Most Common Challenges of Amazon Data Scraping and How to Overcome Them

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The e-commerce sector is a rapidly growing and evolving market. The face of this industry is changing almost every year since it was first incepted in the early 1990s. With the rising number of digital consumers, the digital retail market has shown a growth rate of more than 20% over the last 3 years.

This growing industry demands sophisticated analytical techniques to predict market patterns, to analyze consumer behavior, or even to gain a competitive advantage over many players in this business. To augment the effectiveness of these analytical techniques, you need credible, high-quality data. These data are called alternative data and can be derived from multiple sources. Some of the most prominent sources of alternative data in the e-commerce sector are customer reviews, product information, and even geographic data. E-commerce websites are an excellent source for many of these data components. It’s not surprising that Amazon has been at the forefront of the e-commerce business for some time now.

Amazon has been on the cutting edge of collecting, storing, and analyzing a large amount of data–be it customer data, product information, data about retailers, or even information on the general market trends. Since Amazon is one of the largest e-commerce websites, a lot of analysts and firms depend on the data extracted from Amazon to derive actionable insights.

However, Amazon data scraping is not easy! Let us go through a few issues you may face while scraping data from Amazon.

Why is Amazon’s Data Scraping Challenging?

Before you start scraping Amazon’s data, you should know that the website discourages scraping in its policy and page-structure. Because of its vested interest in protecting its data, Amazon has put in place simple anti-scraping measures. This could stop your scraper from collecting all the information you need. In addition, the configuration of the page may or may not vary for different items. Your scraper code and logic could fail. The worst part of it is, you could not even know that this problem will spring up.

You may also run into any network errors and unexplained responses. In addition, captcha problems and IP (Internet Protocol) blocks may be a frequent roadblock. You’re going to feel the need to have a database. The lack of one may be a significant problem! You’ll also need to take note of the exceptions when writing your scraper algorithm. This will be useful if you want to avoid issues due to complicated page layouts, unusual (non-ASCII) characters, and other problems such as funny URLs and huge memory requirements. Let us speak in-depth about a few of these topics. We’re even going to discuss how to fix them. Luckily, this will allow you to scrape Amazon records successfully.

Amazon Will Identify and Block Bots and Their IPs

Because Amazon prevents web scraping on its websites, it can easily detect whether an activity is being carried out by a scraper bot or by a human agent via a browser. Many of these patterns are established by closely monitoring the behavior of the user agent. For example, if a query parameter repeatedly changes your URLs at a regular interval, this is a clear indication of a scraper running through the page. It then uses captchas and IP bans to block these bots. Although this step is important to protect the privacy and dignity of the information, some data will still need to be extracted from the Amazon web page. We have some workarounds to do so, let’s look at some of them:

  • Rotate IPs to different proxy servers if you need to. You can also deploy a consumer-grade VPN service with IP rotation capabilities.
  • Induce occasional time-gaps and delays to break the regularity of the page triggers in your scraper code.
  • Remove the query parameters from the URLs to remove the identifiers that link requests together.
  • Adjust the scraper headers to make it look like requests coming from a server, and not a piece of code.

There Are Several Product Pages on Amazon Which Have Various Page Architectures

If you’ve ever tried to scrape product reviews and data from Amazon, you may have encountered a lot of unknown response errors and exceptions. It is because most of your scrapers are designed and tailored for a particular page structure. It is used to track a specific page structure, extract the same HTML information, and then collect the relevant data. However, if this page structure changes, the scraper can fail if it is not built to handle exceptions.

Many Amazon goods have different pages, and the features of these pages vary from the regular template. This is also done to account for various types of products that may have different key characteristics and features that need to be highlighted. Write the code to correct these contradictions to manage exceptions. Your code should also be robust. You can do this by using ‘try-catch’ phrases to ensure that the code does not fail when a network error or time-out error happens first. When you are scraping any of the basic attributes of a product, you can build code so that the scraper can check for that particular attribute using tools like ‘string matching.’ You can do so after removing the complete HTML structure of the target article.

It May Not Be Effective Enough for Your Scraper!

Have you ever seen a scraper that’s been working for hours to get you a hundred thousand rows? This could be because you haven’t taken care of the algorithm’s efficiency and speed. You can do some basic math when you’re developing an algorithm. Let us see what you can do to solve the problem. You’ll still have the number of goods or vendors you need to collect knowledge from. Using this data, you can approximately calculate the number of requests you need to submit every second to complete your data scraping exercise. When you’ve computed this, your task is to build your scraper to meet this need!

It is highly likely that single-threaded network blocking operations would fail if you try to speed things up! You may want to make multi-threaded scrapers! This helps the CPU to operate in parallel! It will work on one answer or another, even if it takes a few seconds to complete each order. This could give you almost 100x of the speed of your original single-wire scraper! You’re going to need a powerful scraper to crawl via Amazon because there’s a lot of details on the web!

Do You Need Web Infrastructure and Other Computer Supports!

A high-performance computer would be able to speed up the process for you! Then you can stop wasting the wealth of your local system! You would need high-capacity memory resources to be able to scrap a website like Amazon! You will also need high-performance network pipes and cores! A cloud-based platform will be able to provide you with these tools! You don’t want to get into memory problems! If you store large lists or dictionaries in your mind, you could put an extra burden on your machine-resources! We advise you to move your data to permanent storage locations as soon as possible. This will also help you speed up the process.

There are a variety of cloud services that you can use at fair rates. You may use basic steps to make use of one of these services. It will also help to prevent unwanted device crashes and delays in the process.

Using a Report to Record Details

When you scrape data from Amazon or some other online website, you can generate large amounts of data. Because the scraping process consumes power and time, we advise you to keep the data stored in the database. Store a record of any product or seller that you crawl as a row in a database table. You can also use databases to perform operations such as simple querying, exporting, and deducting your data. It makes the process of processing, analyzing, and reusing the data easier and quicker!

Conclusion

Several businesses and analysts, especially in the retail and e-commerce sectors, need to scrape Amazon data. They use this data to compare prices, to research consumer patterns through demographics, to forecast product demand, to analyze customer sentiment, or even to estimate competition levels. This may be a boring workout. If you make your scraper, it may be a time-consuming, challenging process.

However, Loginworks will scrap e-commerce product details for you from a wide variety of web sources and provide this data in readable file formats such as ‘CSV’ or other database locations as per client needs. You can then use this data for all of your subsequent analyzes. This will help you save time and money. We advise you to carry out detailed research on the various data scraping services on the market. You can then select the service that best suits your needs.

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