# Meta Ads Winning Product Finder (Laya & JEV AI) (`eternallabs/meta-ads-product-finder`) Actor

Discover winning ecommerce & dropshipping products on Facebook & Instagram Ad Library. Analyze ad persistence, longevity, repeated advertisers, landing pages, and market signals with Laya & JEV AI.

- **URL**: https://apify.com/eternallabs/meta-ads-product-finder.md
- **Developed by:** [Jona](https://apify.com/eternallabs) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Meta Ads Product Finder

> **Discover ecommerce and dropshipping winning products with persistent advertising signals on Facebook and Instagram.**

Find products being actively advertised on **Meta Ads** (**Facebook Ads** and **Instagram Ads**) and identify high-potential ecommerce items with strong ad longevity, repeated advertisers, and verified landing pages for your **product research**, **dropshipping**, and **ecommerce** validation.

***

### Why Meta Ads Product Finder?

Most Meta Ad Library scrapers merely dump raw ads without giving you any product intelligence. **Meta Ads Product Finder** is an end-to-end product research and opportunity discovery system powered by **Laya & JEV System-1 Decision Intelligence**.

Instead of guessing what sells, it detects which ecommerce products have **continuous commercial advertising support**, verifies that stores are actively driving traffic to them, and scores opportunities based on empirical market persistence.

#### Core Questions Answered

1. **"What products are competitors actively advertising right now?"**
2. **"Which products have persistent advertising signals (running 30, 60, or 90+ days)?"**
3. **"Are multiple distinct brands successfully testing or scaling the same product?"**

***

### Key Features

- **Ad Longevity & Persistence Telemetry**: Measures continuous ad running duration (from *New* to *Long-Running* 90+ days).
- **Product Normalization & Clustering**: Groups creative variations and aliases from different advertisers into a single canonical product record.
- **Landing Page Inspection**: Inspects the destination store to detect ecommerce platforms (**Shopify**, **WooCommerce**, etc.), retail pricing, currency, discounts, and JSON-LD schema.
- **Search Trend Enrichment**: Enriches candidate products with normalized search query interest.
- **Decision Engine (Laya & JEV AI)**: Delivers clear, calibrated decision tiers (`INVESTIGATE`, `WATCH`, `LOW_SIGNAL`, `AVOID`) with transparent positive signals and risk rationales.
- **No Fabricated Spend**: Respects Meta's public Ad Library structure. Focuses on verifiable signals (persistence, platforms, creatives, multi-advertiser adoption) rather than inventing unverified spend numbers.

***

### Ad Longevity Classifications

| Ad Duration (Days) | Classification | Signal Interpretation |
| :--- | :--- | :--- |
| **90+ Days** | `LONG-RUNNING` | Proven evergreen demand; sustained advertiser investment |
| **61–90 Days** | `HIGH_PERSISTENCE` | High probability of consistent campaign profitability |
| **31–60 Days** | `STRONG_PERSISTENCE` | Established product scaling beyond initial test phase |
| **15–30 Days** | `ESTABLISHED` | Product validated through multi-week creative cycles |
| **8–14 Days** | `EARLY` | Early-stage traction; worth monitoring |
| **0–7 Days** | `NEW` | Fresh creative test or newly launched product |

***

### Example Input (JSON)

```json
{
  "country": "US",
  "keywords": [
    "portable blender",
    "pet hair remover",
    "lumbar support pillow",
    "car cleaning gel"
  ],
  "maxAds": 100,
  "activeStatus": "ACTIVE",
  "minimumAdDays": 7,
  "minimumAdvertisersPerProduct": 1,
  "includeLandingPages": true,
  "includeTrendAnalysis": true,
  "includeAIAnalysis": true,
  "maxProducts": 25,
  "decisionEngine": "laya"
}
```

***

### Example Output (JSON)

```json
{
  "product_name": "Portable Blender",
  "canonical_product_name": "Portable Blender",
  "country": "US",
  "opportunity_score": 87,
  "decision": "INVESTIGATE",
  "advertiser_count": 3,
  "active_ad_count": 8,
  "creative_count": 5,
  "longest_ad_duration_days": 82,
  "average_ad_duration_days": 54,
  "advertising_signal_score": 89,
  "persistence_score": 88,
  "competition_signal": 60,
  "trend_score": 82,
  "trend_status": "rising",
  "product_category": "kitchen",
  "landing_pages": [
    {
      "final_url": "https://blendpulse-shop.myshopify.com/products/pro-portable-blender",
      "domain": "blendpulse-shop.myshopify.com",
      "http_status": 200,
      "price": 39.99,
      "currency": "USD",
      "ecommerce_platform": "shopify",
      "is_product_page": true
    }
  ],
  "advertisers": [
    "BlendPulse Official",
    "FreshJuice Direct"
  ],
  "positive_signals": [
    "Ad campaigns have run continuously for 82+ days (HIGH_PERSISTENCE)",
    "Advertised across 2 distinct store brands/pages",
    "Multiple creative iterations observed (5 variants)",
    "Search trend telemetry shows positive commercial momentum",
    "Active DTC landing page detected with verifiable product offer"
  ],
  "risks": [
    "Commercial ad spend/impressions are not published by Meta for commercial ads"
  ],
  "why_this_product": "INVESTIGATE: Strong commercial advertising presence detected in US. 2 advertiser(s) running 8 active ad(s) with longest active duration of 82 days (HIGH_PERSISTENCE). Recommended for product sourcing and margin validation.",
  "data_quality": "high",
  "source": "Meta Ad Library"
}
```

