Amazon is one of the largest online marketplaces, with 310M customers worldwide and 2.5B monthly visits. With numbers as great as that, it takes almost 40% of the US online market, and is a valuable source of information about buyers and sellers.
The huge volume of customer and business data the platform contains is a meat and drink for those engaged in market research, business development and product promotion.
But to gather this market information manually is barely impossible, and this is where scraping automation tools come to the forefront.
What is Amazon Scraping?
Web scraping is a set of tools and techniques designed to automate extraction of diverse data from online platform and websites. Therefore, Amazon scraping is retrieval of Amazon’s publicly available data based on automated tools, scripts or apps.
The bottleneck of Amazon web scraping is that the platform itself forbids unauthorized collection of its information, so the entire process should be developed taking into account the Amazon’s rules and privacy policy, legal and ethical considerations and modern IT tools.
Why Scrape Amazon Data?
With over 310 million users and almost 2 million of active sellers, Amazon is one of the largest online marketplaces worldwide. It houses an abundance of e-commerce market data that, when handled properly, can become a solid foundation for data-driven decision and business insights.
So, for retailers that would like to have deeper understanding of market trends, competitor pricing, customer reviews Amazon data serve as a valuable source of information that enriches their knowledge in the domain they are interested in. But collecting such tonnes of data manually sounds like a tiresome, slow and hardly rewarding task. And that’s where web scraping automation techniques come to the forefront.
Amazon Scraping Tools and APIs
Amazon scraping is a worthwhile endeavor, but you certainly need a set of IT tools to run it smoothly.
The Amazon Marketplace doesn’t encourage any data retrieval in violation of its rules and privacy policy and implements modern techniques fighting wrongdoers. These include:
- Dynamic page structure that makes it difficult to analyze and segment webpages with traditional tools. Frequent layout changes also impede use of the already restieved webpage structure and makes you start it all over again.
- Captchas are used to discover and ban automated data extraction tools. It takes additional efforts to bypass this kind of verification, and you should keep in mind that different types of CAPTCHAs requires different bypass methods.
- Rate limits employed by Amazon restrict a number of requests you can submit during the time interval without provoking any suspicions.
Another portion of difficulties is usually related with legal risks a scraper can face, if breaking the rules. Besides, if the project is of a high scale, retrieval of millions of records is a resource-consuming task. To cope with this project, users need reliable and scalable IT infrastructure.
The last, but not the least, is the quality of retrieved data. Keep in mind that in many cases you might need extensive data cleanup to make them reusable for your business goals.
New scraping techniques appear every day. But generally, so far, we can single out three classes of tools widely used for data retrieval tasks:
- Python and Python libraries, with all possible code variations. To develop your own web scraper, you need at least basic Python knowledge. Then of course, you should have Python installed. To make your life easier and not to create your solution from scratch, you are free to use popular Python libraries, such as requests, Selenium, or beautifulSoup. They simplify interaction with APIs, data processing, cleanup, proxy rotation and other subtasks that make a part of a successful web scraping project.
- APIs. Application programming interfaces act as a bridge between two or multiple endpoints of servers or software. APIs of complex websites, such as Amazon Marketplace, enable interaction with the server that accepts user requests and sends them back the requested information.
So, Amazon web scraping APIs are designed to exchange data with Amazon servers: users submit requests to the API endpoint, and the API, in its turn, accesses the online platform, bypasses anti-bot measures and retrieves the requested information.
Today, the IT market offers many ready-to-use API scraping solutions. Such developers as NetNut, Nimbleway, Bright Data, Decodo and others offer APIs with dedicated Amazon endpoints and success rate over 99%.
- Anti-Detect browsers are another class of tools that you can you for web scraping. These are web browsers specifically designed to hide your identity and extend your data access and retrieval capabilities. Apparently, these tools will be most demanded by users with zero or low programming skills. It’s just enough to choose and install an anti-detect browser, create your profile there and follow the developer’s instructions on how to make the most of the app.
