6 Ways Big Data Analytics Will Impact eCommerce
The number of digital buyers worldwide has reached 1.92 billion in 2019, which is a quarter of the world’s population. On Amazon alone, there were 120 million products as of April 2019. With such a huge volume of digital transactions going on, it goes without saying that big data analytics has a significant influence on the #Ecommerce industry.
In this #article, I will highlight 6 ways E-commerce benefits from big data analytics.
With the ever-growing demand for social media apps such as Facebook, WhatsApp, Twitter, and many sellers are creating online groups/pages for their online business. E-commerce has recently become a game-changer. With so much data at hand, it makes it easier for online retailers to apply some data analytics to e-commerce, and to make high-impact business decisions. With such a large amount of digital purchases going on, big data analytics has a significant impact on the e-commerce industry. We’ll highlight points in this blog post by which e-commerce profits from big data analytics.
Big data generally means large datasets that are collected and processed with the aid of the latest technologies. It provides useful market insights for your business and assists in decision-making. Big datahas played a crucial role. When it comes to enabling organizations to improve their functional ability, expand their scope, and better communicate and support customers from the extraction of qualified user data.
Big data analytics means the process of harnessing these large data sets to reveal hidden patterns, market trends, customer preferences, etc. With the help of big data analytics, business owners are empowered to derive values from information and make optimal business decisions.
In eCommerce, big data analytics not only helps business owners understand customers well, but also it predicts market trends and assists in boosting revenue. Let me break down the advantages big data analytics brings to the eCommerce industry.
Business is all about figuring out people, especially the customers. Back in the time when online transactions were not prevailing and people only shop in stores, it was not feasible to trace the background information of every customer. Nowadays, there are around 2.05 billion people purchasing goods online. Though they tend to switch between sites before making a purchase, the browsing activity data can be tracked and analyzed.
Big data analytics tools can track the buying journey of customers. They capture the interactions a user previously had with a brand, including products viewed, clicks, past purchases, etc. The data allows business owners to get the shoppers’ information and understand the shoppers in-depth- what they like and dislike, which products are in hot demand recently, what time of the year the demand for certain products rises, etc.
87% of shoppers said that when online stores personalize the shopping experience, they are willing to buy more. After a business gets the shoppers’ info, they can create personalized experiences that cater to their needs.
Personalized experience strategies include sending customized emails to users providing special discounts and offers, showing targeted ads to different groups of people, implementing up-selling and/or cross-selling strategies to individuals, etc. The world’s largest eCommerce giant Amazon is a great example of using big data analytics and cross-selling strategy to generate high revenue.
When browsing products on Amazon, people are frequently attracted by recommendation lists such as “customers who viewed this item also viewed”, “inspired by your browsing history”, “popular products inspired by this item”. These recommendation lists were generated based on Amazon’s millions of online shoppers’ databases. According to the browsing history, Amazon provides personalized recommendations to each shopper and this greatly increases the chance of successful sales. It sounds like a small strategy, but the result is astounding: in total, the product recommendation algorithm drives 35% of cumulative Amazon company revenue.
Big data analytics gives you a better understanding of the overall operations of your e-commerce business. Thus, using e-commerce data lets you control inventory, supply chain, forecasting criteria, competent pricing strategies, and sales strategies. Therefore, helping you in predictive analysis for better approaches to boost your e-commerce business. E-commerce would have the added benefit of versatility in deciding on the best possible means of operating productivity across multiple networks. There may also be room for learning in this field through several big data case studies on e-commerce.
Above all, big data offers a centralized platform for all the payment functions. Not only it makes the lives of customers easy, but also it prevents fraud, which is very common in any online transaction. Big data allows the detection of fraud and presents methods of risk identification and solutions to these risks.
Analysis of data provides an increase in sales for multi-vendor eCommerce companies by cross-selling, thanks to improved customer understanding. Customer data is validated through the generation of push notifications.
The increase of smartphone usage in modern society is simply put enormous. Recent research shows that PCs are a dying breed. Laptops, notepads, and mobile phones are the future.
Mobile technology is providing big data with multiple sources for information gathering, and it makes it easier to see what is trending in today’s society. Always a pioneer, Google is giving a clear advantage to websites that allow users access on their mobiles. The brands that do not provide mobile-friendly websites are about to see a big decrease in their sales due to low traffic on their domains.
Apart from attending to the present business, it is important to catch and even create new opportunities in the future. Ecommerce business relies heavily upon stocking. Too less stocking will lead to product deficiency and impact customer satisfaction, while too much stocking may cause excessive costs. For products with a short shelf life, this is especially harmful because the cost would be irreversible.
Big data can help companies estimate future stocking based on past experience, and plan marketing campaigns ahead of time. Based on historical sales data, online retailers can predict future sales and prepare a proper number of goods in the warehouse. Using social listening, they can discover new buzzwords and react promptly to catch golden opportunities to make more sales.
We’ve looked at the six ways big data analytics can have an impact on e-commerce. Through knowing and evaluating consumer expectations and behavior, it paves the way for new ways to deliver improved customer support. Big data analytics also lets you understand the strengths and weaknesses of your own company. Therefore, allowing you to create better product designs, better pricing strategies, and better competitive strengths. To top it all, big data analytics helps the authorities detect payment frauds through websites and mobile apps. This allows companies to provide different payment options via a single centralized platform to make payments more convenient.