Scrape Amazon Reviews: eCommerce Insights And Smart Data Collection
When it comes to analytics to grow your business or power your start-up, do you ever wish that you could scour the web quickly for relevant data and save it all in one place for convenient usage.
If so, then what you wish for has a name. It’s called web scraping. And for business-related applications, its purposes are endless. The amount of time that it would take an employee, or even a team, to complete the same processes is, by comparison, inefficient.
Today, we’re going to take a look at how you can use web scraping. Specifically, how to scrape Amazon reviews and to collect and apply all of that Amazon review data where you need it the most.
Whether that’s analyzing purchasing habits or customer preferences, Amazon review data can be a guidepost for your sales processes and web scraping can help illuminate it all.
What is Web Scraping?
Web scraping is like a copy-and-paste mechanism but is applied far more efficiently to much larger chunks of information. If you need to scour whole websites and glean from all of the information key pieces of insights, then you need a web-scraping tool.
This method utilizes intelligence automation tools written with specific codes to obtain large amounts of, usually, unstructured data in HTML format. Afterward, that data is standardized and organized to make it easier to see connections, patterns, and relationships.
Because web scrapers are written with specific codes, they can be created uniquely and modified for particular jobs. Generally, the web scraper will be provided with the URLs of the sites to be scraped.
Once the web scraper tool acquires and then loads the different HTML codes for each site, it saves and then outputs them in a readable format specified by the user, such as an EXCEL spreadsheet. At this point, the user can note all kinds of useful data and apply it.
All of this data is useful in a variety of ways. Companies can use web scrapers to monitor competitor pricing, produce real-time analytics and predictions, fetch product descriptions and images, and monitor consumers’ experiences and feedback about those experiences.
Scraping Amazon Reviews
For companies and enterprises that want to do just that, to monitor customers’ experiences and feedback, Amazon reviews are a perfect application for web scraping. Scraping Amazon reviews can provide you with large quantities of data that your company can use in a wide variety of ways.
If you’ve ever read Amazon reviews before, for personal or professional reasons, then you know what a treasure trove of information they are. They contain data about customers’ purchasing habits and preferences, product information and pricing, feedback about the purchasing experience, and other sentiment-related information.
You can use this data to analyze possible opportunities and demand for new products, monitor brand reputation, and evaluate overall trends in shipping or pricing to keep up with market expectations.
Overall, especially for e-commerce businesses, the process of scraping Amazon reviews can be easy, efficient, and rewarding. If your company or start-up wants to dive into the world of web scraping in the data-rich realm of Amazon reviews, the best place to start is with a proxy.
What Are Proxies and How Do They Help with Web Scraping?
To scrape Amazon product reviews, a key part of the process is anonymity. When accessing a website normally, that website is privy to all your saved information based on your internet connection. This data can tell the website all kinds of details about you and your connection.
However, utilizing a proxy means that your connection is fully disguised and your identity is secure. A proxy hides your IP address from the website you are accessing, giving you total access and security.
Proxies are especially important in the web scraping process because websites will often ban any detected automated behavior associated with bots or hacking. Although perfectly legal, websites can often shut down web scraping because of this confusion.
Proxies can help navigate around this miscommunication through the use of multiple IP addresses, allowing you to still collect as much information as you need reliably and efficiently.
Generally, there are two types of proxies to choose between in your web scraping venture.
Datacenter proxies are the most common proxy type and are useful for applications beyond web scraping, like geolocation switching and cybersecurity. These proxies operate out of large data centers around the globe through which IP addresses get rerouted.
To utilize this method, you will purchase data center proxies in bulk from a secondary source. With the purchase will be many different IP addresses, with a different one associated with each proxy. This way, you can bounce around to different IP addresses through different data centers, using an IP address from across the world to scrape Amazon reviews from the comfort of your own town.
Datacenter proxies are a good choice for a wide variety of usages, including the prevention of data hacking. Many companies choose to utilize data center proxies since you can buy them in bulk. We offer different subscriptions with offerings to fit many different types of needs.
Check out our elite, private proxy packages to utilize the data center proxy power you need in an efficient and cost-effective way.
Residential proxies establish a similar IP address-masking effect by using a different method. This way utilizes a secure but consistent IP address to disguise your own. When you connect to the internet, your purchase of a residential proxy will give your IP address an air-tight cover identity of sorts.
In this way, a residential proxy is more under-the-radar and stable than a data center proxy, as it appears in patterns more indicative of regular human behavior. Because of this, residential proxies are the best proxy choice for web scraping.
Good, ethical residential proxies can be hard to come by. However, we’re working on beta tests to help us cover this proxy-provider gap. See if you qualify to participate in our ethical and customer-focused residential proxy test. It’s a great way to get rock-bottom proxy pricing and contribute to our endeavor to create a trustworthy and reliable service.
Utilizing Amazon Review Data
After selecting a proxy, the next step is to determine what tool or coding language is best for your web scraping needs and goals.
Especially when web scraping Amazon review data, you’ll want to choose a tool engineered to scrape Amazon reviews for products, data, and sentiments to fuel your most valuable analytics.
How to Scrape Amazon Reviews with Python
One of the most popular languages for coding web scraping tools is Python. Highly programmable with simple syntax rules, the programmer can focus on core applications by using small code phrases, even for large tasks.
Many coders find it easy to scrape Amazon reviews with Python because it handles the whole process and extracts data smoothly and easily. Python supports many well-known coding frameworks and is known for its advanced web scraping support features and libraries.
When building up a code for web scraping, it’s important to remember all the most essential components, from start to finish. Python is popular because it allows for many choices and variations for all steps of the process that can be easily suited to many different applications and users.
However, one of the main complaints with Python is the over-abundance of options, specifically for the data visualization portion of the analysis process.
For companies and users who are trained well to handle these options and have many applications that could benefit from multiple types of visualizations, Python would be a great web scraping coding language to utilize.
How to Scrape Amazon Reviews Using R
While Python is notably popular, many coders will claim that it still falls short of the coding language R. For data mining and web scraping, R offers a simple and easy base package that doesn’t require much extra coding to get the job done.
R is undoubtedly the best language specific to web scraping because of its focus on statistical analysis and the functional delivery of data. While Python can be utilized for some of these more focused tasks, the built-in core packages make it process much quicker and easier to scrape Amazon reviews using R, saving time and effort, which is what web scraping really is all about.
While both are open source programming languages, meaning that they are free to use, R has the wider array of packages and options for delivery of data from messy, unsupported formats to a readable and organized destination.
However, compared to R, Python uses less memory and is the less complicated base language to scrape Amazon review data.
Which Language is Best?
At the end of the day, R will be best for those needing a data-specific language that can handle many different specialized kinds of functions in regards to web scraping Amazon reviews.
For those who are looking for a more beginner-friendly language and don’t need as many specializations, Python is a better way to scrape Amazon reviews in general as a beginner.
Before you begin to scrape Amazon product reviews, make sure to select a residential proxy that can protect your anonymity and pick a coding language that will tailor the process to your goals.
Scraping Amazon reviews is a smart and efficient way to bolster your data analytics to drive better marketing, product expansion, and intentional branding. Make sure not to let this great, time-saving tool pass you by!
Get a free trial today and see the Blazing SEO
difference for yourself risk-free!