The top 3 AR experiences at Ulta Beauty

Authors: Agustina Sartori — Director AR Innovation at Ulta Beauty, Martin Etchart — Senior Computer Vision Engineer

Let’s start with the basics. Augmented Reality is an interactive technology experience that augments the physical environment in the real world by overlaying computer-generated information, colors, textures, objects, and digital content.

In the past 18 months, Ulta Beauty has launched three AR experiences in its Android and iOS app. Our goals were to create fun, interactive ways to explore, experience, and help choose the best products for you.

Realism and personalization are at the center of what we do. You can experience authentic, custom discovery within our virtual try-on, shade finder, and skin analysis tools.

See it on you with GLAMLab Virtual Try-On.

Within GLAMLab, an app developed with modern mobile paradigms, makeup is rendered based on a digital product description with great realism using a custom, highly-optimized graphics engine. The digital product descriptions are born from careful data analysis and extensive knowledge of the real product.

GLAMlab makeup try-on in the Ulta Beauty app for Android and iOS

All products in GLAMLab are physically swatched and translated into a digital representation of color, texture, and finish to provide the most realistic AR experience possible.

For a smooth, accurate live try-on experience machine learning algorithms run in the background for facial detection in real-time and a custom-built computer graphics engine works to apply makeup.

Find the right foundation through the Shade Finder.

The foundation shade matcher offers a true fusion of AI and AR at multiple levels.

GLAMlab Shade Finder in the Ulta Beauty App for Android and iOS.

A Deep Learning model trained on diverse face image datasets leverages face scan and built-in, real-time light estimation to determine a guests’ skin tone and undertone.

Based on results, a guest is matched with the best shades from an accurately color-calibrated product catalog, and further personalization is made via a custom AI recommendations engine, leveraging the guests’ purchase history. Finally, guest experience the recommended shade and can navigate similar ones via the foundation try-on.

Understand your skin conditions and how to treat them with Skin Analysis

AR/AI-driven capability in Mobile Apps allows Ulta Beauty to ask guests a few questions and then offer an intelligent, in-depth analysis of their skin.

Skin Analysis experience in the Ulta Beauty App for Android and iOS

Offering a virtual, customized skin report with diagnoses of skin conditions such as redness, breakouts, dark spots, and fine lines is a prime example of personalized innovation especially as the outcome is curated recommendations that includes tips and a means to sort and filter results.

With AI personalization, we aim to select the best-suited products for each guest according to the conditions we detect and their skincare goals.

These experiences are great for guests more relevant than ever before for both the online experience and to further leverage when shopping in-store. As some beauty enthusiasts opt for safe, socially distant beauty experiences, Ulta Beauty is prepared to meet them where they are and with exciting ways to discover and explore. We have seen engagement sky-rocket throughout the pandemic as many shoppers shifted to online shopping. GLAMLab is a fantastic tool today and will continue to evolve.

GLAMLab usage has increased by five times in the pandemic, and we have seen 25 million shades tried on in the post-Covid-19 environment.

We believe our guests will continue to choose tech experiences, even as we assimilate back to life outside the home and return to in-store shopping.

The concept of try-before-you-buy will always be appealing — for both brands and consumers — as it bolsters confidence in purchase decisions, customer satisfaction, and decreasing return rates. And now our Technologies are crucial to our guests.

Download the app here: https://www.ulta.com/app/.

--

--