Not just software, but solutions: What AI and machine learning mean for retail

With 45 percent of retailers planning to use artificial intelligence (AI) technology within the next three years, it’s apparent that technology is continuing to turn retail on its head.

 

On the front end, retailers are already using AI and machine learning to better understand consumers and improve the shopping experience. Retailers can use this technology to determine how much time customers spend in store or online and what marketing materials or discounts resonate best. Live chat, self-support and automated response tactics use AI and machine learning to improve the customer experience. Still, many retailers that deploy some online self-service or automated customer service AI don’t measure its effectiveness.  Capturing and analyzing this critical data is an important part of the process. The retailers that truly understand how customers interact with online technology will be ahead of the game when it comes to adopting the right technology for their backend needs.

 

It’s all about the data

Retailers are just starting to figure out how AI and machine learning technology can improve backend product decision making and make day-to-day tasks more efficient. As 34 percent of brands and marketers surveyed said, ordering and fulfillment processes could be the chief beneficiary from integration with AI in retail. Retailers who use the data provided by AI and machine learning will be able to make more informed decisions, as these tools are designed to provide supplier recommendations to retailers based on industry trends. Since there is so much turn over in retail, a platform that allows retailers to leverage machine learning can also help suppliers make better recommendations to retailers, thereby adding value to the partnership from both sides.

 

Machine learning is all about analytics and access to data. Retailers who leverage the data provided by these technologies can learn what works and what doesn’t in established processes, including those in sourcing and the supply chain. This data has the potential to improve shipping, sampling, fabrics and materials selection and more if used efficiently. Retailers who use a digital platform that allows them access to all this data will be smarter overall and will have the tools they need to really take advantage of the knowledge that comes with it.

 

AI’s ability to automate and learn from customer or internal interactions, and then predict future scenarios makes it a practical tool for retailers to have in their repertoire of resources. Last year, we saw a few companies experimenting with AI and it became the year that this technology started to prove its value for the industry. It will only become more widely used in the coming years.

 

See how else retailers can make sourcing processes more efficient in our latest survey report, “Digital Sourcing in the New Retail Economy.”

About Kamal Anand

Product Technology Strategist

Kamal Anand has deep experience in supply chain and global sourcing software development. He drives the Bamboo Rose product technology strategy. Kamal is an avid traveler and enjoys playing the role of soccer coach and Lego builder with his 2 sons.

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