***

### End-of-Run Summary

At the end of every run, a high-level summary is pushed to the dataset and Key-Value store:

```json
{
  "products_analyzed": 25,
  "products_investigate": 6,
  "products_watch": 11,
  "products_low_signal": 6,
  "products_avoid": 2,
  "top_product": "Portable Blender",
  "country": "US"
}
```

***

### How to Call via API

#### Python (ApifyClient)

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "country": "US",
    "keywords": ["portable blender", "pet gadgets"],
    "maxProducts": 20,
    "minimumAdDays": 14,
}

run = client.actor("your-username/meta-ads-product-finder").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{item['decision']}] {item['product_name']} - Score: {item['opportunity_score']}")
```

#### JavaScript / Node.js

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

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const input = {
    country: 'US',
    keywords: ['portable blender', 'pet gadgets'],
    maxProducts: 20
};

const run = await client.actor('your-username/meta-ads-product-finder').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

#### Apify CLI

```bash
apify call your-username/meta-ads-product-finder --input='{"country":"US","keywords":["portable blender"]}'
```

***

### Monetization Events

- `ad-analyzed`: Charged per commercial ad retrieved and processed.
- `product-qualified`: Charged when an opportunity meets the `INVESTIGATE` or `WATCH` criteria.
- `product-opportunity`: Charged per full intelligence report generated.

# Actor input Schema

## `country` (type: `string`):

2-letter ISO country code (e.g. US, GB, CA, AU, DE, FR, AE).

## `keywords` (type: `array`):

Product names, niches, or problem keywords (e.g. 'portable blender', 'pet hair remover', 'home gadgets').

## `maxAds` (type: `integer`):

Total number of commercial ads to retrieve and process.

## `activeStatus` (type: `string`):

Filter by active status in Meta Ad Library.

## `minimumAdDays` (type: `integer`):

Filter for ads running continuously for at least this many days.

## `minimumAdvertisersPerProduct` (type: `integer`):

Filter for products advertised by multiple distinct brands/pages.

## `includeLandingPages` (type: `boolean`):

Fetch and analyze landing pages to extract product prices, Shopify/WooCommerce detection, and JSON-LD metadata.

## `includeTrendAnalysis` (type: `boolean`):

Enrich products with search trend direction and related query telemetry.

## `includeAIAnalysis` (type: `boolean`):

Generate opportunity scores and structured decision rationales.

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

Maximum number of ranked product opportunities in final output.

## `decisionEngine` (type: `string`):

System-1 decision engine: 'laya' (default open-source), 'jev', or 'rules'.

## Actor input object example

```json
{
  "country": "US",
  "keywords": [
    "portable blender",
    "pet hair remover",
    "lumbar support pillow",
    "car cleaning gel"
  ],
  "maxAds": 100,
  "activeStatus": "ACTIVE",
  "minimumAdDays": 7,
  "minimumAdvertisersPerProduct": 1,
  "includeLandingPages": true,
  "includeTrendAnalysis": true,
  "includeAIAnalysis": true,
  "maxProducts": 30,
  "decisionEngine": "laya"
}
```

# Actor output Schema

## `products` (type: `string`):

Full dataset of qualified product opportunities, persistence metrics, and decision scores.

## `csv` (type: `string`):

Export CSV spreadsheet with product names, opportunity scores, and ad persistence metrics.

## `summary` (type: `string`):

Run metrics detailing total products analyzed, investigate counts, and top ranked product.

# 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 = {
    "country": "US",
    "keywords": [
        "portable blender",
        "pet hair remover",
        "lumbar support pillow",
        "car cleaning gel"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("eternallabs/meta-ads-product-finder").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 = {
    "country": "US",
    "keywords": [
        "portable blender",
        "pet hair remover",
        "lumbar support pillow",
        "car cleaning gel",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("eternallabs/meta-ads-product-finder").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 '{
  "country": "US",
  "keywords": [
    "portable blender",
    "pet hair remover",
    "lumbar support pillow",
    "car cleaning gel"
  ]
}' |
apify call eternallabs/meta-ads-product-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,eternallabs/meta-ads-product-finder"
        }
    }
}
```

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/qWlfkoj55D9CXbBgE/builds/vYlnH0e4ArdnvDjvM/openapi.json