Deep Fakes for Commerce: A New Era of Personalization for Retail

Mar 6, 2019

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CVS launches "Beauty Mark," its truth-in-advertising campaign; while AI is generating plausibly "real faces." Meanwhile, companies like SuperPersonal are putting customers into model try-on videos. Have "deep fakes" - AI algorithms that map faces and micro-expressions onto stock footage - come to retail? How can they help? How can they hurt?

Show Notes:

Main Takeaways:

Brian and Phillip are podcasting live from #Shoptalk2019!
Deep fakes are getting a little too real to be comfortable.
Personal body mapping for try-on is becoming a reality.
Can companies figure out how to keep their data in-house?

Who's Waldo: Can Humans Even Spot Deep Fakes Anymore?

Deep fakes are becoming more and more realistic, and it's getting creepy.
Future Commerce was ahead of the curve in starting to discuss the phenomenon of deep fakes, which became a buzzword in 2017 when anonymous Reddit users began to use AI to map video streams of celebrities faces onto pornographic images.
Deep fakes have moved beyond the original use-case, and have also been used in political situations, which can have serious implications, especially as deep fakes are getting harder and harder to distinguish.
Also: an effort to combat photoshopped images and promote body positivity, CVS has launched a truth-in-advertising campaign called Beauty Mark, that puts a watermark on all untouched photos, and forces outside brands to identify any untouched images in their promotional campaigns.
There are plenty of start-ups that have sprung up around this phenomenon, one being Truepic, an image-authentication company dedicated to combatting fake social media accounts, doctored photos as well as deep fakes.
Want to be even more creeped out by all of this? There's a former Uber developer who has come up with a fake-face generator, and the images are a little too close for comfort.
And just in case all of this isn't bad enough, here's a "deep fake" image of Steve Buscemi's face on Scarlett Johansen's body at an award's show.

Personalization in 2020: Turning Regular People Into Models:

Personalization, especially in retail has become a theme of 2019, and the tech is finally catching up.
Phillip says that while most virtual try on applications are not very good, Warby Parker has changed the game.
Warby Parker's AR powered virtual try on is so good, it's almost like looking in a mirror, and they are using the same depth map as Apple's facial recognition software for iPhone.
Another company that's working to change the virtual try-on experience is SuperPersonal, an AI-powered virtual dressing room experience that would allow retailers to "multiply e-commerce photography to account for different ethnicities, skin-colors, and age-groups, without the need to shoot multiple models".
"Personalization in 2020 is the whole website is literally you".
Brian makes the point that because of the last 6-8 months of advancements in AI and machine vision, models will not be needed, and will only be required as "aspirational content."

Levi's New Story: From Finished Goods to Customizable Clothing:

One session that was good at Shoptalk was the keynote by Marc Rosen from Levi's, in which he talked about how Levi's was going to be offering customizable jeans.
This changes Levi's from a company that just sells the finished product, to one that sells unfinished products that can be customized by the customer.
And this is changing Levi's entire business model because now their fulfillment centers are part of the supply chain because they are becoming part of the manufacturing process when they process these customizable goods.
And Levi's has eliminated a lot of the process that used to require manual labor to increase efficiency, replacing the old methods with laser-beams and finishes.
Levi's has also hired an AI officer, to get better omnichannel data on customers.

How Can Companies Get to Know Their Omnichannel Customers?

So because 2019 is the year of clientelling, retailers and brands are having to build relationships with their customers, and they need the data to do it.
Phillip points out that the more companies aggregate the data in-house and operationalize it as a tech company, the more they will be able to figure out what works, and what doesn't.
During Brian's interview with Chris Homer from thredUP, Chris mentioned that thredUP has a policy of testing internally, and figuring out what works in-house, before bringing in tools to supplement those processes.
Companies need to figure out what works best for them and double down on that, and they also need to build real systems to house all the data that is collected, in order to utilize it effectively.

There's so much more to see and experience at Shoptalk2019! Stay tuned for more insights, and highlights from the show! Also, let us know, what was your favorite part of #Shoptalk2019 so far?

Go over to Futurecommerce.fm and give us your feedback! We love to hear from our listeners!

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