How Big Data Will Transform Ecommerce

Since 2021, ecommerce purchases have made up over 15% of all retail sales in the United States. This number is bound to keep growing steadily as buying online becomes more practical, accessible and affordable. 

It’s not just that the Covid-19 pandemic forced consumers to start using ecommerce. It’s also that ecommerce experiences have become a lot better. Today’s online stores are redefining what it means to be a retailer and shaping the expectations of tomorrow’s consumers. 

One thing about the massive rise of ecommerce transactions is that it generates a lot of data. We use the term big data to refer to the enormous amount of information bits generated, which only very complex systems can process. 

Today, ecommerce companies are learning to use this data much better, thanks to increasingly complex software, machine learning, and AI. In this article, we’ll explore how the rise of big data technology shapes future ecommerce experiences. 

What Does Big Data Mean for Ecommerce? 

“Data” has been a relevant concept for as long as computers have been around. But more recently, we’ve been hearing a lot more about what's called “big data” —— the type of data that is simply too large or complex for simple software to process. 

Ecommerce owners have to confront the complexity of big data increasingly frequently. As an ecommerce executive, you may have thousands of datasets at your disposal, whether you want it or not. Engaging with big data implies making the most out of it to improve some key processes:

• Customer Experience

• Resource Management
• Product Development
• Service Quality
• Business Decision-Making

The most prominent players in the world of ecommerce (Amazon, eBay, Etsy, Alibaba) are already using big data to devise new types of customer experiences. For example, Amazon uses big data and AI to make algorithmic recommendations of products to purchase, based on a user’s search history, buying patterns, and buying history. 

Meanwhile, Etsy uses big data to make product recommendations based on the aesthetic tastes of each user—using a complex system of image recognition, tags and text analysis. One of the newest trends is that small and medium ecommerce businesses are also catching up, improving their processes with the help of big data. 

Below, we’ve outlined five key ways that big data transforms ecommerce businesses of any size. Here are five distinct applications of big data that benefit ecommerce businesses.

5 Ways Big Data Will Transform Ecommerce

Optimized Logistics

Big data gives ecommerce businesses fantastic opportunities to reshape their logistics based on real-time data. For instance, being able to track what products are selling and how fast allows them to rearrange their supply chain more effectively. 

Predictive analytics allow businesses to get a clear sense not just of what people are buying right now but also of what they’ll be buying in the future. With that in mind, businesses can order more of this product to match the demand. This is nothing new, but big data technologies allow that process to go much faster. In some cases, the process of ordering new products to satisfy increased demand can even be automated. 

Beyond the supply chain, big data can also transform the logistics of processing and delivery. For instance, AI software can use big data to detect errors at any stage of processing and fix them before the product reaches the consumer. Real-time big data increases customer satisfaction and reduces the load of the customer service team. 

Reduced Fraud 

Ecommerce stores are under constant cybersecurity threats, no matter their size. And data is a big part of that. Online businesses have a lot of data on their customers, most notably their credit card numbers. Since the companies are responsible for keeping that data safe, a cyber attack can be absolutely disastrous. 

Luckily, making smart use of their data sets allows companies to detect fraud and cyberattacks as they are happening. For example, algorithms can identify common consumer trends and detect changes that may indicate fraud. They can also flag changes in purchase patterns that can be manually reviewed by cybersecurity specialists. 

With more data, ecommerce companies stand to lose a lot more than money from cyberattacks. But using big data, they can also detect fraud in real-time, making it a significant advantage. 

Personalized Shopping Experiences

Experts are unanimous: the future of ecommerce is personalization. Brick and mortar stores can’t target their offering and promotions to individual customers, but online stores can. Using big data together with AI, ecommerce businesses have the unprecedented opportunity to make each customer experience unique.

Retailers often sell to at least a couple of demographics. For example, a camera shop will sell products to professional photographers, hobbyists who are passionate about film photography, and clueless customers looking for their first camera. With the help of user-generated data, an online camera shop could decide what products show up on their homepage to match the needs and interests of these different customer segments.  

By factoring in data about customers’ buying habits, age, gender, and location, stores can deliver much better shopping experiences. They’ll also get a chance to know their audience better and target products accordingly. 

Improved Recommendations

One of the most noteworthy ecommerce trends is intelligent recommendations. Ecommerce companies such as Amazon use customer data to display products on the homepage that they think customers will love. These intelligent recommendations typically consider many different criteria: age, gender, spending habits, typical spend amount. It’s a very effective strategy that works a little like targeted advertising but with none of the costs. 

Big data-based algorithms also change the game for cross and upselling. As every salesperson knows, there are a few products that customers almost always buy together. For example, when you buy a stapler, you’re likely to buy some staples too. Algorithms can now identify these trends and automatically suggest staples to customers who just added a stapler to their cart. 

Similarly, it makes sense to buy certain products in bulk. So when a customer adds a bag of protein powder to their cart, the store could suggest “supersizing it” and getting two bags for a small discount. These are not new practices, but big data technology allows them to be fully automated, which saves ecommerce stores a lot of time and money. 

Targeted Advertising 

Big data is great at segmenting customers. ecommerce stores have a lot of data on their customers: where they’re from, what they search for, what social group they belong to. All of these metrics can be used to design better ad campaigns—the ultimate goal: creating ads that answer and even anticipate customers’ interest in a given product. 

Not knowing how big of an impact an ad is about to have is a consistent problem for marketers. Big data changes that completely. Marketers use data to target an online ad at a specific customer segment. While the ad campaign is still running, marketers can access a ton of data on who sees the ad, and how they interact with it. This allows companies to adjust ad campaigns in real-time and save a lot of advertising budget. 

The idea of targeted advertising goes even deeper than personalized ads. Using data on customer behavior traits, algorithms can also determine the best frequency and times to display ads. In that sense, big data has the potential to drastically improve conversion rates when it comes to advertising. 

The Rise of Big Data: Should Ecommerce Owners Expect a Pushback? 

The possibilities that big data opens up are incredibly promising for ecommerce business owners. But for many consumers, they’re cause for serious concern. Practices such as dynamic pricing and targeted ads are already under much more scrutiny. Simply put, a lot of internet users are afraid that the data they generate will be used to take advantage of them. 

AI and machine learning technologies are evolving too fast for policy-makers to follow. This means that a lot of ecommerce practices currently exist in a legal gray zone. Take notice, as we’re sure to see a lot more ethical debates related to data use in the coming years. 

As an ecommerce owner, the best thing you can do is to err on the side of caution. Always respect existing data laws, and be completely transparent about the way that you use customer data.

Final Words

With so many benefits, use of big data is on the rise across all industries. Using data in a smart way will help companies get more customers, make more sales and improve their logistics. Most importantly, this data can be used to create vastly improved consumer experiences. 

The rise of ecommerce is nowhere near its peak yet. There may come a time when most retail sales come from ecommerce and where AI rules the sales and marketing world. In the meantime, ecommerce owners should start making the most out of the data they have—it’s one of their most precious assets. 

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