# Amazon Influencers Profile (`solid-scraper/amazon-influencers-profile`) Actor

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- **URL**: https://apify.com/solid-scraper/amazon-influencers-profile.md
- **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community)
- **Categories:** E-commerce, Lead generation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

### Amazon Influencers Profile 🔍

**Amazon Influencers Profile** is a scraper that collects influencer metadata from Amazon Storefront profiles—helping you quickly understand an **Amazon influencer profile** (also known as an **Amazon influencer page** or **Amazon creator profile**) at scale. It’s built for teams and researchers who want an **Amazon influencer storefront profile** overview, including details like the influencer name, profile description, post counts, and whether they appear to be an affiliate creator.

Whether you're a marketer, affiliate manager, or data enthusiast, this actor streamlines **Amazon influencer profile setup** and ongoing **manage Amazon influencer profile** workflows by saving you hours of manual review. 🚀

***

### Why choose Amazon Influencers Profile?

| Feature | Benefit |
|---|---|
| ✅ **Scrapes Amazon Storefront profiles** | Extracts influencer metadata (name, description, posts count, and affiliate status) in one run |
| ✅ **Country support via `country`** | Pulls results from the selected Amazon storefront domain using your provided **country code** |
| ✅ **Built-in proxy support for reliable scraping** | Improves consistency when scraping publicly available data at scale |
| ✅ **Resilience through fallbacks** | Includes fallbacks for extracting key fields like post counts and descriptions |
| ✅ **Structured JSON output** | Produces clear, analytics-ready fields for easier downstream use |
| ✅ **Designed for batches of influencer usernames** | Lets you process multiple **Amazon influencer account** entries in a single execution |

***

### Key features

- 🌐 **Amazon influencer profile scraping**: Collects metadata from an Amazon Storefront profile and returns it as structured data
- 📄 **Profile description extraction**: Captures the **Amazon influencer bio**-style description from the storefront page
- 📊 **Posts count tracking**: Extracts `posts_count` for quick sizing and filtering (e.g., active vs. niche creators)
- 🛡️ **Reliability with proxy support**: Uses built-in proxy support to improve scrape stability across requests
- 🔎 **Affiliate status detection**: Returns `affiliate_status` to help you identify whether the influencer appears to earn revenue
- ✅ **Top creator & curation indicators**: Includes `is_top_creator` and `has_curations` flags for faster qualification
- 💾 **Dataset-ready results**: Pushes results to an Apify dataset as a JSON array for easy export and analysis

***

### Input

Provide input via an `input.json` file. Example structure:

```json
{
  "influencer_names": ["sweetsavingsandthings"],
  "country": "US"
}
```

#### Input Fields

| Field | Required | Description |
|---|---|---|
| `influencer_names` | No | List of Amazon influencer usernames to scrape (e.g., `sweetsavingsandthings`). |
| `country` | No | The country code (e.g., `US`, `UK`, `CA`). The actor uses this to build the correct Amazon storefront domain. |

***

### Output

After execution, the actor saves each profile’s data in JSON format (pushed via `Actor.push_data`).

Example output:

```json
[
  {
    "influencer_username": "sweetsavingsandthings",
    "name": "Sweetsavingsandthings",
    "country": "US",
    "domain": "www.amazon.com",
    "profile_description": "Example profile description text",
    "profile_link": "https://www.amazon.com/shop/sweetsavingsandthings",
    "is_top_creator": false,
    "affiliate_status": "None",
    "has_curations": false,
    "posts_count": 123,
    "scraped_at": "2026-06-02T00:00:00.000Z",
    "success": true
  }
]
```

#### Output Fields

| Field | Type | Description |
|---|---|---|
| `influencer_username` | string | The influencer username that was processed |
| `name` | string | Extracted influencer name (falls back to a formatted username if missing) |
| `country` | string | The country code used for the scrape |
| `domain` | string | The storefront domain built from the provided `country` |
| `profile_description` | string | The influencer’s profile description (bio-style text) |
| `profile_link` | string | The full Storefront profile URL |
| `is_top_creator` | boolean | Flag indicating whether the influencer appears to be a “Top Creator” (based on page content and/or high post counts) |
| `affiliate_status` | string | Affiliate monetization status detected from the profile page (e.g., may be `Earns revenue` or `None`) |
| `has_curations` | boolean | Flag indicating whether the influencer has curations/content tabs present |
| `posts_count` | number | Extracted number of posts (with fallback extraction logic) |
| `scraped_at` | string | ISO timestamp (UTC) for when the profile was scraped |
| `success` | boolean | `true` when scraped successfully; `false` when an error occurred |
| `error` | string | Present only when `success` is `false` (e.g., HTTP status code or exception message) |

You can export the dataset to JSON or CSV from the Apify UI after the run completes.

***

### How to use Amazon Influencers Profile (via Apify Console)

1. **Open Apify Console**\
   Log in at [console.apify.com](https://console.apify.com) and go to the **Actors** section.

2. **Find the actor**\
   Search for **Amazon Influencers Profile** and open the actor details page.

3. **Add your input**\
   In the **INPUT** panel, enter `influencer_names` (a list of Amazon influencer usernames) and optionally `country` (like `US`, `UK`, or `CA`).\
   The actor accepts the usernames as plain strings (no special formatting required).

4. **Start the run**\
   Click **Run** to begin scraping the **Amazon influencer profile** information for each username.

5. **Monitor logs**\
   Watch the runtime logs to see which profile is being processed and whether any errors occur (when `success: false`).

6. **Review results in the dataset**\
   When the run finishes, open the **OUTPUT** tab to view the dataset where the actor pushed the JSON array of profile objects.

7. **Export data**\
   Use Apify’s dataset export tools to download results (commonly as JSON or CSV) for use in your reporting, lead sourcing, or research workflow.

