It is becoming increasingly convenient for people to find and purchase the things they need online. The same has happened to sellers who are now setting up stores and doing business online at Walmart, Flipkart, eBay, Alibaba, etc. However, to get a user's attention and turn them into a customer, e-commerce sellers need to use data analytics to optimize their offerings.
Many shoppers now start their searches with Amazon rather than search engines like Google or Bing. As of 2022, Amazon is the largest e-commerce company in the U.S., accounting for 38% of e-commerce retail sales. Which makes the platform a great source of data that can allow companies to make informed business decisions and better understand customers.
Amazon is the place where you can find all the relevant, valuable information about products, sellers, reviews, ratings, special offers, news, etc. Collecting data from the platform benefits everyone: sellers, buyers, and suppliers.
Instead of scraping through hundreds of different sites, collecting data from Amazon can help solve the costly process of extracting e-commerce information. And here's exactly what kind of data you can get:
Boost the growth and productivity of your retail or manufacturing business with e-commerce data
Collecting data available to all individuals from Amazon's site is legal. However, the platform is concerned about data security. The content that Amazon has made private and prohibited all search robots from scraping is illegal and could be subject to legal action, and Amazon could sue a person or search robot who tries to scrape that data.
Amazon adheres to the following ground rules to make scraping its data quite difficult:
So you should first make sure that your scraping will comply with Amazon's policy on automatic data collection.
Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce. And here are the main benefits you can get if you incorporate automatic data scraping techniques into your work:
Web scraping enables retrieving relevant competitor price data from Amazon pages on an ongoing basis. If you don't track price changes in the marketplace, especially during peak seasons, you can suffer huge losses in online sales volumes and competitive disadvantage. Price analysis can help you monitor pricing trends, analyze competitors, set promotions, and determine the best pricing strategy to stay on the market. A well-planned pricing strategy will increase profits and attract more leads.
Every dealer has a specific customer base that buys a certain product. By understanding what your target group is, you can make reasonable choices for selling in-demand products. Researching customer sentiment and preferences on Amazon can help clarify your customer base, learn their buying habits, and plan different sets of products for customers accordingly, increasing sales.
Entrepreneurs must keep track of how their products sell in the marketplace. For sellers on Amazon, the best way to achieve high sales is to put products at the top of relevant searches. To make the product fit the description, you need to develop and add to the product profile. Here you can pull product information such as price, descriptions, ratings, ranks, reviews to analyze sentiment and do competitive analysis. In this way, companies can get a better understanding of their product positioning, market trends and correctly tailor product profiles to relevant searches to bring their goods to the top and get more customers.
To determine the most profitable niche, it is necessary to study market data in detail. This will allow you to analyze how your products fit into the existing market, track interest in the product on Amazon, and identify which products are in the highest demand. Scraping the platform will provide you with the data that after detailed examination can improve your supply chain to optimize your internal assortment, properly manage inventory and make better use of your production resources.
Boost the growth and productivity of your retail or manufacturing business with e-commerce data
After considering all the benefits of Amazon scraping, a reasonable question arises: How do you collect this data? There are several methods of web scraping, such as using APIs. But when it comes to collecting large volumes of data, the best solution is to use web scraping services.
However, there are a few problems you can run into when scraping data from Amazon on your own, regardless of the method you choose. The worst thing about self-scraping is that you may not even anticipate the problems and may even encounter network errors and unknown responses.
Here are examples of the most common problems you may encounter when scraping Amazon content on your own.
Amazon can easily determine whether information is being collected by a bot scraper or manually through the browser. This is detected through tracking the browser agent's behavior.
For example, when a site detects scrapers or when a user makes 400 or more requests for comparable pages at one time, certain actions are taken against whoever is collecting the data. Therefore, captchas and IP bans are used to block bots. If one IP address keeps requesting pages without a Captcha confirmation, it will be banned from Amazon or the address will be blacklisted.
To overcome such obstacles, we use different solutions and strive to make the behavior of our crawlers more human:
When collecting product description data from Amazon on your own, you may have encountered a lot of response errors and exceptions. The whole reason is that most scrapers are set up for a specific page structure, extracting HTML information from it and collecting relevant data. But if the page structure changes, the scraper can fail because it is not designed to handle exceptions.
Amazon's website uses multiple templates to update product information and pages have multiple layouts, properties and HTML elements. This is mainly to emphasize key attributes and features of a certain type of product. The category or product group of newly added ASINs also affects the template used in the product installation process on Amazon.
Therefore, to eliminate all inconsistencies, we write the code in a way that it can handle these exceptions. By doing so, we ensure that the code does not fail at the first network error or timeout error.
One product can have different variations, allowing customers to easily explore and choose what they need. For example, sweaters come in different sizes or lipstick comes in different shades.
Product variants are identical to the patterns we've outlined above and are also presented on the site in different ways. And instead of being rated on one version of a product, ratings and reviews are often rolled up and accounted for by all available varieties.
There is also a difference in product listings, search results and product detail pages when exploring an Amazon version from another region. For example, if you visit Amazon from Italy, the site only shows items that are shipped to Italy. And if the U.S. zip code is specified as the shipping destination, only details such as price and availability are displayed.
When we collect feedback data on Amazon for customers, we show the total number of reviews. And to get around the geolocation issue, we use the IP addresses of the countries from which we collect data on the Amazon platform.
It's pretty hard to develop a web scraper on your own that will run for hours and collect several hundred thousand strings. The site's algorithms are basically hard enough to scrape because Amazon is not like other sites. The site is built to minimize the practice of crawling.
Also, Amazon stores a huge amount of data, and if you want to collect content for your company's needs, you have to realize that scraping large amounts of material can be difficult. Especially if you're doing it yourself. It's a time-consuming and regular activity, so building a good effective web scraper on your own will be nearly impossible.
The quick and reliable way is to leave Amazon information gathering to professionals who can not only bypass the hurdles of scraping, but also systematically provide the data you need in the format you want.
Boost the growth and productivity of your retail or manufacturing business with e-commerce data
If you have to choose between different Amazon scraping methods, the clear winner is the data scraping services. Unlike the other methods, web scraping services can handle all of the problems mentioned above. If you hire the right scraping services, it will collect content for you and provide you with quality data on a regular basis. Scraping services employ professionals who are well aware of all the legal restrictions and will not have problems with blocking.
And it would be more efficient and effective for your company if you put your resources into your business and give Amazon data collection to a third-party firm that you just make a deal with and they do the data scraping for you according to the timeline you set.
Amazon is the world's largest online retailer, where shoppers begin their search for the products they want and are increasingly confident in purchasing the items they need. E-commerce sellers must use data analytics to optimize their products to turn the average online consumer into a loyal customer.
That’s where Amazon scraping can provide a wealth of information in one place that you can easily accelerate your e-commerce data scraping process and use to make key business decisions. Also, to avoid running into problems when scraping Amazon pages because of too frequent queries or too predictable behavior, get help from scraping professionals.
Let us take your work with data to the next level and outrank your competitors.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
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