Q&A with FaceCake Founder and CEO Linda Smith

KEY POINTS

  • Focused on augmented reality since 2010, FaceCake Marketing Technologies describes itself as “a leader in augmented retail with a personalized, cross-device, targeted marketing platform. Combining patented technologies with intuitive user interfaces, FaceCake’s innovations in try-on allow consumers to virtually try individual or multiple products on their own images in real time, while instantly providing relevant product recommendations within each user session for superior personalization.”
  • We were able to catch up with Linda Smith, Founder and CEO of FaceCake, to discuss the launch of the company’s new GlamScout mobile app, which allows users to visually search any beauty look, try it on using augmented reality (AR) and shop for the products used in the image.
  • According to Euromonitor International, e-commerce and m-commerce are the fastest-growing retail platforms globally. In 2015, they totaled 6.4% of sales in the beauty space. We see new digital beauty services enhancing consumers’ shopping experiences and allowing them to make smarter purchase decisions.

Q: TELL US ABOUT FACECAKE.

We recognized early on that the future of shopping lay at the intersection of Augmented Reality and highly relevant personalization. FaceCake’s shopping platform intuitively delivers on that vision. Our robust platform runs across product categories and delivery methods—mobile, in-store, desktop, etc.—is patent protected, scalable, and adaptable to any category or partner.

We were inspired and motivated by the idea that shopping could be easier with tech, but that you had to marry the two—it could not be just tech for tech’s sake or something cool that did not fit into or extend the way you would naturally shop. I have spent the last several years working with a great team here at FaceCake to build out various shopping applications and solutions, including a virtual dressing room, a browser-based AR shopping platform and a visual search mobile beauty app.

 

Q: WHAT INSPIRED YOUR LATEST OFFERING, GLAMSCOUT?

Our latest app, GlamScout, is what I really love: being able to see a picture of a beauty look you really like and get product recommendations for the complete look. GlamScout is taking visual search to a new level. Using our color-match search process, we are able to pull the colors off an image, detect the products or shades that are in the photo, and give users product recommendations to achieve that look. We have also included our AR try-on component in GlamScout, so users can try on the look themselves. Users can then share the look with friends to see what they think and purchase the products featured in the look. These things all grew out of the natural progressions that people go through when they shop. Users continue to come back because “scouting” is the new way to search.

 

Q: WHAT SETS GLAMSCOUT APART FROM OTHER AR BEAUTY APPS?

The visual search component of GlamScout is very important in order to really fit into the shopping experience and be an extension of shopping. However, we are looking for the whole package: we want shoppers to be able to instantly grab a look and see the products, mix and match, try it on, compare it, share it and buy it. The try-on aspect is an amazing feature, but the other aspects in our platform are what make it a true platform. AR is necessary to really emulate or extend the shopping experience, but it is just a piece of the overall offering, in addition to visual search and product recommendation.

We are also the only browser-based AR company, meaning that if shoppers go to websites for NARS or Cargo Cosmetics, they can try on products using their webcam. One of the most important aspects of making AR a reality is that it has to be browser based, so it is easily accessible to shoppers from desktop and mobile.

 

Q: CAN GLAMSCOUT USERS REFINE THE SEARCH USING PERSONAL PREFERENCES, SUCH AS SKIN TYPE?

Yes, we have those capabilities, but that is not on deck for this app at the moment. We have the capabilities in the full platform to recommend based on various skin types. We detect in your image quite a bit about your skin automatically; attributes and skin conditions are recognized. We are working with a partner right now to release something geared toward exactly that.

GlamScout also offers users a “Glam Look” and a “Glam Look for Less,” the first with prestige brands and the other with mass brands. Users can even pair their favorite NARS blush with a lipstick from CoverGirl to combine the looks. Users are able to feel they have created something that they are interested in very quickly by drilling down their search very quickly.

However, we do make alterations to the product recommendations in application based on skin tone and lighting. Lighting variations matter a lot in the AR scenario and we have created proprietary processes to automatically adjust to lighting in the user session, making it a better experience for the user. As far as recommendations, we can do that and we have done that, but GlamScout is a straight-up search; the user is dictating their search and what they like to see.

Q: HOW DOES GLAMSCOUT WORK WITH BRANDS?

