3 Ways Real-Time Technologies Are Improving the Retail Industry

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With so much new data available, executives in the retail sector can adjust their business strategies and cater to consumers in ways they never could.

The availability of today’s nearly instantaneous data streams has helped people in various sectors adjust their business strategies and cater to consumers in ways that make the most sense based on the input received. Then, they can make rapid but insight-driven conclusions to potentially grow profits.

Due to the fast-paced nature of the retail industry, it’s not hard for most people to see why real-time technologies are particularly advantageous in the sector. Companies that have chosen to implement the capabilities report seeing notable improvements.

1. Determining Customers Needs in the Moment

Consumer desires can swing rapidly based on numerous factors. If a famous actress carries a particular handbag during an awards ceremony, sales could spike based on that visibility. The threat of inclement weather can also spur purchasing decisions. Some real-time technologies show retailers what people search for online, allowing them to capitalize on opportunities as they arise. Others focus on in-store sales.

See also: 8 real-time lessons retailers learned this past holiday season

Tesco, the mega supermarket chain based in the United Kingdom, invested in real-time data analytics to achieve several goals, including understanding more about how customer needs fluctuate. Another one of the brand’s goals is to reduce food waste, another aspect related to shopping behavior. If Tesco uses in-the-moment data to accurately predict the foods its customers want most, less gets discarded.

2. Promoting Retail Efficiency

Due to the immediacy offered by real-time technologies, they aid retailers in achieving more efficiency throughout all aspects of their business. Reliable information drives educated business decisions, and there is now no need to delay addressing issues after identifying an area for improvement.

Eldorado Ltd., a Russian retailer of consumer and household goods, wanted to fulfill business needs more quickly. By being part of a rapidly evolving industry, its representatives knew that more streamlined operations were necessary.

The company implemented Hewlett Packard’s HANA platform, which handles real-time analytics and business processes. It was doing so while preparing for a massive systems migration that involved a transition from Germany to Russia. After using HANA, employees could process sales reports 15 times faster and create them hourly instead of every two hours.

3. Delivering Personalized Experiences to Shoppers

People in the retail industry have also realized how real-time technologies make it possible to provide highly personalized shopping experiences for customers. For decades, brands have tried numerous things to attract attention, keep people browsing and make them come back. Information given in real-time gives retailers a more in-depth understanding of the customers they assist.

Helzberg Diamonds recently unveiled its Concierge app for employees, which seeks to facilitate better jewelry-buying experiences during in-store purchases. Workers have real-time access to shoppers’ purchase history, wish lists and other pertinent information, including contact details. Furthermore, retailers can instantly check statistics for in-store inventory or pull up product information from the store’s catalog.

By relying on the captured data — plus engaging in conversations to determine shoppers’ expectations — in-store personnel should find it easier to make product suggestions. Based on the information provided about stock levels, associates can avoid disappointing customers by discussing jewelry that’s not immediately available. The app also shows whether customers are part of Helzberg Diamonds’ rewards program, an insight that might lead to promotional benefits.

These are just a few of the many ways the retail sector, an industry that must constantly know what customers want, is using real-time technologies. As an increasing number of brands try these offerings and find out what works and what doesn’t, we can expect to see platforms and tools that are even more intelligent and personalized.

As an increasing number of brands try these offerings and find out what works and what doesn’t, we can expect to see platforms and tools that are even more intelligent and personalized.

Kayla Matthews

About Kayla Matthews

Kayla Matthews writes about big data and its uses and applications in daily life. To read more posts by Kayla you can follow her blog, Productivity Bytes.

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