This post was co-authored by Qamar un Nisa and Mike Cedric.


Customized shopping is becoming a trend lately as consumers all over the world are attracted to tailor-made solutions and experiences. Businesses everywhere are now moving to technologies that can provide this specialized content to the consumers. Using these technologies, they are providing unmatched unique and creative experiences to their users that drives their market value.

The technologies that are making customized shopping possible are machine learning and artificial intelligence. Together, they are revolutionizing the way consumers purchase their everyday products. By using cognitive abilities, retailers are targeting users based on their shopping behavior, trends in the market, and the overall business environment. It’s been said that AI will change the way we shop, and that’s now happening — the technology is already implemented and as predicted, it’s transforming shoppers’ experiences.

These new technologies have definitely changed the way we shop online, where we need to scroll through a long list of products to choose from and then work our way through any number of unnecessary menus. With these new technologies, we’re no longer required to go through this tedious process; based on a user’s past shopping behavior and specific interests, the system makes relevant suggestions.

Machine learning: No programming required

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to “produce reliable, repeatable decisions and results” and uncover “hidden insights” through learning from historical relationships and trends in the data.

Machine learning is also making fundamental changes to the way businesses and clients interact. Customer service is at the forefront of these changes, with increasingly advanced artificial intelligence giving companies new options for offering support, information, and assistance.

The North Face: Personal shopping with Watson

Let’s look at an example: The North Face teamed up with IBM to use the Watson natural-language, machine learning system as part of the Expert Personal Shopper (XPS) software. The AI-powered online shopping assistant, which has been 12 months in the making, is live on The North Face site. The company wants its customers to get the perfect jacket for whatever they’re doing — skiing in Vermont, ice skating in New York City, or just trying to stay warm on the way home from work. The AI system asks questions like, “Where and when will you be using this jacket?” “What type of precipitation do you expect?” and “What kind of activities will you use this jacket for?” The system then assesses the criteria, sorts through the selection of jackets and offers up its best picks.

Analyst Rob Enderle, speaking with ComputerWorld, says the technology will allow retailers to give their customers a more personal shopping experience. “It will more effectively allow for highly customized user experience at massive scale,” he said.

Businesses can now use artificial intelligence systems to remember user preferences, ultimately giving them more relevant information and showing them campaigns and products tailored to their interests.

Additional reading

Interested in learning more about AI and machine learning? Check out these pages:

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