Challenges User face in Amazon Data Scraping

Introduction

We know that data has value, in currencies, and otherwise. It’s recognized as a force that drives businesses towards knowledgeable decisions. In fact, many eCommerce stores frequently consult web scraping services to drive continuous growth through data.

These days, web data extraction appears a lot easier than it is. Sure, with a small focus group, things run smoothly. But, as soon as you sit down to scale, things go very wrong very quickly. That’s why we’re going to talk about the challenges of web scraping that, if not acknowledged timely, can raise a ruckus. 

A Brief Introduction to Web Scraping in Amazon

There are a lot of reasons you might want to scrape data from Amazon. As a competing retailer, you might want to keep a database of their pricing data, so you can try to match them. You might want to keep an eye on competitors selling through the Amazon Marketplace. Maybe you want to aggregate review scores from around the Internet, and Amazon is one of the sources you’ll want to use. You could even be selling on Amazon yourself, and using the scraper to keep ahead of others doing the same.

Amazon seems to have slackened up in recent years. This thread from 2014 indicates that Amazon doesn’t bother with enforcing low-scale scraping blocks. They have automated systems that will slap you with a ban if you cross their path, but they aren’t actively and persistently seeking out and banning all data scrapers. It makes sense; a retailer of their size has so much data to filter through on an hourly basis that it would be impossible to ban every single data scraper.

It can be a little bit more complex though, but it doesn’t stop people from doing it, because it’s all about collecting data that they can use for a variety of purposes.

Usually, web scraping can be done for:

  • Ranking pages
  • Accessibility and vulnerability checks
  • Extracting data from SERPs (keywords, rankings, etc.)
  • Collecting website data (products, prices, ratings, reviews, etc.)
  • Other purposes.

Before you continue, here are seven things you should know about making Amazon the target of your data scraping. By keeping them in mind, you should be able to keep yourself safe from both automated bans and legal action.

Major challenges in web scraping

  1. Amazon is Very Liberal with IP Bans

The first thing to keep in mind if you’re going to be harvesting data from Amazon is that Amazon very much is liberal with their bans. You won’t be harvesting data while logged into an account, at least, not if you’re smart. That means the only way you’ll be able to be banned is through an IP ban. 

A proxy server, in case you aren’t aware, is a way to filter your IP address. The website, in this case Amazon, will see your connection as coming from the proxy server rather than your home connection.

  1. Amazon is Very Good at Detecting Bots

Think about it. If you were tasked with detecting bots and filtering them out from legitimate traffic, what would you look for? There are simple things, like the user agent and whether or not it identifies itself as a bot. Those are easily spoofed, though.

Amazon is very good at distinguishing between bots actions and human actions. Therefore, to avoid your bots being banned, you need to mimic human behavior as much as possible. Don’t be repetitive. Don’t be predictable. Vary your actions, your timing, and your IP. It’s harder to identify a bot when it only accesses a couple of pages. 

  1. Always Review Scraping Software Before Using

This is just a general tip for any time you’re getting software from online, particularly in a gray hat or black hat arena. Things like scraping software may not be illegal, but they have a bad reputation, and as such are often the targets of malicious agents. This is even more important if you’re using a scraper that requires you login, either with credentials for Amazon or credentials for anything else.

  1. Never Sell Scraped Data or Use it to Make a Profit

I mentioned above that you shouldn’t copy product descriptions, because you’ll end up shooting yourself in the foot. This is because of Google’s algorithm, which heavily penalizes copied content. Google knows, obviously, that the product descriptions originated on Amazon. When they see your content, they’ll penalize it, because it’s just low-effort copying from a bigger retailer.

  1. A lot of product pages on Amazon have varying page structures

If you have ever attempted to scrape product descriptions and scrape data from Amazon, you might have run into a lot of unknown response errors and exceptions. This is because most of your scrapers are designed and customized for a particular structure of a page. A lot of products on Amazon have different pages and the attributes of these pages differ from a standard template.  This is often done to cater to different types of products that may have different key attributes and features that need to be highlighted. 

Solutions to scraping Amazon Data

If you’re building your own scraper, the solution is to have a lot of money and undying desire to solve any upcoming challenges to complete the process successfully and luckily automate things in the future. However, not everybody has development skills. And definitely not everybody wants to build their own scraping tools, simply because it’s out of their targeted niche and it also requires a lot of manual work first.

While there are a lot of comprehensive API guidelines explaining what APIs are and how they work, we will not dig into it today. However, what’s worth mentioning is that Amazon has its own official API which deals with all the above-mentioned issues but does it more effectively and smoothly.

However, it’s proven that some people are not always satisfied with official APIs and have an interest in looking for third-party APIs either because they want a simpler interface or they want to build their own software.

Conclusions

While some developers like scraping for sport or profit, business owners, especially retail and e-commerce businesses need to crawl Amazon to make price comparisons, forecasting product sales, estimating competition rate, etc. Creating your own scraper is a time-consuming, challenging process and is only for the most enthusiastic enthusiasts out there.

On the other hand, if you’re a decision-maker, you may be interested in APIs to hit your goals directly. Usually, APIs are doing pretty much the same work and solve the same issues, however, more effectively. While APIs may or may not always be cheaper than building your own scraper, they can definitely save time and nerves.

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