Query POI changes between months (PLACES_COUNT_CHANGE)

The PLACES_COUNT_CHANGE function calculates changes in Places of Interest counts and retrieves sample added and removed Place IDs between two specific months across multiple input geographies.

Like PLACES_COUNT_V2, this function is designed for efficient batch processing by accepting an input table parameter of geographies, allowing you to evaluate growth trends and commercial shifts across many locations simultaneously.

Syntax

SELECT *
FROM
  `PROJECT_NAME.LINKED_DATASET_NAME.PLACES_COUNT_CHANGE`(
    TABLE input_geographies,
    filters
  );

Parameters

• PROJECT_NAME: The name of your Google Cloud project.
• LINKED_DATASET_NAME: The name of the BigQuery dataset containing the Places Insights functions (e.g., places_insights___us).
• input_geographies: A BigQuery table containing the geographies to analyze. This table must include the following columns:
  • geo_id (STRING): A unique identifier for each geography.
  • geo (GEOGRAPHY): The BigQuery GEOGRAPHY object representing the area. This can be a point, polygon, or other geography type.
• filters (JSON): A JSON object containing key-value pairs for filtering the places. See Filter Parameters. It must include the following filters:
  • month1 (STRING): The first month to look for places.
  • month2 (STRING): The second month to look for places.

Output table schema

The PLACES_COUNT_CHANGE function returns a table with columns:

The results are sorted by percentage_change and start_count descending.

How it works

The function processes each row in the input_geographies table. For each geo object, it counts the number of places that fall within the geography (or within the geography_radius if the geo is a point and the radius is specified in the filters) in the two months specified in month1 and month2 in the filters. Using those places, it calculates other useful statistics such as percentage change and compound monthly growth rate from the first to second month.

The count includes only those places that match all the conditions defined in the filters JSON object.

Example: Calculate changes in POI counts between two months

This example demonstrates how to query the changes in POI counts between two specific months using the month1 and month2 parameters, with a radius of 5000 from a given geolocation point.

WITH my_locations AS (
  SELECT
    'loc_1' AS geo_id,
    ST_GEOGFROMTEXT('POINT(-122.4194 37.7749)') AS geo
  -- Add more target locations as needed...
)

SELECT *
FROM `PROJECT_NAME.places_insights___us.PLACES_COUNT_CHANGE`(
  TABLE my_locations,
  JSON_OBJECT(
    'geography_radius', 5000,
    'month1', '2026-01', -- Baseline snapshot month (YYYY-MM)
    'month2', '2026-02'  -- Comparison snapshot month (YYYY-MM)
  )
);

Analyzing the output

The query returns a table with a row for each input geography.

• Growth metrics: The output displays the baseline count (start_count: 89,560) and comparison count (end_count: 90,923), yielding a net_change of +1,363 places (+1.52% percentage_change).
• Ground-truth inspection: The sample_added_place_ids array lists specific Place IDs that became active in month2 (February 2026), while sample_removed_place_ids lists Place IDs no longer present.
• Bridge to Places API: You can pass these sample Place IDs directly to the Place Details API (New) to look up store names, addresses, and attributes for newly opened or closed businesses.