It wasn’t so long ago that the concept of AI, or artificial intelligence, seemed to many like science fiction. But now, we encounter AI on a daily basis. Indeed, much of our engagement with the apps and online services we use regularly relay on artificial intelligence.

For example, if you’ve ever used Google Maps while driving and have heard the narrator inform you that a faster route has become available, that’s the work of AI. The recommended videos you see featured on Netflix or YouTube have been selected just for you using AI that’s informed by viewing choices you’ve made in the past. The same goes for the suggestions you see when you visit online retailers—the ones that appear after you’ve added an item to your cart, or even on the sides or bottom of a specific item page. These have all been carefully selected for you using AI algorithms and calculations.

AI In Online Retail

AI impacts the way we shop online. The items we see under the “recommended for you” or “customers who viewed this item also viewed” sections of retailer web pages, are driven by the analysis performed by machines, of data gathered about your online activities.

AI is also behind other convenient features we find on most e-commerce websites today. Think that’s a human on the other side of that Support chat box? Think again. Many online retailers employ intelligent chat bots that offer immediate, around-the-clock support to their customers, to varying degrees of sophistication. The AI technology behind these chat bots is constantly advancing, enabling AI to understand and participate in conversation with a human.

Why has AI had such an impact on the world of online retail, and why will this impact only grow? The answer is simple: personalisation. A recent AI breakthrough has been the ability to take content personalisation to the next level. Presenting different users with different configurations of online content according to their personal preferences. This level of personalisation heightens the customer experience beyond measure, in turn helping retailers increase sales.

The Ability To Analyse Big Data & Present

an e-commerce retailer’s content in ways that will best resonate with shoppers and prospects is powerful. In the past, it was up to the retailers themselves to constantly perform a variety of content tests, analyse their results and make tweaks accordingly. It’s easier for artificial intelligence to deconstruct big data, and faster for AI to create targeted consumer experiences.

How E-Commerce Retailers Can Embrace AI

Advancements in AI technologies are allowing retailers to achieve new and exciting feats in personalised customer experiences that increase profits. Those e-commerce retailers who ignore AI will wind up playing catch-up for years. Indeed, the customer experiences already enabled through AI—including suggestions that accurately predict customer preferences, searches that result in items the consumer will actually have interest in and more—will soon become something consumers not only demand, but expect.

In addition to using artificial intelligence to effectively personalise customer experiences, retailers can embrace AI as a method for eliminating costly, time-consuming content testing. Testing at the hands of marketing and sales professionals involves a number of touch points (messaging, text positioning, call-to-action, etc.) that make it difficult to implement the exact array of changes needed to achieve the best possible communication—especially if you’re targeting a variety of consumer types. AI will be able to quickly shed light on the web page layouts and messaging that work best for a number of audiences without the need for testing and analysing.

Evolutionary algorithms (EAs) are a subset of AI that retailers can also embrace to help improve the customer experience and grow sales. EAs create a group of potential solutions (for example, solutions to content presentation) that are tested. New groups of potential solutions are then automatically developed and tested based on the most successful solutions from previous groups. In other words, EA can test variations of messaging, images and layouts, constantly creating better options to find the best solution.

Today, technology is available to retailers that embraces evolutionary algorithms in order to help deliver the best possible experience for shoppers and close more sales. These machine learning algorithms help retailers deliver highly targeted incentives, giving customers the experience that these incentives were specifically designed for them and helping close more sales.