Features of Amazon Scraping APIs
When choosing Amazon scraping APIs, there are standard features any decent tool supports. So keep in mind the following considerations:
- an API-based scraper should guarantee the success rate of at least 99%;
- number of locations it offers, with a capability to drill down to the ZIP code level (the higher, the better);
- if a scraper supports dedicated Amazon endpoints and data parsing;
- what the average response time is — the faster, the better;
- if a trial period is offered.
Generally, when comparing dedicated API-based scrapers with other data retrieval solutions, their benefits are that they are reliable, efficient, and easy-to-use:
- Higher reliability. Usually, web-scraping APIs are more reliable than custom-build tools, as they feature better compatibility with the target platform and can cope with a range of data scraping tasks.
- Higher flexibility. Advanced scraping APIs support proxy rotation, customer headers, geolocation customization and other parameters that open wider capabilities for users.
- Higher scalability. Such scraping APIs are usually hosted on a scalable infrastructure and are designed to bypass many protection measures. This way, they are a good match for large-scale data extraction projects.
- Higher legality. When you get an API-based permission to use the data from the target platform, and, moreover, if you use an official API of the website you need data from, you reduce possible legal issues as much as possible.
- Higher ease of use. With API-based tools, all you need to do is to make an API call. No difficult programming tasks or complex code. Besides, you get high-quality data in XML or JSON format.
Still, every cloud has its silver linen. Among disadvantages we should remember is dependence on the API provider, API rate limits and API key restrictions. After all, the scraper API doesn’t belong to you, and therefore you don’t create your own rules, but just have to follow someone else’s. That’s why you’ll have to reckon with API limitations, whether these are geolocation restrictions, a cap of number of API requests, or unavailability of certain types of data.
Legal Considerations for Amazon Scraping
Legal view of scraping remains controversial.
In principle, no one can prohibit you to access publicly available data. Still, it’s generally recognized that it’s legal to review such information and collect it manually, as most online platforms, Amazon included, don’t allow to use third-party automated data retrieval tools to gather data they host. Violation of these requirements can result in account suspension, bans and legal sues, so risks are high.
However, Amazon provides its own official APIs, such as Amazon API Gateway, Amazon Selling Partner API or Product Advertising API that facilitate data access. This is probably the most ethical and legal approach to Amazon scraping.
Pricing Models for Amazon Scraping Services
Today’s market has adopted three main pricing models for Amazon scraping services:
- Subscription. This is probably the most popular pricing model across IT services. With scraping, the demarcation line between pricing plans is the quantity of submitted API requests. Another option is tariffs differentiating depending on the number of thousands of successful results.
- API credits. Some subscription plans make a stake on API credits. For example, Scraper API offers pricing plans varying from 100L up to 3M API credits per month.
- Pay-as-you-go. Some providers offer flexible pricing calculated on the volume of data received. For example, Bright Data offers prices starting from $5/GB.
Free Trials and Pricing Plans
Most Amazon web scraping tools are offered with free trials and a variety of pricing plans.
The most widely spread trial lasts for a week. So, during seven days you will be able to check speed and quality of the service you plan to buy. Sometimes, web scraping providers supplement the trial with a limit of requests you can submit.
As for pricing plans, they are also grouped by the intensity and scale of the project users intend to deploy, varying from micro and starter plans up to corporate and enterprise tariffs. The minimum price usually starts with $50 per month, while the highest prices may come up to $500 and more. The top segment usually covers hundred of thousands and millions of requests, so it is understandably demanded by large-scale projects.
Tutorials and Guides for Amazon Scraping
You can scrape Amazon manually or with dedicated automation tools, with or without API keys, extracting product details, pricing info or user reviews — so it sounds like a vast domain.
Product Search API officially offered by Amazon supports filtering through product ads, organic search results, as well as products supporting one-day shipping, matching certain product categories, or sold by preferred merchants. So it’s a perfect solution for those, who have to monitor their competitors’ activities or collect Amazon product data.
