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5 Technology trends that can reshape the future of Retail Industry

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digital transformation

Today, digital transformation has reshaped shopping, online experiences, and even customer expectations from physical stores. The COVID-19 outbreak changed not only our every-day life but also the way of doing business. But by turning the world upside down, it also brought many technological innovations.

Technology is changing the way every industry functions by helping to create efficiencies, save money, and provide better products and services. Retail businesses are also adopting technology to their advantage. Listed here are the top 5 tech trends that will transform the retail industry.

  1. Machine Learning

Machine learning can be beneficial in various ways for retailers. Some of the advantages of machine learning for retailers include customer analytics, up-selling and cross-selling the product, demand forecasting and in-store analytics. Since many retail businesses are looking to use big data, demand forecasting driven by machine learning has become one of the innovative methods to optimize customer and supplier relationship management, logistics and manufacturing processes, and running smart marketing campaigns.

Compared to traditional forecasting methods, machine learning approaches are more adaptable to changes and faster to implement. This feature makes ML-based demand forecasting applicable to today’s reality.

  1. Augmented Shopping

Retailers are utilizing augmented and virtual reality technologies to help customers interact with their products remotely and thus make more informed purchases.

Several brands embraced AR long before the pandemic. Lacoste, American Apparel, and several other brands opened virtual showrooms and fitting rooms to allow customers to try products in virtual spaces. These brands also introduced the “try-before-you-buy” approach and augmented shopping attracts customers because they can shop within their comfort zones.

Brands such as IKEA and Amazon are using ARKit-based apps to help customers visualize what new furniture will look like by moving their smartphone cameras around the room in real-time.

  1. Data Science

Data science is used to create recommendation engines which proved to be of great use for retailers as the tools help to predict customers’ behavior. Retailers have started using recommendation engines as one of the best approaches to analyze customers’ choices.

Providing recommendations enables retailers to increase cross-sale opportunities. Recommendation engines manage to improvise depending on the choices made by the customers.

  1. Predictive Analytics

Businesses often struggle with how to move their products and assets around places in the most efficient way. There are many variables that the retailers have to struggle with: shifting demand, human error, traffic, weather, etc. With technological advances, the data collected on a daily basis is analyzed to gain meaningful insights from which business-impacting decisions can be made.

Data science enables the application of advanced mathematics which provides the insights to appropriately maximize return on assets. Predictive logistic analytics is applied to predict machine behavior, human behavior, and even weather behavior. This demand forecasting helps them to stock goods in order to use them in the time of crisis. The main aim of the retail business is to provide its customers with a proper product at the right time, in a proper condition, at a proper place. When companies leverage predictive analytics into their logistical operation, they experience less mechanical downtime, more efficient routes, increased customer satisfaction, and higher stock prices.

  1. Cashier-Less Stores

A mix of cameras, machine vision, IoT, and RFID tech can track shoppers throughout the store and charge them automatically for items they pick up, eliminating the need for cashiers and checkout counters.

Cashier-less stores will improve the customer experience, since they will no longer have to wait in checkout lines. By reducing the need for manual labor in stores, this tech can reduce overhead costs as well. In addition, data on shopper behavior and movement within a store let the retailer make decisions that can better align their offerings with this behavior.

Conclusion:

Digital transformation, consumer demands for convenience, and the increase in buying power of Gen Z has created waves of disruption for retail. Therefore, fast-growing retailers are investing in technologies that directly affect the customer experience and make it convenient for the customer to shop.

Retail data is extremely growing in volume every year. Retailers are using advanced technologies to turn insights into profitable margins by developing data-driven plans. These uses of technology in retail are giving retailers an opportunity to be in the market, improve the customer experience, and increase their sales and hence revenue. And as technology continues to advance, it has a lot to offer to the retail world!

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