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Home / Blog / Improve Retail Business With Machine Learning
Improve Retail Business With Machine Learning
Blog
3 min read
Data and AI

Improve Retail Business With Machine Learning

October 22, 2020·By Premkumar S
3 min read
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Premkumar S
Premkumar STechnical Architect
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Technology has transformed how customers and brands communicate with each other. Shoppers were once dependent on face-to-face, in-store interactions to make purchases and receive support. Now, shoppers do their research before entering a store (81 percent of shoppers conduct online research before buying) and hardly rely on salespersons to help them make decisions. Retailers, however, have understood that by embracing technology, they can extend their storefronts to their customers’ fingertips.

Shoppers can make purchases from within social media apps and compare prices without leaving a store. While these technologies have propelled the retail industry further into the digital age, the technology that is still evolving will have the largest impact on the future of the customer service and retail industries.

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Embracing Big Data

More retailers are tracking customer shopping habits through data sources such as social media, purchase history, consumer demand, and market trends. By relying on big data technology to gain a deep understanding of shoppers and their buying trends, retailers can maximize customers’ spending and encourage customer loyalty.

According to research by Accenture report, 70 percent said that big data is necessary to maintain competitiveness, and 82 percent agreed that big data is changing how they interact with and relate to customers.

Matching Products with People

Machine learning technology boosts the reach of big data analytics and can help create an exceptional shopping experience. Innovative retailers can tap into the power of machine learning algorithms to do things like determine available products from outside vendors or recommend the quantity, price, shelf placement, and marketing channel that would reach the right customer in a particular area.

Further, the capability to automate everything through advanced analytics and machine learning soon will mean that basic customer service will be performed by bots that can predict our needs and provide service in the fastest, most immediate way possible: by offering us items we didn’t know we needed. As retailers gain more insight into their customers and products, machine learning will be able to match buyers and sellers based on buyers’ needs and product availability.

Digital Assistants

Shopping is becoming increasingly programmatic. In the future, services like digital assistants (Siri, Cortana, etc.,) will learn more about us and offer us relevant and personalized product offers. Say, for example, you use a particular brand of perfume. Your digital assistant will learn your shopping and usage habits and offer you the best deal on the product at the right time. It might even place the order for you.

Improving the backend

Machine learning and advanced analytics will not only change how we shop and provide customer service, but also simplify how retailers perform basic operations. Data science and machine learning give us the ability to automate so much of the heavy lifting required to find insight within a pile of data. With these tools, retailers can find useable and useful data to change the shopping experience for consumers.

Technology enables us to create an index of every product in the world, enabling retailers to offer customers the best prices, keep products adequately stocked, and track competitors’ minimum-advertised-price violations. A central database of the world’s product information enables retailers to offer the best shopping experience for buyers.

An innovative-technology approach to customer service and commerce will combine data about our behaviors and choices with data about products and product attributes to create the best shopping experience. This approach takes the guesswork out of purchasing and makes the shopping experience more cherishable for everyone.

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