Information is the oil of the 21st century, and analytics is the combustion engine.”–Peter Sondergaard, Senior Vice President, Gartner Research.
Every industry has absorbed data in real-time, customized it and are in the modern digital landscape. This change necessitates retail industries to join the race to optimize services of business processes and their customer expectations. Digitization has given power to consumers and today they are called ‘digital-customers’ or ‘omni-customers’. They don’t care what channel it is as far as it’s convenient and matches their expectations. In order to survive or keep running in the race, retailers must stop selling only the things and start selling the experience along with the thing.
“Cross-channel retail sales in the U.S. will reach about $1.8 trillion by 2017.”–Forrester
With the evolving digital technology, there has been a plenty of operational changes in the retail industry. Big data analytics has played a critical role in helping smart retailers to manage valuable data. The e-commerce platform is one of the best examples of big data user and has acquired the most benefits.
For example, Amazon, the world’s largest electronic commerce company is the massive adopter of big data analytics. Whenever a user browses their website, based on the user’s behavior, it starts sending recommendations of the similar products on which the user has shown interest or based on an algorithm prediction of what the user may like. Research says around 30% of their sales are from the recommendations. Therefore, big data is helping Amazon to increase their sales percentage immensely.
Big data is a huge information set. Big data analytics helps enterprises to obtain tie-ups and resolution from the large data using powerful tools to extract conclusions from both systematic or nonsystematic data to provide insights. It provides a reliable vision and an enormous opportunity to the enterprises. Big data analytics provides three major benefits, they are;
The acquisition of big data analytics helped retailers to better interpret their customer or potential customer’s behavior. It’s cost-effective technique has helped both online and offline retailers to embrace analytics solutions to effectively target their audience and upgrade their supply chain operations.
The retail industry has come a long way and this analytics helped them to not only identify their customers but also know their customers inside out. Leveraging the fast transforming digital world, retail industries are now able to grab a deeper insight using big data analytics. This is only possible if you have the appropriate tools, a flawless strategy, and manpower who can extract most benefits from the Big Data Analytics.
“Retailers that embrace big data analytics yield a 60% boost in margins and a 1% improvement in labor productivity.”–Mckinsey
Price optimization is no more a choice, it’s a need: Big data analytics plays a vital role in price control. Algorithms provide a deep insight on the demand flow, inventory status and help retailers to have a smart peep on their rivals. Depending on the data, price optimization helps them to decide when to drop and when to raise the price. Earlier most of the fashion retailers used to change their merchandise prices depending on the change of the season. Like at the end of any season, having the assumption of less demand, they used to reduce the prices. However, after implementing big data, retailers will have informations that are data-driven and prices that are optimized based on the real time demand. Now with the updated and analyzed big data, prices can be changed any minute as per the demand.
Prediction for future trends and demand: Big data helps retailers to weigh the present situation and envision the future. Advanced machine learning algorithms are used to predict the upcoming trend with the help of social media and web browsing pattern. The gathered customer data will help retail industry to forecast the product demand and target their users accordingly in a particular category.
According to KPMG 2017 Retail Survey report, Millennials choose social media to collect information about trending fashion, products or brands that toll with them. All these information are used by the retailers to leverage a digital gateway which helps them to create a database of customer preferences. With the right data and analytics retailers will have the ability to predict and set a campaign to target their users based on demographic, gender and user’s behavior.
Offer smart experience to the customers: Retail industry’s competition is warming up and customer experience is on their priority strategy list. Each transaction or the activities that the customer does will be recorded and will have a unique ID, which can be accessed by the retailers. Big data analytics plays an essential part here to ensure which customer showed interest in what product. With the accumulated data, the retailer can create a smart shopping experience on every interaction with their customers.
Retailers determine which product has more demand in the market, using data analytics and ensure that there is no shortage in the stock. They are able to regulate the product price, send relevant promotions to the customers to have pleasant shopping experience. As per the Harvard Business Review research, retailers who are able to provide the smart shopping experience to their customers are likely to increase their ROI from 5 to 8 times and raise their sales up to 10%.
The key to enabling a better customer shopping experience in retail industry is to integrate high-end technologies to gather data. Augmented Reality and Internet of Things (IoT) are the two emerging technologies that have a huge scope in the future for the retail industry. It was already predicted by Juniper in 2015 that retailers are going to spend $2.5 billion on connected devices by 2020.
A retailer’s real assets to run his retail business are the customers and the data. Therefore, to better understand their customer’s behavior, all smart retailers are going to use big data analytics to ensure an efficient customer experience.