From construction to manufacturing, retail to healthcare, the three Vs– Velocity, Volume, and Variety – govern everything. These also form the essence of all technological innovation such as Bigdata. In fact, the merger of all the three Vs into Big Data has revolutionized the way industries, especially the retail sector, function these days. In 2017, e-commerce was responsible for around $2.3 trillion in sales and is expected to hit $4.5 trillion in 2021, according to a report by Statista.

In the US alone, e-commerce represents almost 10% of retail sales. And the numbers are expected to grow by nearly 15% each year. A lot of homework goes behind achieving these goals. Everything on the Internet is tracked: the IP address from where the order is placed, shopping trends at that address, click-through rates, the optimal time of engagement, likes and their reactions, demographics to even referral traffic.

Big Data Analytics and the world of retail

Retail and E-commerce are fast-moving domains, which witness constant innovation transforming their landscape in a major way. Retail industries, thus familiar with the ever-changing demands of the customers, are ready to invest in technologies such as machine learning, Big Data, and artificial intelligence to improve the customer experience. Big Data, however, plays a very important role in gauging customer behavior by tapping into important search information every time a customer shops online. It reveals patterns, trends, and associations, especially relating to human behavior and interactions. Simply put, Big Data services the purpose of attracting new customers and retaining their interest in the respective brands.

Using BigData analytics services in retail

 

Spending predictions

The filters on Amazon or eBay create a blueprint of the customer’s behavior every time he shops. Some of the most common ways the predictions are made are through loyalty programs, credit card transactions, and more. As retail businesses gather more information, they can analyze the ebb and flow of shopping and spending. Also, festive seasons and customer ordering trends help in making future predictions in spending and creating personalized recommendations.

Personalizing the buying experience of customers

Through Big Data, retailers get a detailed idea about the user behavior of the customer, allowing them to provide better customer experience. This provides personalized recommendations, adding value to the way people perceive online shopping.

Forecasting the future trends

Sales on e-commerce websites largely depend on current trends. These are predicted through Facebook and social media browsing of the customers. Even web browsing is tapped and analyzed, providing an insight into the customer’s thought process. One of the most interesting examples recorded in the history of retail business is the business strategy adopted by Walgreens and Pantene, which centered around the weather patterns of the area. This not only helped them provide customized recommendations to the customers but also increased sales for the product concerned. The companies aligned with the Weather Channel to take advantage of the increased humidity levels in the air. They started highlighting the advantages of using anti-frizz hair products for hair nourishment. They backed this with a strong marketing strategy to push customers to believe that they must buy the product during the monsoons. The results were significant. The purchase of Pantene products at Walgreens leaped by 10 percent over a span of two months. In fact, Walgreen saw a 4% hike in its sale of hair care products.

Optimizing pricing

Tracking millions of transactions each day gathers a lot of information about the pricing trends that buyers seek. For instance, the price filter set by a middle-class buyer would be different from the one set by buyers who care less about the price tags. While the recommendations would be different from each of them, buyers would get pricing options for the same product. This way, neither the price cutoff needs to be applied nor is the buyer left out from the opportunity of choosing quality overpricing.

Big Data analytics is changing the world quickly. However, it impacts the retail industry most. Better technologies could tap into the e-commerce market 10 years down the line. But Big Data is here to stay, owing to the technology and the strategies it uses to tap into the minds of the customers.