Bing Shopping Scraper

Extract product offers, prices, sellers, images, ratings, and availability from public Bing Shopping search results.

What does Bing Shopping Scraper do?

Bing Shopping Scraper turns public Bing Shopping result pages into structured product data.

It searches https://www.bing.com/shop for the product keywords or start URLs you provide.

The actor saves product cards from the search page into an Apify dataset.

You can use the dataset for price monitoring, product research, marketplace discovery, ecommerce audits, and competitive intelligence.

The scraper is designed for public search result pages only.

It does not log in, bypass paywalls, or access private accounts.

Who is it for?

Ecommerce analysts

Use the actor to collect competing product offers and prices from Bing Shopping.

Marketplace sellers

Check how your products and competitor products appear in Bing Shopping search results.

Price intelligence teams

Collect price, seller, and shipping snippets for recurring product monitoring workflows.

Affiliate and content teams

Find products, merchants, and image URLs for buying guides and product comparison pages.

Data teams

Feed structured product search data into BI dashboards, spreadsheets, or internal enrichment pipelines.

Why use this actor?

Bing Shopping is a useful comparison-shopping surface that is often overlooked in ecommerce research.

Google Shopping has many scraper options, but Bing Shopping can show different merchants, prices, and product cards.

This actor focuses on a simple, low-cost HTTP implementation.

It avoids browser automation unless the public HTML stops exposing product cards.

That keeps runs cheaper and faster for routine product-search monitoring.

What data can you extract?

Field	Description
query	Search query or query parsed from the start URL
rank	Product rank in the scraped Bing Shopping result pages
title	Product title shown on Bing Shopping
productUrl	Decoded Bing product page URL when available
bingProductUrl	Original Bing Shopping or Bing redirect URL
imageUrl	Product image URL
price	Parsed numeric price
currency	Currency inferred from the price text
priceText	Raw price text shown by Bing Shopping
merchant	Seller or merchant name
rating	Visible rating when Bing shows it
reviewCount	Visible review or rating count when Bing shows it
shipping	Shipping snippet such as free shipping
availability	Availability snippet when visible
sourcePageUrl	Bing Shopping page URL used for the result
scrapedAt	ISO timestamp when the item was scraped

How much does it cost to scrape Bing Shopping?

This actor uses pay-per-event pricing.

You pay a small start fee per run and a per-result fee for product cards saved to the dataset.

The default per-result price is designed around ecommerce monitoring workloads.

Use a small maxItems value for first tests.

Scale up after checking that the output matches your product category.

How to use Bing Shopping Scraper

1. Open the actor on Apify.

2. Add one or more product search queries.

3. Optionally add Bing Shopping start URLs.

4. Set maxItems to the number of product cards you want.

5. Keep proxy disabled unless your environment is blocked.

6. Run the actor.

7. Export the default dataset as JSON, CSV, Excel, XML, or HTML.

Input configuration

Search queries

Use queries for product keywords.

Examples:

• iphone 15 case
• sony headphones
• running shoes men
• laptop stand
• lego star wars

Start URLs

Use startUrls when you already have a Bing Shopping URL.

Example:

https://www.bing.com/shop?q=iphone+15+case&cc=us&setlang=en

Maximum products

maxItems controls the total number of product cards saved across all inputs.

For a quick test, use 10 to 25 results.

For routine monitoring, use a higher value after validating output quality.

Market and locale

Use market and locale to influence Bing's regional search results.

Examples:

• market: us, locale: en-US
• market: gb, locale: en-GB
• market: de, locale: de-DE

Proxy settings

Proxy use is optional.

The default is direct HTTP to keep runs cheap.

Enable Apify Proxy only if Bing blocks your execution environment.

Output example

{
  "query": "iphone 15 case",
  "rank": 1,
  "title": "Apple iPhone case example",
  "productUrl": "https://www.bing.com/shop/productpage?...",
  "bingProductUrl": "https://www.bing.com/shop/productpage?...",
  "imageUrl": "https://th.bing.com/th/id/...",
  "price": 19.99,
  "currency": "USD",
  "priceText": "$19.99",
  "merchant": "Example Store",
  "rating": 4.5,
  "reviewCount": 120,
  "shipping": "Free shipping",
  "availability": "In stock",
  "sourcePageUrl": "https://www.bing.com/shop?q=iphone+15+case",
  "scrapedAt": "2026-06-03T08:00:00.000Z"
}

Tips for best results

Use specific product keywords for cleaner results.

Brand + model searches usually produce better cards than broad category searches.

Use multiple queries when tracking several product families.

Keep maxItems modest for exploratory runs.

Review the first dataset before scheduling large recurring jobs.

