The Intersection of AI and AR: How Machine Learning is Changing the Game

Thanks to the combination of AI (Artificial Intelligence) and AR (Augmented Reality), the world of retail and eCommerce has been able to provide more personalized, immersive, and efficient shopping experiences for customers.

But how is that possible? Well, the answer is as simple as this: AI algorithms can analyze large amounts of customer data to make predictions about customer behavior and preferences, while AR technology allows customers to visualize products in their own space. Together, they create a vortex of possibilities.

First, let’s look at how AI is used to create better AR experiences in retail and eCommerce and then let’s explore the ways in which AI is used to generate recommendations in virtual try-on experiences, such as for eyewear and makeup.

AI For Better AR Experiences in Retail and eCommerce

Let’s first address the obvious; Machine learning is a branch of artificial intelligence that involves training algorithms to make predictions or decisions based on data. In retail and eCommerce, machine learning can be used to analyze large volumes of customer data to identify patterns and trends, and then make predictions about customer behavior, preferences, and needs.

And so, AI – i.e. Machine Learning – plays a critical role in improving AR experiences by enabling accurate and reliable image recognition and tracking. Since image recognition algorithms use deep learning techniques to analyze and interpret visual data, AR applications can then place virtual objects or information onto the real-world scene, recognizing and understanding the environment around us.

AI can also improve image tracking, which is the process of tracking the movement and position of objects in real time. This is important in AR applications because it ensures that virtual objects remain stable and anchored to real-world objects as the user moves their device.

Another added benefit to AI is analyzing customer data and providing personalized AR experiences. This can include displaying products that are more relevant to the customer's interests or recommending complementary products.

Finally, AI-powered chatbots can provide customers with quick and efficient customer service, whereby said “Chatbots” can answer frequently asked questions, provide product recommendations, and even process orders.

AI for Virtual Try-On Experiences

With the help of AI, retailers can create virtual try-on experiences for customers, allowing them to see how eyewear, makeup or even clothes will look on them before making a purchase. AI algorithms can track the customer's body movements and display products on their bodies in real-time. This can help customers get a better sense of how products look before purchasing them.

Another important aspect here is facial recognition technology, which analyzes a customer's facial features and allows them to apply makeup products virtually to their face, giving them an accurate representation of how the makeup will look on their skin. Customers can even try on different shades and finishes to see which product suits them best. AI is also used in VTO for skincare products, through which a customer's skin type is analyzed, and the most suitable products for individual needs are recommended.

At Designhubz, our AI-Powered product recommendations enhance customers' shopping experiences and aid in their purchasing decisions. Indeed, our solution scans the face and recommends products based on facial features – all of which perfectly fall into place in both the cosmetics and eyewear industries.

In addition to improving the overall shopping experience, AI-powered virtual try-on apps can also provide valuable data for the retail industry. By analyzing customer preferences and behavior, these apps allow companies to better understand their customers' needs and develop new products that are more tailored to their individual preferences.

Brands Channeling AI-Powered solutions for VTO

L'Oreal, Sephora and Warby Parker are some of the many brands that have developed a range of virtual try-on experiences for their makeup and eyewear products using AI and AR technology.

L'Oreal "ModiFace" app uses facial recognition and 3D modeling to create accurate virtual representations of customers' faces, allowing them to try on different makeup products and see how they look in real time. The app also includes personalized skincare analysis and recommendations based on the customer's skin type and concerns. Interesting fact: when the leading beauty group acquired Modiface in 2018 to include VTO to its marketing strategy, it saw an increase of 52% in its eCommerce sales during the following year.

In the eyewear industry, Warby Parker has developed its own "Virtual Try-On" feature using facial recognition and tracking to place virtual glasses on the customer's face allowing them to see how different frames will look in real time. In this brand’s case, the placement algorithm mimics the real-life process of placing a pair of frames on your face, taking into account how your unique facial features interact with the frame. In other terms, the glasses will stay fixed even if you tilt your head.

In a world where Artificial Intelligence and a brand’s success are so interconnected, it only seems fair to bask in the glory of Machine Learning and grasp its benefits by the handful.