The world of ecommerce has expanded exponentially from the days of Amazon founder Jeff Bezos selling books out of his garage. Now, customers can purchase almost anything online and have it delivered within a matter of days or even hours. There’s no end in sight to the way ecommerce can be utilized. One of the aspects of this growth is the implementation of AI ecommerce. It plays a pivotal role, especially in larger stores.
The term artificial intelligence (AI) refers to a collection of programs that can simulate the way a human interacts with the world. This allows companies to implement chatbots that will respond to customers the same way in which a customer service representative would. Couple AI with machine learning, and the chatbots can pick up on language and interactions on its own. This leads to the creation of powerful shopping tools for stores and customers alike. It also adds to the online customer service experience.
AI ecommerce isn’t just about chatbots. In fact, a large portion of it deals with systems that run behind the scenes and add to a customer’s shopping experience.
Amazon has grown tremendously since its inception and is now one of the world’s largest ecommerce stores with an annual revenue of $136-billion. The ecommerce giant didn’t grow to this magnitude from just selling DVDs and video games. Bezos has had to be clever about the way in which Amazon expands – just look at the Kindle range of devices.
A core aspect to its growth is making sure clients always have the products they want and showing them options they didn’t know they needed. This is achieved through AI ecommerce and machine learning. Amazon is able to recommend similar products to clients other than the ones they are currently looking at. By analyzing buyer history, the store can ‘predict’ what a customer will purchase next. Whenever you look at a product page on Amazon, each product recommendation and “customers who bought this item also bought” suggestion is generated through AI and machine learning. The more you purchase, the more accurate Amazon is able to send you relevant product recommendations. This methodology helps stores stay up to date with online shopping trends.
By data mining the buying habits of customers, Target was able to know that a woman was pregnant before her father did. By creating a set of criteria, the store was able to isolate which women would soon be expecting a child and send them relevant marketing information. And while this may appear to b extreme, it does make way for other product marketing options, such as similar books or movies you purchase.
Ecommerce isn’t just about selling physical products and shipping them to the customer. For example, Netflix uses advanced systems to recommend new shows to consumers based on their viewing habits. When doing so, it looks at a range of factors, such as the videos you liked and what other people like as well. The company was able to further refine this function by removing the star rating from titles and replacing it with a thumbs up or down option.
This allows the service to offer up products that customers want to enjoy, which encourages them to keep subscribing. The service does not look at pure tailoring as it offers up alternative titles to show the client that there is some variety as well. Netflix is also able to analyze data on which shows have been watched and their ratings in order to create future content, such as the service’s original series. By doing so, the company increases their pull in online customer service without the customer knowing.
And ecommerce isn’t alone in leveraging these technologies for their benefit. AI and chatbots are being deployed by the banking industry too. Read our article on how this is helping their customer service teams handle more clients faster and more effectively.