How Amazon Used Big Data to Rule E-Commerce

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Amazon is an e-commerce giant in today’s consumer landscape, and its success didn’t come by accident. The brand frequently taps into big data to make decisions, stimulate purchases and please customers. Here are some reasons Amazon and big data plans often arise in discussions about why companies thrive. 

It Implements Dynamic Pricing to Stay Competitive

Before retailers used big data for price changes so often, people generally saw the same prices for stuff from day to day, no matter how many times they visited a website. Now, prices change frequently. One of the reasons is because big data platforms assess a person’s willingness to buy. 

An example of this outside Amazon relates to prices for plane tickets and hotel rooms. If people check fares and rates for the same destinations several times, they might notice the prices progressively get higher — or at least change. This tactic is called dynamic pricing, and Amazon uses it aggressively. 

The company changes product prices about 2.5 million times daily, meaning the cost of an average product shifts every 10 minutes. Thanks to the company’s massive amounts of data, it can analyze things ranging from competitor pricing to available inventory, then make informed choices about how much items should cost. 

It Screens Purchases and Return Requests for Signs of Fraud

Amazon’s top-notch status in the e-commerce world makes it a frequent target for retail fraud. The company collects more than 2,000 historical and real-time data points on every order and uses machine learning algorithms to find transactions with an elevated likelihood of being fraudulent. This system stops millions of dollars worth of fraudulent transactions each year. 

Due to Amazon’s proactive approach, and big data algorithms tweaked to meet precise needs, the company can also scrutinize suspicious return requests. For example, if big data shows a person has returned an unusually high percentage of things over the past few months, the company might investigate further. In 2018, some long-time customers reported getting banned for making what Amazon deemed too many returns. 

It Encourages People to Buy More With Each Order

Amazon’s product recommendations are probably the big data applications most familiar to everyday users. It works by presenting users with related items based on things already in their carts or products they’ve purchased before. 

Then, with the release of Amazon Personalize, the company provided developers with an easy-to-use and highly scalable platform that gives recommendations to users across nearly any domain. Other companies could tap into Amazon’s technology for their customers, showing them merchandise options ranging from clothing, food and more. 

When Amazon can successfully appeal to customers with personalized picks and make them want to spend more, company profits rise and people get the perception that Amazon is a place where they can buy virtually anything they might need.

It Uses Data to Change Physical Stores

When Amazon acquired Whole Foods Market, it immediately started using data to change that brand’s operations, including by lowering prices on popular items. That was the first step in a substantially broader effort to harness big data analytics. Succeeding in that aim could help Amazon shake up the supermarket industry and decide how to improve it. 

Amazon Go, the brand’s cashierless convenience store brand, also heavily relies on data to function. Sensors detect which items people pick up to buy, and cameras ensure shoppers don’t succeed with shoplifting attempts. Although the company has not gone into detail about the data it collects about Amazon Go shoppers and why, it’s likely the firm would use the data to make its stores better. 

For example, if cameras showed people with baby strollers had trouble navigating the aisles, Amazon might make them wider. Alternatively, if sales data indicated vegan-friendly items sell especially rapidly in a specific region, it might order more of those products to match customer needs. 

It Depends on Information to Run Fulfillment Centers

Amazon calls its warehouses “fulfillment centers.” It’s not surprising that the company uses big data there, too. One of the more controversial uses relates to crunching productivity statistics and automatically sending workers warnings about being too slow. But, Amazon also uses data to track which items people buy most often and whether the stock is running low. 

The brand has a patent for what it calls “anticipatory shipping,” too. That approach would predict what people want to buy before they place their orders. 

Amazon and Big Data: A Smart Pairing

Amazon almost certainly could not have made the progress it has without big data. People should expect the company to continue doing the same moving forward. 

About the Author

Caleb Danziger writes about big data, AI, cloud computing and the IoT. Read more from Caleb on The Byte Beat, his tech blog.

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