How does Amazon use big data? (how to use, data analysis, storage, etc.)
Amazon is one of the leading e-commerce sites, and as such, they collect a lot of data on a regular basis. To manage this data, Amazon uses big data analysis techniques.
However, customers may be curious about how Amazon uses big data and how it works. If you want to know more about it, keep reading this article for my findings!
How does Amazon use big data?
Amazon uses big data to analyze their customer base, which means they keep records of what customers search for and buy. By recording this customer data, Amazon can better identify and recommend other products that customers may be interested in buying, which in turn increases Amazon’s sales by convincing consumers to buy.
If you want to learn more about how Amazon Big Data Analytics works, the ways Amazon uses Big Data, and other helpful tips and information, keep reading this article!
How does Amazon’s big data analytics work?
When Amazon uses big data analytics, they collect personal data about each customer’s use of the site, such as what they look for, what they buy, what items they view, reviews they leave, and their location.
By using big data analytics, Amazon is able to better satisfy each user’s website experience, which leads to increased sales due to the positive outcome of customers’ shopping.
For example, by gathering information about customer locations, they are able to better choose which warehouse to ship orders from, reducing transit times and resulting in a more positive customer experience.
In what ways does Amazon use big data?
Amazon is able to collect user data in a number of different ways as they regularly collect and store customer information while using their website and website add-ons.
Listed below are some of the ways Amazon is able to collect this data:
1. Alexa recording
Amazon Alexa is a voice-command device that customers can use to gather information about the weather, news and other basic facts.
Customers simply ask Alexa questions with their voices, and the device will provide the answers.
However, when customers issue voice commands to Alexa, those commands are actually recorded and uploaded to Amazon’s servers.
By recording voice commands, Alexa is better able to recognize and recognize speech patterns, which helps provide more accurate responses.
While recording customers’ voices helps Amazon collect data, some customers say the practice violates their privacy.
Fortunately, though, Amazon does give customers the option to delete each voice message with the Alexa-enabled assistant.
2. Personalized recommendation system
Amazon has a Collaborative Filtering Engine (CFE) built into their website that records behavioral analytics when customers use the site.
This filtering system analyzes behavior such as buying patterns based on previously purchased items, items in customers’ shopping carts and wish lists, product reviews and ratings, and most searched products.
Once this data is collected, Amazon uses it to recommend products that customers are most interested in. For example, a customer searching for classic fiction might have other classic books in their recommendations.
This big data harnesses the power of recommendations to customers to encourage last-minute purchases. The use of this suggestion has proven effective as 35% of Amazon’s sales come from using this method.
3. One-click order
Due to the high competition for online ordering, customers often look for alternatives from other sites if they expect longer shipping periods for their purchases.
So Amazon added a “one-click order” option that allows customers to add items to their order without clarifying their shipping and payment information.
When using the one-click method, the customer has 30 minutes to remove the product, after which time the customer’s account is automatically charged and the order is placed.
This one-click approach keeps many customers coming back to Amazon on a regular basis because it allows them to have their orders ready for shipping in no time. In contrast, the same product may take longer to arrive from a competitor.
4. Expected shipment patterns
Amazon’s Expected Shipment Model is an additional method used to measure the type of product a customer ordered based on when the order was received by the customer and where it was shipped from.
The model helps Amazon better predict shipping and delivery times for customers based on orders from the warehouse closest to where the customer lives.
By putting more accurate timestamps on orders, Amazon increases the chances of customers returning because they are able to rely on Amazon’s shipping forecasts more than other e-commerce sites.
5. Kindle e-book recommendation
Another method Amazon uses to measure customer data is the Kindle e-reader. Amazon has linked Goodreads to its Kindle functionality, allowing customers to highlight Kindle pages and share them with others.
This social networking feature allows Amazon to regularly monitor the words customers highlight so they can better cater to customers’ book recommendations.
This method of creating recommendations has proven effective, resulting in increased book sales through the Amazon Kindle.
Which big data platform does Amazon use?
Amazon has its own branded big data platform called Amazon Web Services (AWS) for recording customer data.
Amazon used to use Oracle to collect big data, but they now operate entirely with their own data analysis service.
How Much Big Data Does Amazon Collect?
Due to the huge amount of website traffic and users, Amazon collects a lot of big data.
Currently, Amazon collects more than 2,000 historical and real-time data sets for each order.
Additionally, Amazon also uses machine learning algorithms to prevent any fraudulent transactions from entering their data collection.
The vast amount of data Amazon collects includes customer purchases, search histories, and other customer activity involved in using Amazon’s website.
Does Amazon collect data on all customers?
Amazon’s systems automatically collect data on all activity that takes place on its website. As a result, all customers who shop on Amazon will have data on any purchases, searches, reviews or other traces they leave behind.
While Amazon uses the data to narrow recommendations to its customers, some may have privacy concerns about their personal information being logged.
However, customers can rest assured that while Amazon records their data, they do not share any personal information outside the company and use it purely for research purposes!
Customers concerned about their personal information being recorded can use tools such as the Alexa-enabled assistant, which can delete recordings of their voice and other personal data.
To learn more about Amazon, you can also check out our related posts on Amazon Book Sales Statistics, If Amazon Made Anything, and Why Amazon Search Is So Bad.
in conclusion
Amazon uses big data to better recommend products to customers.
Amazon records purchase history, search engine history, personal contact information, data from Amazon wishlists, and items customers save to their shopping carts.
Amazon uses tools such as Amazon Alexa voice commands, a personalized recommendation system, one-click ordering, expected shipping patterns, and Kindle recommendations to record big data and improve the overall customer experience.
