# Local Market Opportunity Intelligence (`northpeak_data/local-market-opportunity-intelligence`) Actor

Stop guessing where the next local-market opportunity is. Turn local business data into evidence-backed insights on market saturation, underserved areas, service gaps, competitor strength, and where to investigate next.

- **URL**: https://apify.com/northpeak\_data/local-market-opportunity-intelligence.md
- **Developed by:** [Northpeak Data](https://apify.com/northpeak_data) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.90 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Local Market Opportunity Intelligence

**Stop guessing where the next local-market opportunity is — turn raw business listings into evidence-backed market decisions.**

Local Market Opportunity Intelligence transforms Google Maps and local-business datasets into a decision layer built for market research, expansion planning, competitive intelligence, agencies, lead-generation teams, investors, and multi-location operators.

Instead of returning another list of businesses, it answers the questions behind the data: **Where is the market crowded? Which zones look underserved? Which services are missing? Who are the strongest competitors? Is the opportunity real enough to investigate now?**

### What you get

- **Opportunity score** for fast market prioritization
- **Market saturation** and competitor concentration signals
- **Underserved zones** that may deserve deeper investigation
- **Service gaps** derived from the supplied business records
- **Top competitors** using rating and review strength
- **Evidence quality** so weak datasets are not treated like strong evidence
- **Counter-evidence** that highlights reasons not to overreact
- **Confidence score** for each analysis
- **Recommended action**: collect more evidence, investigate entry, test a niche/zone, or watch

### Built above the scraper layer

This Actor does not try to replace Google Maps scrapers. It turns their output into **commercial intelligence**. Feed records directly or provide an Apify dataset ID from an upstream local-business Actor.

That makes it useful as the decision step in an automated workflow: **collect → analyze → prioritize → act**.

### Typical use cases

Market-entry research, franchise and location expansion, local SEO opportunity research, competitor mapping, agency prospecting, category white-space discovery, service portfolio planning, and recurring market monitoring.

### Input

Use either:

- local-business records directly in the Actor input, or
- an Apify dataset ID containing business records.

For stronger conclusions, supply a representative set of businesses from the market you want to evaluate.

### Output

The Actor returns structured JSON designed for datasets, APIs, automations, agents, spreadsheets, and downstream BI workflows. Key fields include opportunity score, saturation, underserved zones, service gaps, top competitors, evidence quality, counter-evidence, confidence, and recommended action.

### Important interpretation note

The Actor infers opportunities from the records you provide. A high score is a signal to investigate, not a guarantee of commercial success. Evidence quality and counter-evidence are included specifically to make the output more decision-safe.

# Actor input Schema

## `records` (type: `array`):

Paste Google Maps/local-business records. Works with common fields such as title/name, rating, reviews/reviewsCount, category, address/city/neighborhood, priceLevel and services.

## `datasetId` (type: `string`):

Analyze records from an existing Apify dataset instead of pasted records.

## `minimumBusinesses` (type: `integer`):

Minimum number of businesses used as the threshold for stronger market evidence.

## Actor input object example

```json
{
  "records": [
    {
      "name": "Alpha Dental",
      "rating": 4.8,
      "reviewsCount": 820,
      "category": "Dentist",
      "neighborhood": "North",
      "services": [
        "implants",
        "emergency"
      ]
    },
    {
      "name": "Beta Dental",
      "rating": 4.1,
      "reviewsCount": 95,
      "category": "Dentist",
      "neighborhood": "South",
      "services": [
        "cleaning"
      ]
    },
    {
      "name": "Gamma Dental",
      "rating": 3.9,
      "reviewsCount": 55,
      "category": "Dentist",
      "neighborhood": "South",
      "services": [
        "cleaning"
      ]
    },
    {
      "name": "Delta Dental",
      "rating": 4.7,
      "reviewsCount": 600,
      "category": "Dentist",
      "neighborhood": "North",
      "services": [
        "implants"
      ]
    }
  ],
  "minimumBusinesses": 3
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("northpeak_data/local-market-opportunity-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("northpeak_data/local-market-opportunity-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call northpeak_data/local-market-opportunity-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,northpeak_data/local-market-opportunity-intelligence"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZOhnmMTxF8GIEndNw/builds/NopEBkKvxTbH9Gd6s/openapi.json