# Trending Products Radar (AI-Scored) (`agentumgroup/trending-products-radar`) Actor

Trending Amazon products, each scored 1-10 for sell/promote viability by Claude: demand, competition, buyer-intent search terms, and event-window flags. Raw scrapers tell you WHAT is moving; this tells you whether it's worth acting on.

- **URL**: https://apify.com/agentumgroup/trending-products-radar.md
- **Developed by:** [AgentumGroup](https://apify.com/agentumgroup) (community)
- **Categories:** E-commerce, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Trending Products Radar — AI-Scored Amazon Trends

Raw bestseller scrapers tell you **WHAT is moving**. This Actor tells you **whether it's worth acting on**.

Every run pulls trending product candidates from Amazon's ranking charts (New Releases, Best Sellers, Most Wished For — US and Canada), then scores each one **1–10 with Claude** using a hindsight-validated rubric: demand trajectory, competition saturation, real buyer-intent search terms, and — critically — **event-window timing** (is this product riding a dated event you can still get ahead of?). You get a ranked, decision-ready list instead of 200 undifferentiated product names.

### Why scoring beats raw rank (a validated result)

In an April 2026 backtest we scored 9 trending products and checked their outcomes 3 months later:

- The model's **top pick** was a World Cup match ball — flagged with an explicit event window **3 months before the final**, exactly when acting on it still paid.
- The model's **lowest pick** (a saturated drink-bottle accessory) died, as predicted.
- The score rank-ordered winners and losers almost perfectly — while the **raw trend rank had negative signal** (top-of-chart items were often already peaked).

This is a small, honest sample (n=9, one cohort), not a guarantee — but it's exactly the judgment layer raw scrapers don't have: candidate generation is a commodity, the filter is the value.

### Use cases

- **Dropship / FBA sellers** — triage 200 candidates down to the 5 worth testing, with buyer-intent keywords for listings and ads, and event windows so you don't stock last month's trend.
- **Content & newsletter operators** — a ranked "what to cover this week" feed with ready-made search terms for titles and SEO.
- **Affiliate / commerce media** — competition notes tell you where content is already saturated before you write.
- **AI agents** — a clean, structured "what's trending and is it any good" tool: one call, ranked JSON out.

### Input

| Field | Type | Default | Description |
|---|---|---|---|
| `marketplace` | select | `amazon.com` | `amazon.com` or `amazon.ca` |
| `categories` | multi-select | all 8 | `home-garden`, `kitchen`, `sporting-goods`, `pet-supplies`, `beauty`, `electronics`, `office-products`, `toys-and-games` |
| `trendSource` | select | `new-releases` | Trend signal: **New Releases** (products breaking out before the main charts), `bestsellers`, or `most-wished-for` |
| `maxProductsPerCategory` | integer | 25 | 1–100 candidates per category |
| `minScore` | integer | 0 | Only output products scoring ≥ this (scored mode only) |
| `anthropicApiKey` | secret | — | **Required for scoring.** Your Anthropic API key — used only for scoring, ~$0.01–0.02 of your Anthropic spend per 10 products. Without it you get UNSCORED raw candidates. |

```json
{
    "marketplace": "amazon.com",
    "categories": ["kitchen", "pet-supplies", "toys-and-games"],
    "trendSource": "new-releases",
    "maxProductsPerCategory": 25,
    "minScore": 7,
    "anthropicApiKey": "sk-ant-..."
}
```

### Output

One dataset item per product, ranked best-first:

```json
{
    "rank": 1,
    "name": "Adidas Trionda Official Match Ball 2026",
    "price": 34.99,
    "category": "sporting-goods",
    "url": "https://www.amazon.com/dp/B0EXAMPLE",
    "image": "https://m.media-amazon.com/images/I/example.jpg",
    "trendSignal": {
        "source": "new-releases",
        "rank": 7,
        "asin": "B0EXAMPLE",
        "rating": 4.8,
        "reviewsCount": 312,
        "currency": "USD",
        "marketplace": "US",
        "categoryName": "Sports & Outdoors"
    },
    "score": 9,
    "verdict": "strong_buy",
    "demand_notes": "Demand accelerating into the tournament; official-license products historically spike 2-3 months ahead of the final.",
    "competition_notes": "Single official supplier keeps listing competition low; content competition still thin.",
    "buyer_intent_terms": ["world cup 2026 ball", "trionda official match ball", "adidas trionda review", "best soccer ball 2026", "trionda vs al rihla"],
    "event_window": "FIFA World Cup Jun-Jul 2026",
    "scoredAt": "2026-07-20T12:00:00.000Z"
}
```

A `RUN_SUMMARY` object (mode, counts, upstream run id) is stored in the run's key-value store.

