COMPANYDEVELOPER TOOLS API MCP READY

Google Maps Reviewer Geo Profile API

Infer a Google Maps reviewer's home region from their review history. Clusters review coordinates into a standardized home-region guess (city/state/country + ISO codes), a confidence score, and a local-vs-travel footprint. One row per reviewer, for reviewer vetting and fraud research. MCP-ready.

MEDIAN LAGon demand
PARAMETERS6
TOTAL USERS4
MONTHLY ACTIVE1
TOTAL RUNS36
RUNS SUCCEEDED100.0%
RATING5.0 (1)

Input parameters

PARAMETERTYPEREQDEFAULTDESCRIPTION
contributorId string no — Enter a single Google Maps contributor ID (the long numeric ID from a reviewer's profile, e.g. '107022004965696773221').
contributorIds string[] no — Provide a list of Google Maps contributor IDs to profile in one run.
regionGranularity enum no city Level the home-region guess and confidence are computed at: 'city' (e.g.
minCityPopulation integer no 100000 Snap each review to the nearest city with at least this population, so big-metro neighborhoods (e.g. 'Chicago Loop') group under the principal city ('Chicago').
hl string no en Set the two-letter interface language code (e.g. 'en', 'es', 'de').
maxResultsPerContributor integer no 100 How many reviews to analyze per contributor, most recent first. — drives your bill

Worked examples

Basic — the required input, with the schema's own example values
{
  "contributorId": "107022004965696773221",
  "contributorIds": [
    "example"
  ]
}

Tasks

Saved runs with the inputs already filled in — each one a standalone page and a working configuration example.

Request a task →

Code

curl

curl -X POST "https://api.apify.com/v2/acts/johnvc~google-maps-reviewer-geo-profile-api/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"contributorId": "107022004965696773221", "contributorIds": ["example"]}'

Python

from apify_client import ApifyClient

client = ApifyClient("APIFY_TOKEN")
run = client.actor("johnvc/google-maps-reviewer-geo-profile-api").call(
    run_input={'contributorId': '107022004965696773221', 'contributorIds': ['example']}
)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)