Big Data in E-Commerce: Trends, Personalisation and Beyond

E-Commerce, as an industry, received a jump start because of the progress made by Big Data engines in providing critical and focused analytics to retailers. From pricing to customer analytics to Machine Learning directed marketing campaigns, the solutions are bottomless. To arrive at the solution for all these challenges of online business decision making, there is only one way to go — take in data from every source and over every angle. Big Data Analytics is the name of the solution and it is an engine that comes up with the right solution through the perfect slicing, dicing and deep learning of all relevant data. Read on to find just a few ways to do so.

Buyers and Sellers

Big Data delivers price optimization, trend forecasting and precise marketing capabilities to e-commerce companies. From the customer point of view, Big Data delivers relevant product recommendations, smart buying options and engaging information. This creates a marketplace that is buzzing with activity, efficiency and satisfaction.

Online to Offline

As e-commerce becomes more commonplace, the power of Big Data is being utilised by online players to actually move into the physical retail space too. With the kind of sharp and precise data that they have, the transition back to offline from online is shaking up retail. So, no matter whether you are a physical retailer or an e-commerce business, Big Data is the next phase of business.

Know Your Customers

A Teradata White Paper details the mining of data sources for creating personalized experiences for customers. The sources include marketing emails and interaction logs. The key is to understand the different actions and behavior of the customer on the company web site, mobile site and interactions with emails. Teradata is able to deliver a complete understanding of the customer with its functional analysis of the customer’s browser actions.

Business and Customer Insight

One of the forms of data gathering is to collect information on pages that the customer viewed or clicked on, final purchase, other products considered but not purchased, source of traffic, deals used, and so on. Through this data and the analytics so generated, business can begin to understand the level of interest that it generates among visitors, whether it is related to particular offers and deals or whether it is at a more sustainable level. What a Big Data solution delivers to e-commerce businesses is the ability to understand the standard customer profile better as well as to understand individual customer mindsets.

Send the Right Message

When a Big Data engine works on all of these data sets, your e-commerce business will be able to send the right messages to each of your customers. This makes up the most important aspect of e-commerce. Instead of sending messages that do not interest your customers or which are not even relevant, deep and wide data analysis enables your e-commerce business to communicate messages to customers that are of the greatest relevance. Imagine communicating to your customer just what they were/are thinking about. Being able to provide the ride deal or right message at the right time to incentivise people to make that purchase is what separates a successful e-commerce organization from a regular one.

Fraud Prevention

Detecting and eliminating fraud is a crucial element in effectively managing your e-commerce website. In today’s online world, no enterprise can survive and sustain for long without a powerful tool to implement security. Big Data can offer the perfect solution to just that.

For an example, Fraud Protection company Signifyd has developed an E-Commerce Fraud Index after processing transactions across eight industries. The index reveals fraud at e-commerce sites was 4.07 percent in 2017. In the online department store category, 10 percent of all fraud losses were carried out through ‘account takeover.’ This type of fraud is committed after the user’s login name and password come into the custody of a criminal player either through hacking or phishing. Then, purchases are made with the payment options activated by the customer and the product is directed to a different address by the felon. The solution is developed by picking up trends over a substantial spectrum of e-commerce merchants.

Seizing Opportunities

It is important to always be on the lookout for next big opportunity and building a connect with your market base in time to utilise the opportunity. This can includes delivering targeted ads to people within a specific region during a specific type of situation. When a special event is underway at a certain location, you can send real-time targeted ads to your customers, to increase interaction. The same can be done with weather-related events and offers for particular merchandise to be used during extreme weather or even normal weather patterns.

Recommendation Engine

Recommendations are a big factor for customer interaction and sales conversion. Identifying sales trends and purchase patterns, a good Machine Learning algorithm would be able to increase the sales and click-through rate of the online store. Not only that, total sales value of each sale also goes higher. Since this is a Machine Learning solution, the right algorithm will constantly refine the suggestions based on user, purchase history, category, customer type, and so on. The same type of process is also implemented when customers search for products. They are presented with the exact type of product they are looking for and not just a jumbled mass of uninformed products.

Getting off the blocks for a retailer has become easy through e-commerce platforms. The introduction of Big Data engines has just helped transform the modern marketplace into one that is of great relevance and efficiency for customers.

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