### Cost transparency

Two separate costs, both small and both visible:

1. **This Actor** (your Apify account): platform compute plus the upstream chart scrape at ~$0.005/product. A typical 4-category × 25-product run ≈ $0.50–0.60.
2. **Scoring** (your Anthropic account, via your `anthropicApiKey`): batched calls to `claude-sonnet-4-6`, roughly **$0.01–0.02 per 10 products**. A 100-product run costs you ~$0.10–0.20 in Anthropic credit. No web search, no hidden calls — your key is used only for the scoring requests and never stored.

No key? The run still completes in **unscored mode**: raw ranked candidates with `"verdict": "unscored"` and a clear notice in the log.

### Coverage & data quality

- **Marketplaces:** amazon.com (US), amazon.ca (Canada).
- **Categories:** the 8 highest-signal consumer departments (see input table). More on request.
- **Trend charts:** New Releases / Best Sellers / Most Wished For. Amazon retired its Movers & Shakers pages as a scrapeable surface in mid-2026 (they now render as empty client-side shells) — New Releases is the closest live "breaking out" signal, and it's what we default to.
- Products are deduplicated per chart, ranked by score (then chart rank). Failed scoring batches degrade to unscored rows rather than failing the run.

### Fair use

Scores are model-generated judgments to prioritize your own research — not financial advice. Product data comes from public Amazon ranking pages via a maintained upstream scraper; no personal data is collected.

# Actor input Schema

## `marketplace` (type: `string`):

Amazon marketplace to watch.

## `categories` (type: `array`):

Amazon departments to scan for trending products.

## `trendSource` (type: `string`):

Which Amazon ranking chart supplies the trend candidates. <b>New Releases</b> (default) surfaces products breaking out before they reach the main charts — the closest live proxy to the retired Movers & Shakers surface. <b>Best Sellers</b> = current top sellers. <b>Most Wished For</b> = demand ahead of purchase.

## `maxProductsPerCategory` (type: `integer`):

Cap per category (Amazon publishes at most 100 per chart). Scoring cost scales with this: roughly $0.01-0.02 of your Anthropic spend per 10 products. Prefill is a fast demo (1 category × 10 items, ~90s); raise for full weekly scans (8 × 100).

## `minScore` (type: `integer`):

Only output products scoring at least this (1-10). 0 = no filter. Ignored in unscored mode.

## `anthropicApiKey` (type: `string`):

REQUIRED for scoring — your Anthropic API key (console.anthropic.com), used only for scoring, ~$0.01-0.02 of your Anthropic spend per 10 products. Without a key the Actor still runs but returns UNSCORED rows (raw trend candidates, no AI analysis).

## `scoreResults` (type: `boolean`):

Set to false to run in FREE unscored mode: returns raw trend candidates with no AI scoring and no PPE charges. Ideal for discovery, testing, or budget-sensitive scans. Default: true (scoring enabled when an Anthropic key is also provided).

## Actor input object example

```json
{
  "marketplace": "amazon.com",
  "categories": [
    "kitchen"
  ],
  "trendSource": "new-releases",
  "maxProductsPerCategory": 10,
  "minScore": 0,
  "scoreResults": true
}
```

# 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 = {
    "categories": [
        "kitchen"
    ],
    "maxProductsPerCategory": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("agentumgroup/trending-products-radar").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 = {
    "categories": ["kitchen"],
    "maxProductsPerCategory": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("agentumgroup/trending-products-radar").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 '{
  "categories": [
    "kitchen"
  ],
  "maxProductsPerCategory": 10
}' |
apify call agentumgroup/trending-products-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentumgroup/trending-products-radar"
        }
    }
}
```

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/jMqfYWThDBY2oPXkU/builds/78DfZo6WeaQ7wpCDL/openapi.json