A customer walks into a store, the salesman assesses him and decides to sell him a particular brand-the human brain at work. A customer logs into an e-commerce site and do you know where he came from, what he looked at, what he bought last time, how he navigated through the site, how much he was influenced by promotions, reviews, and page layouts, and similarities across individuals and groups, and so much more-that is big data at work!
E-commerce companies are among the fastest adopters of big data and truly understand the importance of analytics. The efficient use of data and analytics, often becomes the competitive differentiator. Enterprises collect a wealth of data around consumer behavior, transaction details, traffic data, competitive data. The information might reside in the transaction database, web analytics database, SQL database or third party systems and is brought onto a single platform using ETL technologies so that it can be assimilated to extract valuable business insights.
USES OF BIG DATA FOR ONLINE RETAILERS
Most small merchants think that big data analysis is for larger companies. In fact, it is important for small businesses too, as they attempt to compete with the larger ones. This becomes even more important as online retailers interact with their customers in real time. Here are some key uses of big data and analytics for online retailers:
- Personalization: Consumers shop with the same retailer in different ways. Data from these multiple touch points should be processed in real-time to offer the shopper a personalized experience, including content and promotions. Product recommendations can be made based on userÃ¢??s browsing behavior, past transactions and other customers transaction where there is similarity of browsing and transaction behavior.
- Logistics: Customers expect to know the exact availability, status, and location of their orders. This can get complicated for retailers if multiple third parties are involved in the supply chain. But, it is a challenge that needs to be overcome to keep customers happy.
- Customer Service: Excellent customer service is critical to the success of an e-commerce site. But big data has made customer service a challenge by requiring seemingly every interaction with a shopper to be used for serving that shopper.
- Managing Fraud: Larger data sets help increase fraud detection. But it requires the right infrastructure, to detect fraud in real-time. This will lead to a safer environment to run your business and improved profitability.
- Dynamic Pricing: Online retailers need dynamic pricing to stay competitive. A price recommendation engine requires taking data from multiple sources, such as competitor pricing, product sales, regional preferences, and customer actions to determine the right price to close a sale.
- Predictive Analytics: Analytics is crucial for all online retails, regardless of size. Without analytics it is difficult to sustain your business. Big data has helped businesses identify events before they occur. This is called ‘predictive analytics'. A good example of this is predicting the revenue from a certain product in the next quarter. Knowing this, a merchant can better manage its inventory costs and avoid key out-of-stock products.
Several studies indicate that the digital universe will double in about every two years for the next few years. It is estimated that that the world's largest retailer collects more than 2.5 petabytes of data every hour from its customer transactions, which is the equivalent of about 20 mn filing cabinets worth of text. So the challenge of this big data for online retailers is to have a clear understanding of what questions you are looking to answer, which system will be used as the source of data, and how users, products, merchants, logistics partners, etc, are tagged within these systems, so that all the data can be brought to a single platform where it can be methodically analyzed to draw meaningful inferences. Exciting times have just begun!