Our number one focus is for the user or consumer to receive a direct hit on the match of the shade that they are looking for. But, in the future, we see the ability for brands to pay for placement in the results. We have done that previously on other parts of the platform. It is one way to promote a product. For example, a brand could own the lipstick category in the reds for a period of time. For now, what we have done is create an automatic search that goes in on a weekly basis and scrapes all of our partners’ websites for shades, so users know they are always getting the latest shades. The GlamScout app and all of our other products are constantly being updated. That is incredibly important when it comes to having accurate results.

We also enter into affiliate relationships with brands that are featured on the app, so we get a percentage of the sales we are driving to them, but we do not require any upfront payment to be featured on the platform. The more shades, the better; the more partners, the better. We want GlamScout users to have a lot of choices, so they are able personalize their experience to match their preferences. For now, it is really more important to have as many choices as possible for a product match than it is to have a pay-to-play situation. In the future, as activity builds, we could offer brand placements, but a brand would still have to fall in line with our criteria for a product match.

 

Q: WHAT KIND OF ENGAGEMENT HAVE YOU SEEN WITH SCOUTING?

GlamScout is a product discovery platform that we have been really excited about and the enthusiasm for it has been wonderful. It is really a conversation with the shopper, almost like having a personalized makeup stylist who guides you through the process. It is a great way for shoppers to experiment with colors and trends they would not normally try, while receiving personalized advice and trying them out.

Users come back again and again because they are generating the content that they want to see themselves. We are also constantly updating the featured looks on the GlamScout app, so users can come in and see new, relevant looks and instantly try them out. People are coming back to use GlamScout as a resource for style and beauty looks, because they know they can immediately see how to get a look from last night’s Oscars or Grammys, for example.

The idea behind scouting is that you can search visually for whatever you want and find exactly the color you want without being limited to what is presented to you when shopping in-store or online. Our Scout app users generally return an average of three times a month and scout an average six times per session, three times more than standard search. We have great engagement rates: the first time they interact, users usually spend around 12 minutes on the app. After that, users are interacting with the platform for an average of seven minutes per session.

 

Q: WHAT DO YOU DO WITH THE DATA COLLECTED IN THE APP?

We know users’ attributes and we know their digital body language based on their self-selected items. This is how we are able to present a more personalized shopping experience to the user in the application. We are able to go back and make product recommendations using our unique algorithm that combines user attributes with the preference tables that they have created for themselves. We are able to be very expert at engagement because we can capture users’ interest by seamlessly personalizing the experience. FaceCake is really at the heart of personalization.

In addition to being able to drill down to the unique user, we also have all the global metrics: we know what shades are coming in, what shades are going out, what people are looking for. Our CTO, Darren Lu, always tells this story about when he worked at Autobytel, selling cars on the internet in college. He explained that they would push the color of the cars they had on the lot, which drove orders of one green car they had because it kept being sold—so it was feeding a fallacy into the data that this color was sought after.

With our products, we can see what people are really searching for, not just what is being offered back to them in a presentation on a website or even in a store. We see exactly what is being searched, which gives us insights into what is happening for trends and what shoppers are looking for. We see differences in different parts of the country, too. Although very similar at any given time, generally, the top three lipsticks that are searched and tried are almost the same throughout the country, but the actual order of shades is very different. New York is bolder; the South is a little bit soft; Texas is a little more intense in the oranges and the peaches.

FaceCake is very deep into analytics and metrics; we are always looking at what is happening. We have a patent on the process of marketing back to someone using their own image. We are able to, if you would like, show you yourself in recommended products. We can present that back to you, tailored to you, to what your preferences are, to relevant products. For example, I have very dark hair and I am not interested in hair products that will highlight my hair or make it lighter. I want to know what will make dark hair shiny. If I receive a promotion about blonde hair, it is not relevant to me and would not engage me. Now, let’s say I am not actively shopping for something for my hair, but if I see something that says, “Brunettes, get shine like you wouldn’t believe,” then that is interesting to me. That is the kind of intuitive platform that we have; we are making it relevant to the user.

It is helpful to users to have the ability to interact with product without risk and receive a personalized experience. We marry these two aspects in a way that keeps users engaged. They feel like they are getting what they need from our application.