# Nike Product Scraper — Sale Prices, Discounts & Style Codes (`jamhimself/nike-search-scraper`) Actor

Scrape Nike.com search into structured Nike product data — titles, sale prices, discounts, colorways, style codes, images. No API key, no login, bulk, pay per result.

- **URL**: https://apify.com/jamhimself/nike-search-scraper.md
- **Developed by:** [Jaime Martinez](https://apify.com/jamhimself) (community)
- **Categories:** E-commerce, Agents, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 product results

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/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

## Nike Product Scraper — Sale Prices, Discounts & Style Codes (No API Key)

Scrape Nike.com search results into clean, structured Nike product data — no API key, no login. This Nike scraper turns any search query into a bulk dataset of product titles, current and full prices, sale discounts, colorways, style codes, and image URLs. It's a practical sneaker scraper and Nike sale price tracker for developers, analysts, and AI pipelines that need Nike product data extraction without maintaining a scraper or reverse-engineering the nike.com search API. Pay per result.

Under the hood it uses Chrome TLS impersonation, residential US proxies, and automatic session rotation to clear anti-bot walls — so you scrape Nike.com without an API and without managing proxies or logins yourself.

### ⚡ Quick start

Paste this into the Actor's **Input** (JSON view) and hit **Start**:

```json
{
  "searchQuery": "air max",
  "maxResults": 40
}
```

Each result row looks like:

```json
{
  "title": "Nike Air Max 90",
  "subtitle": "Men's Shoes",
  "productCode": "CN8490-002",
  "color": "White",
  "price": 79.97,
  "fullPrice": 130,
  "discountPercentage": 38,
  "onSale": true,
  "url": "https://www.nike.com/t/air-max-90-mens-shoes-CN8490-002"
}
```

Or run it from the API:

```
POST https://api.apify.com/v2/acts/jamhimself~nike-search-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN
```

### What you get

| Field | Description |
|---|---|
| `title` / `subtitle` | Product name and category (e.g. "Men's Shoes") |
| `color` / `colorDescription` | Colorway |
| `price` | Current price |
| `fullPrice` / `discountPercentage` / `onSale` | Original price and discount |
| `productType` | FOOTWEAR / APPAREL / EQUIPMENT |
| `productCode` | Nike style code (e.g. `IW6954-121`) |
| `featuredAttributes` | Flags like `JUST_IN`, `SALE` |
| `image` | Product image URL |
| `url` | Nike product page |

### Use cases

- **Nike sale price tracking** — pull current vs. full prices and discount percentages across a keyword to monitor markdowns over time.
- **Sneaker market research** — size demand and compare colorways, prices, and product types for a search term.
- **Competitor & assortment monitoring** — track which styles are on sale or newly listed in a category.
- **Sourcing & reselling** — build shortlists of sneakers by style code, price, and discount.
- **Feed an LLM / RAG pipeline** — hand structured Nike product data to an AI workflow.
- **Dataset building** — assemble a clean sneaker and apparel dataset for analysis or ML.

### Input

- **searchQuery** — what to search Nike.com for. Example prefill: `air max` (or `pegasus`, `tech fleece`).
- **startUrls** — (optional) paste Nike search URLs directly, e.g. `https://www.nike.com/w?q=air%20max`. Overridden by searchQuery if both are set.
- **maxResults** — maximum number of products to return; paginates automatically via Nike's product wall API. Default `60`, up to `1000`.

### Pricing

Pay per product delivered. No subscription.

*A quick review on the Apify Store really helps other builders find it.*

# Actor input Schema

## `searchQuery` (type: `string`):

What to search Nike.com for, e.g. "air max", "pegasus", "tech fleece".

## `startUrls` (type: `array`):

Alternatively, paste Nike search URLs directly (e.g. https://www.nike.com/w?q=air%20max). Overridden by searchQuery if both are set.

## `maxResults` (type: `integer`):

Maximum number of products to return (the first page yields ~200+; deeper paging uses Nike's product wall API).

## Actor input object example

```json
{
  "searchQuery": "air max",
  "maxResults": 60
}
```

# Actor output Schema

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

One row per 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 = {
    "searchQuery": "air max"
};

// Run the Actor and wait for it to finish
const run = await client.actor("jamhimself/nike-search-scraper").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 = { "searchQuery": "air max" }

# Run the Actor and wait for it to finish
run = client.actor("jamhimself/nike-search-scraper").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 '{
  "searchQuery": "air max"
}' |
apify call jamhimself/nike-search-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/l9KDKfbTT8aA0JatR/builds/uQsDJ5iQfOIDmrbcN/openapi.json