a handful?
- Has the establishment count grown since the last planning cycle?
How different verticals use it
RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.
Counts establishments by type to size a distributor or direct-sales territory.
Locates employer density that drives freight and service volume.
Estimates seat counts by firm size before quoting a territory quota.
Cross-checks provider registry counts against independent establishment data.
How RepVector uses it
- You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at point runs without you knowing any codes.
- The planner selects Places and points of interest (Google Places) only when your question matches what it actually reports. It is never included to pad a result.
- Returned rows are normalised into the shared metric layer, so figures from Google line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If Google suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
- The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.
What it does not tell you
- Counts establishments, not decision makers — names and phone numbers come from registry and directory sources.
How it fits with the rest of the catalog
Establishment counts set the size of the opportunity; provider and facility registries turn that size into named targets. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to Places and points of interest (Google Places):
Other business datasets
Common questions
What does Places and points of interest (Google Places) contain?
Named places matching a text search near a location, with address, primary type, rating, rating count, operating status and website. Broad coverage of both consumer and commercial premises. It is published by Google at point and place grain.
How often is it refreshed?
Google publishes on a live cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.
Do I need an account to use it?
No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.
Build the list for one county and see whether the names are right.
Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.
3 free runs — no card required.