Using Amazon web data scraping service, we can scrape Price, Rank, Ratings, Reviews, Product Claims, Product Description, and bullets, Category breadcrumbs, ASIN, Product Name, Model Number, Manufacturer, Insurance Coverage, and any other data available on the Amazon website.

Python is the best option to build web scrapers to capture large amounts of data and automate the job in set time intervals.

Amazon Web scraping is allowed as long as the data extraction is limited to publicly available data while making sure no Personally identifiable information (PII) information is captured. We built our scrapers specifically to ensure a high level of data security.

SetuServ’s Amazon Web Data Scraping Service uses python to build amazon web data scrapers since it captures large amounts of data and automates the job in set time intervals.

We at SetuServ have been serving fortune 500 clients across the globe with our services as a DaaS provider, i.e., data as a service provider. Our work as a service provider involves scraping data from multiple websites like Amazon across various geographies, allowing them to concentrate on their business goals.

Our scrapers can adjust to changes made to the website and thus provide uninterrupted access to data. Therefore, over the long run, outsourcing such services becomes reliable and cheap.

Available methods are listed below:

1. Scrape data manually using ‘ctrl c+ctrl v,’ but this is tedious and time-consuming
2. Develop your eCommerce scraper. (There are many python frameworks available that can help to develop your scraper. E.g., Scrapy)
3. Many scraping tools are available online (both free & paid) that can help to extract the data
4. Reach out to companies providing professional scraping services and engage them in collecting data as per your requirement

Things to keep in mind when scraping data from Amazon include:

1. Check whether the solution you adopt can operate at scale, i.e., extract a large amount of data
2. There are chances that Amazon might block your IP address. (you can use proxies to mitigate this)
3. The speed of data extraction might be slow
4. There are chances of data loss so, the accuracy of data extracted needs to be validated
5. Amazon might detect your request as an attempt to scrape and send you captchas to evade scraping attempts.

The product URL contains a link to the seller page and high-level statistics on the seller (e.g., seller rating). By scraping the product URL, we can get high-level statistics on the seller. If more detailed information is required, we can scrape the respective seller page.

Note: Amazon is likely to throw captchas to evade scraping requests so, make sure you configure your scraper to handle it.

If updating a scraper that can avoid blocking attempts by the website is difficult, you can seek help from professional data scraping service providers.

At SetuServ, we have managed to build scrapers for many such websites across geographies. As a result, we have minimized data loss and have an unmatched data extraction speed (almost 3x of existing scrapers). Fortune 500 companies are using our scraping services since we provide scale and accuracy at a fraction of the cost by setting up an in-house team.

Scrape this URL https://www.amazon.com/Best-Sellers/zgbs to get data about best sellers. 

Additionally, get URLs of each sub-category for which we want to get best sellers. Then use scrapers that can traverse using pagination to get the product listings in the category. 

We at SetuServ have automated this feature and thus get data faster than conventional scraping techniques.

Amazon data scraping helps in:

1. Identify emerging as well as under-performing products
2. Improve product profile & categorization to enhance ranks and discoverability
3. Track and manage online reputation
4. Detect counterfeit products
5. Benchmark against competitors
6. Competitively price products and discounts
7. Understand product positioning and revise product claims for better product differentiation
8. Identify top performing and emerging products
9. Optimize price and positioning based on the fit in the category
10. Improve category ranking
11. Improving merchant listing pages
12. Update inventory when the stocks are sold out
13. Monitor product reviews on Amazon across geographies
14. Manage online reputation through real-time alerts for negative reviews
15. Understand the leading and lagging areas for each SKU
16. Optimize product descriptions to enhance sales

We at SetuServ have built the capability to analyze the scraped data and present key metrics that affect your brand and consumers’ perception.

SetuServ is an end-to-end data science company that can scale large amounts of data and analyze them to give actionable insights. Visit SetuServ.com to know more.