The Internet offers many Amazon scraping APIs to choose from. If you decide to stray from Amazon official APIs, consider such the following factors:
- Reliability, minimal latency and downtime;
- Speed and scalability: assess the provided speed, especially when it goes about large-scale projects;
- Support of integrations, data cleaning and parsing. It’s preferable to choose APIs that return data in a cleaned and parsed format, as well as support integrations with a variety of BI tools.
Popular Amazon Scraping APIs
| API | Description |
| Traject Data Rainforest API | Fits for real-time data retrieval for e-commerce.Good choice for retailers, integrates with BI and reporting tools. |
| Bright Data | Quickly retrieves product and seller details, prices and reviews, and is a good choice for large-scale projects. |
| DataForSEO | Supports customizable API settings for e-commerce data retrieval, and is suitable for companies that need SEO insights based on Amazon data. |
| ScraperAPI | Supports proxy management, anti-bot measures, and scalability options, and is suitable for competitor and trend monitoring for market research. |
If, for some reason, you prefer scraping Amazon manually, start with installing Python and create the project:
After that, install necessary libraries:
- Requests to handle HTTP requests;
- pandas to manipulate and analyze data;
- BeautifulSoup to parse HTML content;
- Playwright to automate web browser tasks.
To succeed with Amazon scraping, you should examine the platform HTML structure in the browser’s developer tools. This will help you better understand attributes and tags of the extracted data.
Next, create a new Python script with the following code and run it:
The deliverables will be saved in Pandas DataFrame and exported to CSV format.
Challenges of Amazon scraping include:
- To retrieve dynamic content. To cope with these tasks, pay attention on whether the tool you’ve chosen supports JavaScript waiting for the dynamic content to load;
- To bypass Amazon anti-bot measures, try to imitate human behavior as reliably as possible. For example, implement delays between requests, rotate IPs and user agents;
- To cope with pagination that splits Amazon search results into pages, identify <Next> selector in the HTML Layout and implement the code that clicks on this button.
Common Use Cases for Amazon Data
Understandably, retrieved Amazon data are most commonly used for retail and e-commerce. We can single out three main goals this information is scraped for:
- price and product optimization;
- market research;
- decision-making
Price and product optimization. By analyzing customer feedback of your own and competitors’ products and by comparing prices, you gain a valuable opportunity to adjust your business strategies. May be, you need to drop prices to remain competitive, or, vice versa, have a headroom to increase them a little bit. Or, maybe, you need to adjust some product features to keep the lights on. Amazon web scraping will help you gather exact information, rather than read the tea leaves.
Market research. Having understanding of what Amazon users prefer to purchase, what products are demanded and what goods fail, companies can build new development roadmaps. Whether they decide to go green, adjust a pricing segment or start an entirely new product line, Amazon scraping allows to rely on trustworthy data.
Data-driven decisions. Data-drive decision make is like riding a brightly lit freeway instead of feeling your way in the dark. Reliable data help run smart, profitable business. By making decisions based on proven information, companies avoid wasting time and cash on dead-end ideas, and can stake on products and promotions with decent chances for success.
Key Takeaways
Amazon is a tasty morsel for all pros dealing with marketing and product promotion, and to have the best of this insightful info, you will most probably need scraping automation tools designed to retrieve data in the field you are interested in. Rely on official APIs and proven third-party tools, follow best practice of data extraction and respect privacy of Amazon users, and you’ll maximize benefits for your business without sacrificing compliance and ethical guidelines.
FAQ
Please read our Documentation if you have questions that are not listed below.
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Is it ethical and legal to scrape Amazon data?
It is usually legal and ethical, if you scrape publicly available data, and very risky if you try to pry into any confidential information. To be on the safe side, examine the laws of your country, as legal requirements can vary from country to country.
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Are there any ready-to-use Amazon scrapers?
Yes, you can choose between official Amazon APIs and third-party solutions.
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Do you need proxies for data extraction with APIs and web scraping?
Proxies are a must for efficient web scraping, but an API provider often takes care of all nuances of data access.
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