Common use cases

Price monitoring

Run the actor daily for important products and compare price changes over time.

Merchant discovery

Find sellers appearing for product categories that matter to your business.

Competitive analysis

Compare product titles, prices, and shipping messages across Bing Shopping results.

Product feed audits

Check whether your products appear for expected search terms.

Regional ecommerce research

Run the same terms with different market and locale settings.

Integrations

You can connect the dataset to Google Sheets, Zapier, Make, Slack, or your own API.

For recurring workflows, schedule the actor in Apify and export the dataset after each run.

For dashboards, pull dataset items with the Apify API and load them into your BI tool.

For alerts, compare new prices against stored prices and notify your team when values change.

API usage with Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/bing-shopping-scraper').call({
  queries: ['iphone 15 case'],
  maxItems: 25
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

API usage with Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('automation-lab/bing-shopping-scraper').call(run_input={
    'queries': ['iphone 15 case'],
    'maxItems': 25,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

API usage with cURL

curl -X POST 'https://api.apify.com/v2/acts/automation-lab~bing-shopping-scraper/runs?token=YOUR_APIFY_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"queries":["iphone 15 case"],"maxItems":25}'

MCP integration

Use the Apify MCP server to run this actor from AI tools, Claude Code, Claude Desktop, and other MCP-compatible clients.

MCP URL:

https://mcp.apify.com/?tools=automation-lab/bing-shopping-scraper

Claude Code setup

$claude mcp add apify-bing-shopping https://mcp.apify.com/?tools=automation-lab/bing-shopping-scraper

After adding the server, ask Claude Code to run the actor with a query, maxItems, and optional locale settings.

Claude Desktop JSON config

Add this server entry to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "apify-bing-shopping": {
      "url": "https://mcp.apify.com/?tools=automation-lab/bing-shopping-scraper"
    }
  }
}

Restart Claude Desktop after saving the config, then use prompts like the examples below.

Example prompts showing MCP usage

Use these MCP prompts in Claude Code, Claude Desktop, or another connected client:

• "Run automation-lab/bing-shopping-scraper for sony headphones, get 20 results, and summarize the price range by merchant."
• "Use the Bing Shopping Scraper to collect laptop stand offers and export the dataset as a comparison table."
• "Search Bing Shopping for five product SKUs, identify the lowest visible price per SKU, and flag items with free shipping."
• "Compare Bing Shopping results for air fryer, espresso machine, and office chair, then group products by seller and price band."

Legality and responsible use

This actor extracts publicly visible Bing Shopping search result data.

Always follow applicable laws, Bing's terms, and your organization's compliance rules.

Do not use the actor to collect private data or bypass access controls.

Use reasonable run sizes and schedules.

Troubleshooting

I got fewer results than requested

Bing may show fewer product cards for a query, or duplicate cards may be skipped.

Try a broader query or add more queries.

Prices are missing for some items

Bing does not show every field on every card.

The actor keeps optional fields nullable when the page does not expose them.

The run returned no items

Check that your query opens public Bing Shopping results in a browser.

If your environment is blocked, enable Apify Proxy and retry with a small maxItems value.

Related scrapers

• Google Shopping Scraper: https://apify.com/automation-lab/google-shopping-scraper
• Bing Search Scraper: https://apify.com/automation-lab/bing-search-scraper
• Google Search Scraper: https://apify.com/automation-lab/google-search-scraper

FAQ

Does this actor visit product detail pages?

The initial version extracts data from Bing Shopping search result cards.

It does not crawl merchant websites or private product pages.

Can I scrape multiple queries in one run?

Yes. Add several values to queries and set maxItems high enough for the combined output.

Can I use start URLs instead of keywords?

Yes. Add public Bing Shopping URLs to startUrls.

Does the actor require a proxy?

No. The default configuration uses direct HTTP.

Enable proxies only if your execution environment is blocked.

What export formats are supported?

Apify datasets can be exported as JSON, CSV, Excel, XML, RSS, or HTML.

Can I schedule this actor?

Yes. Use Apify schedules to run it hourly, daily, weekly, or on a custom cron expression.

Can I integrate it into my app?

Yes. Use the Apify API examples above or the official Apify clients.

Is this a browser scraper?

No. The first implementation uses HTTP and Cheerio because public Bing Shopping HTML contains product cards.

What if Bing changes the page layout?

Open a support issue with an example query and run ID. The extractor can be adjusted for new public HTML markers.

Can it extract seller pages?

No. The actor extracts seller text visible on the result card, not seller profile pages.

Changelog

Initial version: public Bing Shopping product search extraction with query/start URL inputs, price fields, merchant fields, image URLs, shipping snippets, and timestamps.