Big Data transforms modern e-commerce industry, there’s no doubt about that. This technological trend has whatever it takes to improve customer experience, logistics, and business performance. In this article, we are going to analyze 10 ways in which big data can be used in e-commerce.

As you probably already know, big data consists of structured and unstructured data. In the e-commerce world, structured data includes entries such as names, products, vendors, orders and addresses, while unstructured data is stored in various formats, and comprises pictures, social media data (tweets, clicks, likes), online reviews, and comments.

Let’s look at how you can use big data in e-commerce to expand your business and serve your clients better.

Secure online transactions

According to Langate’s CEO Paul Kavalenko, a typical US online retailer lost $3.36 to every $1 fraud in 2020. Why? Customers tend to shy away from businesses that have a history of cyber theft. Today, personal and financial data security is of paramount importance. This is why companies should perform extensive data analysis to detect various fraudulent activities. For instance, a series of purchases on the same credit card in a short time or numerous payment methods from one IP address are huge red flags that need to be looked into.

Elevate your clients’ shopping experiences

Big data unlocks new levels of shopping experiences. With an endless supply of data to power predictive analytics, anticipating how your customers are likely to behave in the future should not be out of reach. Thanks to information like the:

  • Average number of products people add to their shopping carts
  • Number of clicks per page
  • Average time users spend in between a homepage visit and a purchase

You can design perfect shopping experiences and provide users with tools and solutions that streamline the purchasing process, making everything much easier.

Predict Trends

Business owners would typically rely on their gut feeling to decide what items they should stock up. But the gut feel is likely to lead you astray since it is not based on real-time data. AI-powered solutions can help you unmask trends in customer purchasing decisions that a human eye would miss. For example, if you sell dresses online, you will need intel on what your clients are likely to order (e.g., most preferred designs) before making an order from your manufacturer.

Offer Better Customer Care Services

Competitive prices and exceptional products mean nothing when a company offers whack customer care services. According to business.com, loyal customers spend about 67% more than new ones, which is why keeping customers satisfied should be a priority for every e-commerce business. Big data technologies can analyze data from social media campaigns, emails, and online self-service tools to reveal problems in product delivery and other customer service drawbacks that might be derailing business progress. It is easier to make a workable change if you already know what works better for your clients.

Predict Demand

Demand forecasting uses big data to understand and predict customer demand tendencies. It gives insights into a business’s potential in the market, making it easier for managers to prepare for the peak or potentially slow seasons. For example, if you are a retail shop owner, demand forecasting will help you estimate the number of customers you’ll have in for the next couple of weeks and what they are likely to purchase to stock up on those items. This way, you are less likely to end up with dead inventory on your shelves.

Increase Personalization

You’re definitely losing revenue if you are not using e-commerce personalization to track your visitors’ preferences. Using big data technology, you can quickly gather valuable user intel such as recently viewed products, items abandoned on carts, past purchases, and recent email interactions. This allows you to send emails with customized discounts and apply different marketing techniques to different target audiences.

Optimize Pricing

Guessing at your pricing is more like throwing darts in a blindfold. You’ll hit something, but it is less likely to be the dartboard. Some eCommerce executives stand guided by their competitors’ pricing (which they probably pulled out of their hats) and wonder why their sales are not going up. Data-backed price management is quite effective. By use of Big data automation tools, you can analyze information such as previous purchases, clickstreams, and cookies and set your prices based on real-time data.

Improve user interface

When it comes to digital presence, it’s hard to visualize anything better than user experience. Initially, UX design services were intuitive and left in the hands of experts’ knowledge. Despite the promising results, it still looked like guesswork. Thanks to big data, user experience is now data-driven. Based on purchases and online actions, you can make your products more usable and comfortable. A good example is how Virgin America revolutionized its ticket sales by creating a new responsive website design. It resulted in 20% fewer support calls and a 10% increase in sales.

To cut down on operational costs.

Big data resources allow businesses to advance in all aspects of business planning, from supply chain to marketing and customer experience. This helps you avoid costly mistakes, reduce employee churn and reduce energy usage. No matter what type of business you run, a big data strategy is instrumental in saving money and finding more profit in your marketplace.

Boost Sales

You need to rely on actual data instead of shooting in the dark to generate more sales. All the points mentioned previously somehow have an impact on sales. Big data analytics is helpful in delivering customized product recommendations and coupons to match customer desires. The aftermath of high traffic as a result of personalized customer experience is more business.

Clearly, Big data has revolutionized every aspect of the e-commerce landscape. It breaks down all the data collected from customers and brings out essential pieces of information that you can use to prepare for seasonal influxes, create personalized experiences for customers, optimize prices, predict trends, secure online payments, and reduce operational costs. When put into proper use, this sea of information can boost your company’s revenue.

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