# Amazon Product Opportunity Finder — AI Niche Analysis (`fuze/amazon-product-opportunity`) Actor

Point it at any Amazon/ecommerce product-listing scraper's dataset and get an AI opportunity read for the niche: demand vs competition, price band, review-gap openings, differentiation angles and a go/skip verdict. For FBA and ecommerce product research.

- **URL**: https://apify.com/fuze/amazon-product-opportunity.md
- **Developed by:** [Fredrik Hansson](https://apify.com/fuze) (community)
- **Categories:** AI, E-commerce
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $154.00 / 1,000 opportunity reports

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

## Amazon Product Opportunity Finder — AI Niche Analysis

Already scraping Amazon? Find out if a niche is worth entering. Point this at **any Amazon/ecommerce product-listing scraper's dataset** (search results or a category) and get an AI opportunity read.

![Amazon Product Opportunity Finder — AI Niche Analysis — input and sample output](https://datatools-hub.vercel.app/actor-shots/amazon-product-opportunity.png)

### 🔗 Chain it after your scraper

Already scraping with **[Amazon Product Scraper (`junglee/Amazon-crawler`)](https://apify.com/junglee/Amazon-crawler)**, **[Amazon Bestsellers Scraper (`junglee/amazon-bestsellers`)](https://apify.com/junglee/amazon-bestsellers)** or the free **[Amazon Scraper (`junglee/free-amazon-product-scraper`)](https://apify.com/junglee/free-amazon-product-scraper)**? Pipe the dataset straight in — paste its dataset ID and get a demand-vs-competition read, price band, review-gap openings and a go/skip verdict for the niche. Works with any Amazon or ecommerce product-listing scraper's output.

### What you get

- **Opportunity score** (0–100) and a **go/skip verdict**
- **Demand vs competition** read
- **Price band** and review volume
- **Review-gap openings** — unmet needs to exploit
- **Differentiation angles** for a new entrant
- **Risks** to watch

### How to use

1. Run any Amazon/ecommerce product scraper on Apify for your keyword/category.
2. Copy its **dataset ID**.
3. Run this actor with that `datasetId`.

```json
{ "datasetId": "YOUR_PRODUCTS_DATASET_ID", "niche": "bamboo cutting board" }
```

For FBA sellers, ecommerce brands and product researchers — the Jungle Scout angle, pay-per-use, on top of scrapers you already run.

### Pricing

Pay per opportunity report — one cost-effective AI pass over the listings. Uses the listing metadata you provide; it does not fabricate sales estimates.

Actively maintained.

### Example output

```json
{
  "niche": "bamboo cutting board",
  "productsAnalyzed": 5,
  "opportunityScore": 38,
  "verdict": "High competition with strong incumbents makes this niche difficult to enter profitably.",
  "priceBand": "12.99–32 (median 24.99)",
  "medianReviews": 340,
  "totalReviews": 7449,
  "demandRead": "The median reviews indicate a solid demand for bamboo cutting boards, but the presence of a few incumbent products with high reviews sugge…",
  "…": "…"
}
```

# Actor input Schema

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

The dataset ID from any Amazon/ecommerce product-listing scraper's run (search results or a category). The actor auto-detects title, price, rating and review-count fields.

## `niche` (type: `string`):

The niche or search term these products are for, used in the report.

## `maxProducts` (type: `integer`):

Cap on how many listings to read.

## `model` (type: `string`):

gpt-4o-mini is the cost-effective default.

## Actor input object example

```json
{
  "maxProducts": 60,
  "model": "gpt-4o-mini"
}
```

# Actor output Schema

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

All rows in the default dataset.

# 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("fuze/amazon-product-opportunity").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("fuze/amazon-product-opportunity").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 fuze/amazon-product-opportunity --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fuze/amazon-product-opportunity"
        }
    }
}
```

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/McWr0FJVYhK2QAKKF/builds/UgE9ucoHP8J773d1s/openapi.json