Scrape Amazon products‘ price with no code

With the rapid growth of e-commerce, having insights into competitors‘ pricing has become invaluable. This article guides through scraping product data from Amazon to monitor prices over time – all without needing to code.

We will implement a workflow using ScrapingBee, Make and Airtable to regularly extract pricing from Amazon and store to a database.

Why Scrape Amazon for Pricing Data?

Amazon captured 38.7% of the US ecommerce market in 2021, totalling over $669 billion in sales.

[chart]

Price monitoring reveals trends across top categories by revenue:

Category	2021 Revenue
Electronics & Media	$8.19 billion
Toys & Baby	$7.84 billion
Home & Kitchen	$6.44 billion

Armed with this competitor pricing data, you can:

✔️ Adjust pricing models to remain competitive
✔️ Uncover seasonal or holiday price changes
✔️ Optimize promos/sales around price drops
✔️ Analyze price elasticity by product type

Getting Started

To follow along, you will need accounts with:

ScrapingBee – Web scraping API
Make – Workflow automation tool
Airtable – Database & spreadsheet

We will use ScrapingBee to extract Amazon pricing data, Make to coordinate the workflow, and Airtable to store results.

Configuring the ScrapingBee Integration

ScrapingBee provides proxies and browsers to scrape sites without getting blocked.

To scrape Amazon, generate an API key from your dashboard and add it as a connection in Make.

// Sample API Key 
6v7n6vo3g9nunvyyg948yun7ntvun69vno7yb9om

The scraping job is configured by:

1. Providing the Amazon product URL
2. Adding JSON Extraction Rules to parse pricing data
3. Enabling proxy rotation to avoid blocks

Here is a sample configuration:

// Extraction Rules
{
  "results": {
    "selector": "div.s-result-item", 
    "output": {
      "name": "h2 > a",
      "pricing": ".a-price-whole" 
    }
  }
}  

// Parameters 
URL: https://www.amazon.com/s?k=sneakers
Use Proxies: Yes

Now ScrapingBee can reliably extract Amazon pricing without getting blocked!

Storing Results in Airtable

Airtable provides a spreadsheet-database hybrid perfect for storing scraped results over time.

We will set up a table containing:

Name	Price	Scraped Date

And append scraped results from Amazon each day.

Viewing pricing history for a product over the last month, we can visualize trends:

[price history chart]

Using Airtable‘s filtering capabilities, we can query for:

• Most volatile products week-over-week
• Products with prices decreases greater than 20% to take action
• Average price decrease across categories

Empowering comprehensive pricing analysis and monitoring!

Conclusion

With this automated no code Amazon scraping workflow, you can gain an invaluable competitive pricing advantage across industries:

✔️ Undercut competitor prices
✔️ Optimize promotional discount depths and timing
✔️ React quickly if competitors have flash sales
✔️ Uncover seasonal holiday pricing deadzones

Hope this end-to-end tutorial helps you leverage proxies and automation to unlock hidden insights in Amazon‘s catalog!

What other product data would you want to collect and analyze? Let me know in the comments!