Web scraping, the process of programmatically extracting data from websites, has become an essential tool for businesses looking to gain a competitive edge. By collecting and analyzing publicly available web data at scale, companies can make data-driven decisions, automate processes, and unlock valuable insights.
One of the most popular use cases for web scraping is extracting product and pricing data from ecommerce giants like Amazon. With 63% of all online retail sales in the US occurring on marketplace sites, and Amazon capturing 41% of that market, Amazon‘s product data offers unparalleled market intelligence.
Scraping Amazon data allows you to:
- Price competitively: Monitor competitor prices in real-time and instantly react to price changes.
- Optimize product listings: Analyze top-performing products to improve your own listing titles, descriptions, images and pricing.
- Identify market gaps: Find high-demand, low-competition product niches to enter.
- Generate leads: Collect vendor and seller contact information for B2B outreach.
Historically, scraping Amazon data required building a sophisticated web scraping infrastructure to handle the site‘s complex anti-bot measures. Amazon extensively uses CAPTCHAs, user agent checks, IP rate limiting, and other techniques to block bots, making it challenging to reliably extract data.
However, the rise of no-code web scraping tools like ScrapingBee has made it possible for non-technical users to scrape Amazon with ease. ScrapingBee is an API-based web scraping solution that handles all the backend complexity of extracting data from difficult sites.
Under the hood, ScrapingBee uses a combination of rotating proxies, browser fingerprinting, and machine learning CAPTCHA solving to ensure successful data extraction. The API user simply needs to provide the Amazon URL they want to scrape and ScrapingBee returns the fully rendered HTML.
From there, you can parse out the desired pricing and product data using simple CSS selectors, with no programming required. When combined with a no-code integration platform like Make (formerly Integromat), you can set up a completely automated "set it and forget it" web scraping pipeline.
Step-by-Step Tutorial
Let‘s walk through the process of building an automated Amazon price scraper using ScrapingBee and Make. This system will scrape a list of product ASINs (unique Amazon product identifiers) on a daily basis, extract the current price, and save the data to an Airtable spreadsheet.
Prerequisites
- ScrapingBee account (free tier available)
- Make account (free tier available)
- Airtable account (free tier available)
Step 1: Set up Airtable Base
First, let‘s create an Airtable base to store our scraped pricing data. Create a new base and set up the following columns:
- ASIN (single line text)
- Name (single line text)
- Price (currency)
- Date (date, include time)
Step 2: Create ScrapingBee API Token
Next, sign up for a free ScrapingBee account and generate an API token from the dashboard. We‘ll use this key to authenticate our requests to the ScrapingBee API.
Step 3: Build Make Scenario
Now the fun part – building our automated scraping workflow in Make! Create a new Make scenario and add the following modules:
1. ScrapingBee > Make an API call
- Method: GET
- URL: https://www.amazon.com/dp/[ASIN]
- Extract rules:
{ "name": "#productTitle", "price": { "selector": ".a-price .a-offscreen", "type": "text" } }
Replace [ASIN] with the unique Amazon product ID you want to scrape. You can find the ASIN in the Amazon product URL.
2. Iterator
No configuration needed – this will automatically loop through multiple ASINs if provided.
3. Airtable > Create a Record
- Base: Your newly created base
- Table: Select your table name
- Mapping:
- ASIN: 1. ASIN
- Name: 2. name
- Price: 2. price
- Date: Current date/time
Step 4: Add Multiple Products
Want to scrape more than one product? No problem. Simply modify the Amazon URL in the ScrapingBee module to include multiple comma-separated ASINs:
https://www.amazon.com/dp/ASIN1,ASIN2,ASIN3
The Iterator module will take care of looping through each product and saving it as a separate Airtable record.
Step 5: Schedule and Activate
The last step is to schedule your scenario to run daily to capture price changes over time. Click the clock icon on the ScrapingBee module and set your desired schedule:
Turn on scheduling and activate your scenario. Make will now scrape your products every day and log the prices to Airtable!
Analyzing Your Data
After your scheduled scraper has run for a few days, you‘ll have a spreadsheet full of valuable pricing data. Here are a few ways to analyze and visualize it:
Price Change Alerts
Set up a Make scenario to compare the latest price to the previous day‘s price and send an email alert if it changes by more than a certain threshold. This is an easy way to monitor flash sales and promotions.
Price History Chart
Connect your Airtable base to a BI tool like Google Data Studio or Tableau to create an interactive price history chart. Visualizing the data makes it easy to spot trends and seasonal fluctuations.
Competitor Price Benchmarking
Scrape pricing data for your top competitors‘ products and compare their prices to your own over time. Calculate metrics like the percentage difference and identify which competitors are consistently undercutting you.
FAQs
Is it legal to scrape Amazon?
Web scraping falls into a legal gray area and there is no clear precedent for its legality. However, courts have generally ruled that scraping publicly available data is permissible if done in a way that does not violate a site‘s terms of service or cause damage to the site owner.
To stay on the right side of the law and ethics, follow these guidelines when scraping Amazon:
- Don‘t scrape faster than a human could feasibly browse the site
- Don‘t attempt to access any private user data
- Use the scraped data only for analysis and research, not for republishing
- Respect Amazon‘s robots.txt file
ScrapingBee makes it easy to scrape ethically by default with built-in rate limits and other protections against abusive scraping.
Will ScrapingBee get blocked by Amazon?
It‘s impossible to guarantee any web scraper won‘t get blocked, as Amazon is constantly updating their anti-bot measures. However, ScrapingBee has an extremely high success rate on Amazon and proactively monitors their proxy pool to avoid detection.
In the unlikely event that a request gets blocked, ScrapingBee will automatically retry with a new proxy/user agent to ensure you get your data.
Can I scrape reviews, ratings, images and other product data?
Yes! This tutorial focused on pricing data, but you can use the same techniques to extract any publicly visible data from an Amazon product page. Simply modify the CSS selectors in the Extract Rules to target the desired elements.
For example, here are selectors for a few other common data points:
- Reviews:
#acrCustomerReviewText - Star rating:
#acrPopover - Product images:
#main-image-container img
Refer to ScrapingBee‘s Amazon scraping guide for more tips and tricks.
Conclusion
Amazon is a treasure trove of market data, but extracting that data has traditionally been difficult for non-technical users. No-code tools like ScrapingBee and Make have changed the game, enabling anyone to scrape Amazon with ease.
By automating competitor price monitoring, you can make faster, data-driven pricing decisions and identify opportunities for promotions and discounts. Combining daily price snapshots with your sales data lets you correlate price changes with revenue and determine your pricing sweet spot.
Best of all, once your scraper is set up, it runs on autopilot, giving you a continual stream of fresh data with zero effort. I like to think of automated web scraping as my secret weapon for ecommerce market domination.
So what are you waiting for? Sign up for ScrapingBee and start collecting Amazon data today – your competitors probably already are!
