# Maps Local Business: Two-Snapshot Category Changes

**Use case:** 

Compare synthetic dated place datasets to see shifts in business types by region, with sample-size caveats. No Maps scraping or assumed real market demand.

## Input

```json
{
  "snapshots": [
    {
      "date": "2026-01-01",
      "label": "January export",
      "items": [
        {
          "placeId": "a1",
          "categoryName": "Coffee shop",
          "city": "Springfield"
        },
        {
          "placeId": "a2",
          "categoryName": "Coffee shop",
          "city": "Springfield"
        },
        {
          "placeId": "a3",
          "categoryName": "Bakery",
          "city": "Springfield"
        },
        {
          "placeId": "a4",
          "categoryName": "Gym",
          "city": "Rivertown"
        },
        {
          "placeId": "a5",
          "categoryName": "Coffee shop",
          "city": "Rivertown"
        }
      ]
    },
    {
      "date": "2026-04-01",
      "label": "April export",
      "items": [
        {
          "placeId": "a1",
          "categoryName": "Coffee shop",
          "city": "Springfield"
        },
        {
          "placeId": "a3",
          "categoryName": "Bakery",
          "city": "Springfield"
        },
        {
          "placeId": "b1",
          "categoryName": "Bakery",
          "city": "Springfield"
        },
        {
          "placeId": "a4",
          "categoryName": "Gym",
          "city": "Rivertown"
        },
        {
          "placeId": "b2",
          "categoryName": "Gym",
          "city": "Rivertown"
        },
        {
          "placeId": "b3",
          "categoryName": "Yoga studio",
          "city": "Rivertown"
        }
      ]
    }
  ],
  "geoLevel": "city",
  "comparisonMode": "consecutive",
  "minGeoSample": 30,
  "minCellCount": 5,
  "minShareChangePct": 2,
  "maxRowsPerComparison": 500,
  "maxItemsPerSnapshot": 50000
}
```

## Output

```json
{
  "recordType": {
    "label": "Record type",
    "format": "string"
  },
  "periodFrom": {
    "label": "From",
    "format": "string"
  },
  "periodTo": {
    "label": "To",
    "format": "string"
  },
  "location": {
    "label": "Location",
    "format": "string"
  },
  "category": {
    "label": "Category",
    "format": "string"
  },
  "countFrom": {
    "label": "Count from",
    "format": "integer"
  },
  "countTo": {
    "label": "Count to",
    "format": "integer"
  },
  "shareFromPct": {
    "label": "Share from %",
    "format": "number"
  },
  "shareToPct": {
    "label": "Share to %",
    "format": "number"
  },
  "shareChangePoints": {
    "label": "Change (pts)",
    "format": "number"
  },
  "direction": {
    "label": "Direction",
    "format": "string"
  },
  "signal": {
    "label": "Signal",
    "format": "string"
  },
  "warnings": {
    "label": "Warnings",
    "format": "array"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Local Category & Location Trends from Place Data Actor is ready to run with the inputs already set for "Maps Local Business: Two-Snapshot Category Changes". [Sign up or log in](https://console.apify.com/create-task-from-example/4S3q6x80HeqmhUzNQ) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Maps Local Business: Two-Snapshot Category Changes" task

The Local Category & Location Trends from Place Data Actor will start running based on the input automatically. You can also change all the input fields, like dated place snapshots, location level, and more, to match your specific use case.

### 3. Receive the "Maps Local Business: Two-Snapshot Category Changes" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as record type, from, to, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Maps Local Business: Two-Snapshot Category Changes" task via API](https://apify.com/practical_ai_lab_jp/pal-maps-local-category-trends.md).

## About this Actor

This example demonstrates how to use [Local Category & Location Trends from Place Data](https://apify.com/practical_ai_lab_jp/pal-maps-local-category-trends.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/practical_ai_lab_jp/pal-maps-local-category-trends.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/practical_ai_lab_jp/pal-maps-local-category-trends.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).