No coding required — get accurate **Amazon influencer profile** results in minutes. ✅

***

### Advanced features & SEO optimization

- 🧩 **Designed specifically for Amazon Storefront profiles**: Built to collect **Amazon influencer page** metadata such as description, post counts, and storefront links—ideal for an **Amazon affiliate influencer** audit
- 📊 **Qualification-ready fields**: Outputs `is_top_creator`, `affiliate_status`, `has_curations`, and `posts_count` so you can filter an **Amazon creator profile** quickly
- 🔁 **Fallback logic for key fields**: Includes additional extraction strategies for `profile_description` and `posts_count` to improve coverage on varying page layouts
- 🌍 **Country-aware storefront support**: Use `country` to scrape from the selected storefront domain, supporting **Amazon influencer storefront profile** research across regions
- 🏎️ **Batch processing for setup and ongoing monitoring**: Run the actor repeatedly as part of **Amazon influencer program profile** management and updates

***

### Best use cases

- 📈 **Affiliate marketing qualification**: Identify **Amazon influencer affiliate** creators by reviewing `affiliate_status` and `posts_count` in a single export
- 🔎 **Influencer research & benchmarking**: Compare **Amazon influencer analytics profile** signals like posts volume and storefront description quality across multiple **Amazon influencer account** usernames
- 🧠 **Market research for creator trends**: Spot patterns in `has_curations` and “Top Creator”-style indicators to understand engagement or content structure
- 🧾 **Cataloging creator portfolios**: Build an **Amazon influencer storefront profile** directory with direct `profile_link` URLs and standardized metadata
- 🗂️ **Data enrichment pipelines**: Feed structured JSON into spreadsheets or BI tools to track **Amazon influencer profile setup** status and ongoing changes over time
- 🧑‍💻 **Analyst workflows**: Use `scraped_at` and consistent fields to power dashboards about creator activity and storefront presence

***

### Technical specifications

- **Supported Input Formats**
  - ✅ `influencer_names`: array of influencer usernames (strings)
  - ✅ `country`: country code like `US`, `UK`, `CA`

- **Proxy Support**
  - ✅ Built-in proxy support for reliable scraping of publicly available storefront pages

- **Retry Mechanism**
  - ✅ Includes retries and fallbacks for resilience (especially around extracting structured values)

- **Dataset Structure**
  - ✅ JSON array of profile objects with fields including `success`, `profile_link`, `posts_count`, and `scraped_at`

- **Rate Limits & Performance**
  - ✅ Processes profiles in a batch loop and includes a small delay between requests to improve stability

- **Limitations**
  - ❌ Private or restricted content may not return meaningful results because the actor relies on publicly available storefront HTML
  - ❌ Some fields (like `profile_description` or `posts_count`) may be empty or `0` if the page layout doesn’t expose extractable data

***

### FAQ

#### What does Amazon Influencers Profile return?

✅ It returns a JSON array of profile objects for each username you provide. Each object includes fields like `influencer_username`, `name`, `profile_description`, `posts_count`, `affiliate_status`, `profile_link`, and `scraped_at`, along with a `success` flag.

#### Which countries are supported?

✅ You can pass a `country` code such as `US`, `UK`, or `CA`. The actor uses that value to build the correct storefront domain for the **Amazon influencer profile** it scrapes.

#### Do I need full influencer URLs, or can I submit usernames?

✅ You can submit just the usernames in `influencer_names`. The actor constructs the storefront URL internally for the **Amazon influencer page**.

#### Is it possible to scrape an influencer profile that doesn’t exist or errors out?

✅ Yes. The actor outputs an entry with `success: false` for that username and includes an `error` field (for example, an HTTP status code or the exception message).

#### Where can I find the scraped results?

✅ After the run completes, the actor pushes results to an Apify dataset. You can open the **OUTPUT** tab and export the dataset for reporting or analysis.

#### Can I use the results for analytics and CRM enrichment?

✅ Yes. The output is structured and includes consistent fields like `posts_count`, `affiliate_status`, and `profile_link`, making it suitable for data analysis and downstream automation.

#### Does it extract affiliate status and top-creator indicators?

✅ It returns `affiliate_status`, plus boolean flags like `is_top_creator` and `has_curations` based on storefront page content.

***

### Support & feature requests

Have questions about **Amazon Influencers Profile** or want to request enhancements? 💡

- 💡 **Feature Requests**: Tell us what you want next, such as more export options, additional profile fields, or improvements to parsing coverage for **Amazon influencer storefront profile** pages.
- 📧 **Contact**: Reach out at <dataforleads@gmail.com>.

Your feedback helps shape the roadmap for improving Amazon influencer profile scraping reliability and usability.

***

### Closing CTA / Final thoughts

*If you’re looking for an SEO-optimized, reliable way to manage an Amazon influencer profile workflow at scale, **Amazon Influencers Profile** is built for you.*

# Actor input Schema

## `influencer_names` (type: `array`):

List of Amazon influencer usernames to scrape.

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

The country code (e.g., US, UK, CA).

## Actor input object example

```json
{
  "influencer_names": [
    "sweetsavingsandthings"
  ],
  "country": "US"
}
```

# 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 = {
    "influencer_names": [
        "sweetsavingsandthings"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("solid-scraper/amazon-influencers-profile").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 = { "influencer_names": ["sweetsavingsandthings"] }

# Run the Actor and wait for it to finish
run = client.actor("solid-scraper/amazon-influencers-profile").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "influencer_names": [
    "sweetsavingsandthings"
  ]
}' |
apify call solid-scraper/amazon-influencers-profile --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=solid-scraper/amazon-influencers-profile",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/JSNLfitE86jvOgSof/builds/Xac8GGs4mXX3Lfy0l/openapi.json