It is projected that by 2025, the digital universe will have expanded by 61 percent, having about 175zb (zettabytes) of data. Amazingly, eCommerce comprises a huge chunk of that space. As a result, eCommerce has seen massive growth in revenue and sales. According to this article, worldwide eCommerce sales are expected to exceed $7 trillion by 2025. This potential feat is all thanks to the application of big data in the e-commerce industry.
Apart from providing a ton of information about consumer preferences and behaviour, big data helps eCommerce in various ways. We will discuss some of them in this article. But first, let us define what big data is. After that, we will examine how big data applications in eCommerce can help eCommerce businesses make the right decisions. Read on to learn more!
What is Big Data?
Big data refers to a collection of data sets that are so complex and enormous that it becomes difficult to manage using conventional database management software. However, using specialized tools, big data can be analyzed to provide important information that uncovers trends and patterns, especially those related to human interactions and behavior. The very complex process of acquiring this information is called big data analytics.
What is Big Data Analytics in e-Commerce?
Big data analytics and eCommerce go hand in hand. Top eCommerce companies like Amazon and eBay achieved incredible feats due to the big data analytics they have been utilizing over the years.
Applying big data analytics in eCommerce helps to increase sales by improving customer engagement, offering product recommendations, and personalizing the shopping experience. Thus, by utilizing big data, eCommerce giants ensure that their customers get real-time information and suggestions on products and services tailored to their needs.
How Can Big Data Help in Making the Right Business Decisions?
While gathering consumer information and data is essential, it is not until that data has been examined and analyzed that it becomes useful. After thorough analysis, the information from big data helps eCommerce businesses make the right decisions to maximize their profits while improving customer satisfaction. Here are three ways that it achieves this:
1. It Helps eCommerce Businesses to Offer the Best Prices
A combination of eCommerce and big data analytics helps eCommerce businesses offer their customers the best and fairest prices and thus increase their sales and profits. Consumers who show exceptional loyalty to the company are sometimes offered early access to great deals. Additionally, the price of products may differ depending on where a customer lives or works.
Otto is an example of an eCommerce business using big data to optimize prices. This Germany-based retail giant deals in home furnishings and is one of Europe’s most successful eCommerce companies. By creating a massive database from all its data silos, Otto has become one of the biggest companies that use big data in eCommerce retail to help optimize pricing and personalize market campaigns. Their success in the industry stands as a shining example of the importance of big data for eCommerce retailers.
2. Big Data Helps eCommerce Businesses to Decide on How Best to Improve Shopping Experience
One of the reasons why big data is important for e-commerce is that it can tremendously improve the shopping experience — far more than traditional shopping. Ecommerce companies gather a plethora of data that ranges from click-per-page to how long it takes a customer to make a purchase.
This collection of big data is used in e-commerce to make a predictive analysis which helps eCommerce companies make intelligent decisions, including how to reduce purchase time, prevent the abandonment of purchases and utilize new trends to their advantage. In addition, it helps the organization decide which products are best to display in its inventory by anticipating economic or seasonal changes.
An example of a company that applied this eCommerce big data solution is Lenovo, one of the biggest PC vendors in the world. To improve customer experience and distinguish itself from the competition, Lenovo turned to big data to understand consumer buying behavior, needs, and preferences. Due to that, they drastically improved consumers’ shopping experience and recorded an 11% increase in sales per retail unit.
3. Big Data Helps Ecommerce Businesses Make Smart Decisions to Increase Sales
By implementing big data, e-retailers can tailor their product suggestions to their customers’ needs and decide which coupons best fit a particular customer based on historical data. In addition, by gathering extensive data about their customers, eCommerce businesses can run specific and targeted marketing campaigns and remind potential buyers that they have not checked out their orders. Applying these solutions results in high traffic and, consequently, increased sales.
Domino’s Pizza is an example of an eCommerce business that applies big data this way to boost revenue. Its “AnyWare” program eases the process of ordering pizza. Using it, customers can buy pizza from their smartphones, smartwatches, cars, and TVs. Using a big data eCommerce platform, Domino’s combined information from over eighty-five thousand data sources into one massive database. The data collected is analyzed and processed using big data technology to give the food giant a bird’s eye of its global operations and customer and competition information. This information has helped Domino’s increase sales and stays on top of the competition.
We barely scratched the iceberg of big data’s impact on the eCommerce industry. Big data helps eCommerce in more ways than listed here, and the love affair between the two will likely last for many more years. With many companies analyzing the big data of eCommerce businesses for viability and A/B Tests, there is no reason you should not also try big data for your business.
It is, therefore, safe to conclude that the use of big data in eCommerce is not a fad, and any business that aims to precisely meet customers’ needs, stay on top of the competition, offer optimum prices, and predict future trends should take big data analytics quite seriously.
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