Personalized recommendation? Image search? Shopping guide robot? See how artificial intelligence will disrupt the traditional shopping experience

In order to serve today's customers, simply emphasizing the simplicity and convenience of online channels is far from satisfying. A good customer experience is essential for every successful purchase. According to IBM's research, 70% of customers will no longer buy brands that give them a very bad shopping experience. Many of them even lose out because they have not bought the products they are interested in.

Given these issues, the speed at which customer needs are met is crucial because people are prone to immediate gratification and impulse buying desires. So e-commerce needs a fast personalization engine to enhance the customer experience. Each advice given to the customer should be dynamic and personalized. Machine learning has been used by e-commerce giants such as Amazon to provide customized product recommendations and best-selling leaderboard services. This not only saves customers time, it also differentiates them based on their relevance, completing the transaction in a more seamless and quick way.

Most traditional algorithms first use the previous keyword search, customer characteristics, historical clicks, etc. to rank the most relevant items.

Not just text descriptions, image recognition has also been used to enhance the customer experience. A technology company called Visenze is applying visual analysis and machine learning to provide customers with personalized solutions for e-commerce. "Image Search" allows customers to find items that need to be purchased by uploading images without having to enter keywords. It will also recommend to customers products that look visually similar. By looking for styles, patterns, and colors, related products will be displayed based on relevance instead of popularity. E-commerce companies, such as Lazada and Zalora, have used the Visenze solution to improve the customer experience.

Machine learning is used for customer experience and even beyond keyword and image search. Chat bots can help e-commerce interact with customers using large historical data sets and some pattern recognition techniques. By associating mobile messaging applications such as Facebook Messenger, Whatsapp or Kik through APIs (Application Programming Interfaces), chatbots are already adaptable enough to replace human employees.

Imagine personalizing communication with a large number of individual customers without a sales representative or call center. How can this be done? Once you start talking to the chat bot, it will initially ask your interest. After answering the things you are looking for through a machine learning algorithm, it will display the photo of the item you are looking for and some statistics of its corresponding price.

From then on, the customer can respond with the robot to let it show different equipment and accessories. The customer then buys by clicking on the picture to connect to the e-commerce site. In addition, this robot can send emojis facial expressions to allow customers to feel like they are chatting with friends before buying.

A recent IBM study showed that personalized recommendations from e-commerce companies can effectively increase sales efficiency or conversion rate by 5.5 times. These "mass personalization" machine learning tools enhance the customer experience by improving customer understanding and relationships. This can also increase cross-selling and upselling opportunities.

There is no doubt that this innovation will soon change the entire retail business.

Via The Nation

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