How AI is Powering E-Commerce


Unless you have been settled deep underground for the last several years, you’ve most likely learned of artificial intelligence (AI). But how do we apply artificial intelligence to e-commerce? This article is going to share about three practical ways that B2B businesses are using AI in digital marketing and online shopping.

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1.Create AI-Image Search

Since online retail is so image-based, retailers have found out AI is a key element in the digital marketing. Although AI-image search has been initially established, the core technology is grounded on digital platforms running machine that increasingly understands consumers’ preferences based on the images and websites that they browse online and “like”. Then AI software will automatically organize and search content by labeling traits of the image or video.

A great example would be Pinterest’s visual search feature, which allows shoppers to circle a desired item in any pictures online and have Pinterest spit back a number of similar items at a range of price points using image recognition software. Except for finding matching products, AI is enabling net users to uncover products or services they might not even know they need, said Kristin Shevis, chief customer officer at Clarifai. These are both beginnings of how deep learning fit snugly in a retail context.

2.Optimize Websites and Content

Another AI breakthrough in online commerce is website and content optimization. The traditional way to improve online content is through trial and error, which is not time-efficient as this multi-point optimization problem requires degrees of freedom, ranging from images, messaging options, and font size, to page layout, ads placement, and so on. Furthermore, it is hard to define what is “optimized” since people have different aesthetic views and surfer behaviors.

A type of AI techniques, called evolutionary algorithms (EAs), is specifically suitable here. It comes up with a mountain of alternative solutions, measure each performance live, and move on to build better solutions based on those already measured. The key is every solution is measured online against existing user base, and then improved on a constant basis. In other words, the frequent and continual optimization is developing with rapidly changing customer behaviors.

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3.Reconnect with Potential Customers

According to Conversica, at least 33% of marketing leads are not followed up, and at least 50% of sales efforts and 50% of lead generation budget are wasted on those losing leads. This is a fertile area where AI could be applied to improve the sales cycle.

Facial recognition used in mobile device security is becoming familiar to the public. It can also be utilized to capture customer browsing time in the physical store, and send the data to central data bank for customer behavior reports. Such first-hand information is a powerful reference for sales teams to send customized product offerings and make progress in the ability to remarket to those customers.


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