How E-commerce Can Benefit from Big Data Analysis
By 2025, the digital universe of data is projected to expand by 61 percent to 175 zettabytes. E-commerce is a major part of it – accumulating information about buyers’ activity, location, web browser history, and abandoned shopping carts.
While collecting customer data is important, it is the analysis of that data that gives e-commerce businesses a significant advantage. Big Data analytics can help e-commerce companies understand their consumers’ buying habits in the light of current market trends. Thus, these organizations can adapt their marketing strategies to their customers’ needs, develop new products that meet their needs and provide excellent customer service.
What is Big Data Analytics?
Big Data analytics examines large amounts of data to uncover hidden patterns, correlations, and other insights. It allows business owners to derive value from data and make informed decisions.
Big Data analytics in e-commerce not only helps company owners better understand their clients but also forecast consumer behavior patterns and increase revenue. Here are the benefits of Big Data analytics for the e-commerce industry.
The Importance of Big Data for E-Commerce
The structured part of Big Data in e-commerce includes different types of customer information, such as an address, zip-code, and the content of a shopping cart. The unstructured part refers to email, video, tweets, and likes in social media, which may be a valuable information source for e-commerce business.
As online retailers are already using analytic tools to examine shopping carts or display individual content based on the IP address via their content management systems, Big Data discovery will eventually extend their abilities in the shortest term.
Ways to Integrate Big Data into E-Commerce
Improved Shopping Experience
E-commerce firms have an infinite supply of predictive analytics to forecast how consumers will behave in the future. For example, they can calculate the average number of items people add to their shopping carts or the average time between a homepage visit and a purchase. Companies can analyze demographic, age, size, and socioeconomic data if buyers have signed up for a rewards or subscription program.
Organizations can use predictive analytics to create new ways to minimize shopping cart abandonment, reduce time to purchase and react to emerging trends. Similarly, e-commerce companies use this information to improve their restocking and optimize business efficiency.
Along with allowing buyers to make secure payments, Big Data will help them get a more personalized shopping experience. Personalization is an important factor for 71 percent of customers in their buying decisions. Millennials are particularly interested in making purchases online and expect to receive personal recommendations.
Using Big Data analytics, e-commerce companies can create detailed customer profiles. These portraits allow organizations to segment customers based on their gender, location, and social media presence. With this information, companies can create and send personalized emails and adopt different marketing strategies to different target audiences, as well as launch products that appeal directly to particular groups of buyers.
Improved Customer Service
Customer retention hinges on customer satisfaction. Without excellent customer service, even the most attractive prices and goods fail. Attracting new customers costs 5 to 10 times more than retaining existing ones. Furthermore, loyal customers are up to 67 percent more likely to purchase new customers.
Companies that concentrate on delivering excellent customer service have a higher chance of receiving referrals. Any e-commerce company should prioritize customer happiness and satisfaction. Big Data can reveal issues with product quality, customer satisfaction, and even brand perception in social media. Big Data can pinpoint the exact moment when a customer’s perception or satisfaction changed. When businesses have identified areas for improvement, it is easier to make long-term changes to customer service.
Customers value generous offers. E-commerce firms are starting to utilize Big Data to identify the best price for products to boost online sales. Customers who have been loyal to a brand for a long time may be granted early access to sales, and rates may vary based on where they live and work.
In the past, companies used to follow traditional pricing strategies like the rule of thumb, cost-plus markup. However, when it comes to analyzing thousands of millions of products online old school pricing strategies no longer work.
With Big Data, business owners can now look at the big picture and analyze competitor pricing in real-time. Big Data tools can extract the product details from e-commerce sites and adjust pricing according to competitor prices.
Curate Social Media Feedback
Many consumers in today’s digital age will read other people’s reviews before making a purchase. By using Big Data to collect customer feedback helps e-commerce firms to figure out what’s working. Moreover, businesses can improve their products by using social media reviews.
For instance, our e-commerce development team tackled the task of implementing Big Data in social media and analyzing the statistics to further enhance world-famous network’s online advertising campaigns. The requested analysis covered the users’ activities, their behavioral patterns, collaborative filtering, and detection of viral patterns.
Uplifting the customer’s analytics system, SCAND contributed to using the client’s resources efficiently.
So, knowing the audience’s opinions and thoughts gives a tangible advantage among competitors.
Predict Trends and Forecast Demand
Catering to buyers’ needs is not the only issue. E-commerce depends on stocking the correct inventory for the future. Big Data can help businesses prepare for emerging trends, seasonal changes or plan marketing campaigns around events.
E-commerce businesses accumulate massive datasets. By analyzing data from previous years, they can plan inventory, predict peak times and forecast demand as well as streamline overall business operations
To optimize pricing decisions, e-commerce companies can also provide various discounts. With Big Data and Machine Learning, understanding what discounted prices to offer is much more accurate, when to offer discounts, how long they should last, etc.
Big Data has been taking the e-commerce industry by storm. While Big Data helps e-commerce companies to increase revenues, customers benefit from the personalized, real-time experience. Shoppers can view and buy products that they are interested in, while store owners still can make greater profits. Big Data aims to bring the right people in front of the right products at the right time. If you need a consultation, feel free to contact our big data app development team for questions.