Commerce has always been driven by technological innovation. After all, it was the invention of the steam engine that kicked off the Industrial Revolution and established the foundation of today’s business world.
And there have been many other commerce-disrupting inventions introduced since the 19th century. Computers and the internet have brought the world together, and they’ve also significantly increased the amount of information that each consumer produces.
In fact, the new methods that are now available for collecting and analyzing this consumer data may be the most important business technology development of the 21st century. This field is known as big data, and it involves techniques such as data mining, machine learning and natural language processing.
According to McKinsey & Company, retailers that utilize big data can increase their operating margins by as much as 60%.
The ecommerce industry is in a uniquely advantaged position to benefit from big data.
While brick-and-mortar stores can use surveillance cameras and IoT devices to track in-store metrics such as the number of people waiting in checkout lines at different times of the day, it’s much easier for ecommerce merchants to capture information about their customers. All of their interactions with customers (and potential customers) take place online, and just about everything online is trackable.
In this guide, we’ll show you exactly how big data is transforming ecommerce, as well as how your store can benefit from this revolutionary new technology.
It’s almost easier to review the areas of ecommerce that haven’t been affected by big data than the ones that have — online businesses have found that they can improve everything from product design to advertising to customer service with the use of big data.
That said, the following areas stand out as being especially affected by this field:
Not all sales are equal. It’s always good to convert a visitor into a customer, but there’s no telling how long they’ll stick around — they might become a loyal customer and continue to make purchases from you again and again, but they might also be swayed by one of your competitors to start using their service soon after they make their first purchase from you.
For this reason, it’s important to make an effort to increase your average order value. That way, you can get as much revenue as you can from your customers while they’re still your customers.
One of the most effective techniques for convincing customers to add more items to their cart is product recommendations. By showing customers products that are related to the one they’re currently viewing on a product page (or the one they’re about to buy on a checkout page), you can often convince them to buy products that they wouldn’t have otherwise.
The more accurate your product recommendations are, the more sales they’ll generate. Big data tools are able to analyze the historical buying behavior of your customers in order to increase the accuracy of your recommendations.
If you’d like to see proof of this point in real life, you just need to look to the most successful ecommerce company in the United States: Amazon.
The ecommerce giant is famous for its highly accurate “Frequently bought together” section, and these product recommendations generate 35% of Amazon’s revenue (which, in 2019, totaled $280.52 billion).
With brick-and-mortar commerce, it takes a lot of effort for customers to comparison shop. They must take the time to drive around to different stores, and then they need to physically locate items within each store as well. So, in many cases you can get away with your prices being a little higher than the prices of your competitors.
Of course, that’s not the case with ecommerce. Customers can compare the prices on multiple stores with just a few clicks. If your prices are significantly higher than what your competitors are offering, people are going to notice, and you’re going to miss out on many sales.
But it can take a lot of research to discover where your competitors are setting their prices. Considering that there are over 7 million online stores in the world, there are likely dozens if not hundreds of ecommerce sites selling the same types of items you sell to the same pool of potential customers you’re targeting. How are you going to keep track of all that?
That’s where big data comes in.
Through big data, you can process the other prices out there and use that to help you set your own prices. You’ll know how to set them high enough for you to make a good profit, but also low enough to stop customers from seeking out more affordable competitors.
If you can find a way to anticipate what customers will want in the future, you’ll gain a huge advantage over your competitors. That will allow you to stock up on tomorrow’s hottest products before anyone else, putting you in a prime position to jumpstart your sales.
Thankfully, there are big data tools that comb through social media activity and web browsing habits to help you stay one step ahead of these trends.
For example, Google Trends is a free tool you can use to analyze the popularity of different search queries. And then there are paid services like Glimpse, which also tracks social media and online shopping behavior to provide you with insights on trending topics.
One of the more futuristic developments that big data has enabled for ecommerce is visual search. But how can it be, with the all but limitless combinations of colors and shapes that are possible in images, that computers are now able to see?
Recent advances in machine learning technology have made this possible. Computers can literally be taught how to understand the context of images and cross-reference an image that a customer uploads with relevant information.
It can be especially difficult to find the right product for DIY projects, as there are often many different variations of the same item when only the exact right one will work. That’s why Home Depot developed a visual search feature for its mobile app, which allows customers to locate an item by simply snapping a picture of it on their phone.
In addition to helping you make sales and improve customer experience, big data can help you save money as well. This is because, without big data, the development of chatbots would not have been possible.
Chatbots are automated digital assistants that are able to handle a variety of interactions with visitors on your site, such as answering questions about products, scheduling appointments and even guiding customers through purchase decisions.
24/7 support will make your customers feel more valued, and chatbots are more affordable than human customer service reps.
Ultimately, big data is reshaping ecommerce by making the unknown known. What do customers want? Where exactly should you set your prices? How can you provide the people who visit your store with the best experience possible?
With the help of data and the tools that are now available to process it, the answers to these questions have become much clearer.
Adam Ritchie is a writer based in Silver Spring, Maryland. He writes about ecommerce trends and best practices for Shogun. His previous clients include Groupon, Clutch and New Theory.