Six Ways to Use Big Data in Ecommerce

Big Data
In eCommerce, Big Data Analytics (or BDA) is receiving considerable attention as it represents the next level of innovation and competition. Big data presents challenges and opportunities, just as the information revolution has.
We can see that big data will significantly affect e-commerce in the future. E-commerce companies can utilize big data analytics to determine their customers’ purchasing and why. These companies tailor their marketing to meet their customers’ needs and ensure their employees provide the service customers expect.
In this article, we highlight six ways in which big data can be utilized to foster positive change in any e-commerce business.

Six Ways to Use Big Data in Ecommerce Effectively

1.  Improved Shopping Experience
A company that sells products online has an unlimited supply of data that can be used for predictive analytics to predict what a customer will do in the future. With the help of reward and subscription programs, companies can analyze customer demographics, age, style, size, and socioeconomic information. In addition to tracking the number of clicks per page, retail websites also follow how many items customers add to their shopping carts before they check out and the average time it takes between a homepage visit and a purchase.
Businesses can use predictive analytics to develop new strategies to prevent shopping cart abandonment, decrease the time it takes for customers to make purchasing decisions, and cater to various emerging trends. E-commerce companies can also use this data to accurately predict inventory needs based on changes in the economy or seasonality.
2.  Keeping Online Payments Secure
Customers need to feel secure about their payments for a top-notch shopping experience. In the era of big data, it is possible to recognize atypical spending behavior and send a notification to customers as soon as it arises. An organization can set up alerts for various fraudulent activities, especially if a credit card has been used to make several other purchases in a short period of time or multiple payment methods have been used using the same IP address.
In addition, most e-commerce sites today offer a variety of payment options from a centralized platform. E-commerce sites often implement easy checkout experiences in order to reduce the likelihood of shopping cart abandonment. There are a variety of options offered to the customer during the checkout process, including putting an item on a wish list, choosing a “bill me later” option, and paying using multiple different credit cards. A comprehensive data analysis will allow you to determine which payment options work best for each customer, and you can also measure the effectiveness of new payment options such as “bill me later.”
3.  Enhance Personalization
more extensive data set not only facilitates secure, simple payments but can A also improve a customer’s shopping experience. Customers are of the opinion that personalization is an important factor in their purchasing decisions. Millennials are increasingly interested in shopping online, and they expect personalized suggestions.
Using big data analytics, e-commerce companies will be able to build a 360-degree view of their customers. E-commerce companies can now segment their customers based on their gender, location, and presence on social media platforms. Companies will be able to utilize different marketing strategies and launch products that speak directly to the target markets with the help of their information. They can create and send emails with customized discounts and use different marketing strategies for different target audiences.
A number of retailers benefit from this strategy by offering their customers loyalty points that can be redeemed on future purchases. Some e-commerce companies will pick several dates throughout the year to give loyalty members a bonus on every purchase. This strategy aims to increase customer engagement, interest, and spending during a slow season. They also provide the company with information that enables it to offer personalized shopping recommendations. Loyal customers are treated like VIPs.
4.  Price Optimization and Increased Sales
Loyalty programs, secure payments, and seamless shopping experiences contribute more to customer satisfaction. Customers who have been loyal to a company for a long time may receive early access to sales, and customers may pay higher or lower prices based on their location. Using big data analytics, e-commerce companies are able to find the best price for specific customers to boost sales from online purchases.
One of the world’s most successful e-commerce companies is Otto, the biggest online retailer for home furnishings in Germany. It is one of Europe’s most successful e-commerce companies. Keeping that title means Otto has to compete with giants like Amazon. Otto consolidated its many data silos into one database and developed a 360-degree customer profile tool to develop 360-degree profiles of customers, analyze competitor data, and determine what sales channels work best. The company can now use big data to optimize pricing, create more targeted marketing campaigns, and hone its onsite advertising strategy by using big data.
5.  Outstanding Customer Service
Customer satisfaction is key to customer retention. Even companies with the most competitive prices and products cannot have their customers without exceptional customer service. A new customer can cost you five to ten times more than retaining an existing one, according to What’s more, loyal customers are more likely to spend up to 67% more than new ones.
A company that provides top-notch customer service increases its chances of attracting good referrals and sustaining a recurring revenue stream. The main goal of every e-commerce company should be to keep its customers happy and satisfied at all times. When it comes to big data, however, how does that help their customer service department? Big data can discover customer satisfaction levels, product delivery issues, and even brand perception. Big data analytics can pinpoint the exact moments when customer perception or satisfaction changes. By defining areas for improvement, companies can improve customer service more quickly.
ALDO is a footwear retailer in the United States that understands the importance of customer service for millennials, who constitute a significant portion of their sales. ALDO needed the ability to leverage big data to understand customer behavior better and provide excellent customer service to them. ALDO customers are not only interested in interacting with ALDO’s e-commerce webpages, but also in hearing and reading about ALDO on social media and through other channels.
Using big data, ALDO Corporation develops innovative products and delivers outstanding customer service. ALDO collected customer data, but it was a challenge to tie customer profiles to transactions and interactions across all channels. In order to take advantage of variable costs, ALDO now offers a localized experience for each of its customers through the use of a big data tool that is agile, fast, scalable, and flexible.
6.  Predicting Trends and Forecasting Demand
Catering to a customer’s needs isn’t just a matter of the present situation. Successful e-commerce relies on stocking the proper inventory. Marketing campaigns can be planned around big events or emerging trends are identified using big data.
A great deal of data is collected by companies in the e-commerce industry. Studying past data allows e-retailers to predict demand, plan inventory accordingly, stock up to anticipate peak periods, and streamline overall business operations. During peak shopping seasons, social media can advertise significant discounts on e-commerce sites.
As part of optimizing pricing, online retailers can offer limited-time discounts. The ability to determine when values should be provided, how long they should last, and at what price a discount should be offered is more precise and accurate with big data analytics and machine learning.


Big data has already impacted e-commerce to a considerable extent and will likely continue to do so. By 2040, 95% of all purchases will be made online, according to a report by 99 Firms. The use of big data analytics is useful for improving copy, improving customer service articles, and interpreting surveys. Furthermore, e-commerce businesses are prepared to deal with seasonal influxes, new trends, and customer preferences.
Most big datasets are not being utilized by e-commerce businesses, even though big data can be their most potent tool. Traditional on-premises solutions cannot store or process data sets of today’s scale and complexity. What can e-commerce companies do? To harness the power of big data, e-commerce companies use big data analytics powered by the cloud. Data can be held, transformed, and examined quickly and effectively using cloud-based tools.
Big data is a game changer in retail and eCommerce. Make the most of big data strategies in your business to improve customer experience and increase profits. Using ProxyCrawl, one of the most powerful web scraping tools on the market, you are able to collect the necessary data in the desired format.


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