# Amazon Market Intelligence Scraper (`shahab_2025/amazon-market-intelligence`) Actor

Amazon Market Intelligence Scraper 🚀

A high-performance, enterprise-grade Amazon scraper designed for sellers, brand managers, and market researchers. Effortlessly scrape detailed product data, track pricing trends across dynamic price buckets, and export reports directly to Excel or JSON.

- **URL**: https://apify.com/shahab\_2025/amazon-market-intelligence.md
- **Developed by:** [Qudrat Ullah](https://apify.com/shahab_2025) (community)
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

### Python Playwright template

### Included features

- **[Apify SDK](https://docs.apify.com/sdk/python/)** for Python - a toolkit for building Apify [Actors](https://apify.com/actors) and scrapers in Python
- **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input
- **[Request queue](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-request-queues)** - queues into which you can put the URLs you want to scrape
- **[Dataset](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-datasets)** - store structured data where each object stored has the same attributes
- **[Playwright](https://pypi.org/project/playwright/)** - a browser automation library

### Resources

- [Playwright for web scraping in 2023](https://blog.apify.com/how-to-scrape-the-web-with-playwright-ece1ced75f73/)
- [Scraping single-page applications with Playwright](https://blog.apify.com/scraping-single-page-applications-with-playwright/)
- [How to scale Puppeteer and Playwright](https://blog.apify.com/how-to-scale-puppeteer-and-playwright/)
- [Integration with Zapier](https://apify.com/integrations), Make, GitHub, Google Drive and other apps
- [Video guide on getting data using Apify API](https://www.youtube.com/watch?v=ViYYDHSBAKM)
- A short guide on how to build web scrapers using code templates:

[web scraper template](https://www.youtube.com/watch?v=u-i-Korzf8w)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the Actor use the following command:

```bash
apify run
```

### Deploy to Apify

#### Connect Git repository to Apify

If you've created a Git repository for the project, you can easily connect to Apify:

1. Go to [Actor creation page](https://console.apify.com/actors/new)
2. Click on **Link Git Repository** button

#### Push project on your local machine to Apify

You can also deploy the project on your local machine to Apify without the need for the Git repository.

1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action.

   ```bash
   apify login
   ```

2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my).

   ```bash
   apify push
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## `search_query` (type: `string`):

What do you want to research?

## `max_pages` (type: `integer`):

Number of search-result pages to scrape (ignored while Dynamic Price Range Scan is active).

## `deep_market_scan` (type: `boolean`):

Automatically splits the query into price buckets to pull past Amazon's ~20-page cap and harvest 500+ unique products.

## `dynamic_price_scan` (type: `boolean`):

Tick to define custom price buckets below. Overrides page counts while active.

## `min_price` (type: `integer`):

Lower bound of the price range to scan.

## `max_price` (type: `integer`):

Upper bound of the price range to scan.

## `price_step` (type: `integer`):

Width of each price bucket between Min Price and Max Price.

## `pages_per_bucket` (type: `integer`):

Number of result pages to scrape within each price bucket.

## `include_catchall` (type: `boolean`):

Adds a trailing open-ended bucket above Max Price so nothing outside the configured range is missed.

## Actor input object example

```json
{
  "search_query": "wireless earbuds",
  "max_pages": 3,
  "deep_market_scan": false,
  "dynamic_price_scan": true,
  "min_price": 0,
  "max_price": 200,
  "price_step": 10,
  "pages_per_bucket": 10,
  "include_catchall": true
}
```

# 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 = {
    "search_query": "wireless earbuds"
};

// Run the Actor and wait for it to finish
const run = await client.actor("shahab_2025/amazon-market-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 = { "search_query": "wireless earbuds" }

# Run the Actor and wait for it to finish
run = client.actor("shahab_2025/amazon-market-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 '{
  "search_query": "wireless earbuds"
}' |
apify call shahab_2025/amazon-market-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,shahab_2025/amazon-market-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/dkwAXHeMfkggc4cPU/builds/GmXdnmU6TKPJA8DoN/openapi.json