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How Deepfakes Could Change Fashion Advertising


A 2018 Zalando campaign featuring model Cara Delevingne across 290,000 localized ads was carried out using deepfake technology to produce a range of alternative voice shots and fonts. Now that the algorithms for media manipulation and synthesis get more powerful, the fashion industry is starting to take notice.

In the tech world, deepfakes specifically refer to media produced by artificial intelligence technology, called generative antagonistic networks. Deepfakes are video or audio that has been modified, for example by changing a face, words spoken, or language used. The term was first coined on the internet in 2017 by combining deep learning and falsehood.

The Zalandos campaign ran on Facebook in 12 countries, registering 180 million impressions on social media, according to Infinitizer, the micro-targeting agency that worked on the campaign.

Advances in technology have made it more difficult to distinguish between real and manufactured media. Deepfakes has had a bad reputation, not least because the majority is fake pornography. Critics also point to the dangers of political deepfakes that could generate compelling fake news. Any digital window to the real world can sometimes be tricked and rigged, acknowledges Sunny Dhillon, a VC who invested in a deepfake marketing company.

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Like a growing number of marketers and investors, Dhillon emphasizes the absolutely positive applications of technology. As Covid-19 lockdowns restrict in-person activities and advertisers explore digital technologies, deepfakes have significant potential for experiential marketing. Face swap technology, which once took weeks to execute, can now be done in minutes with Hollywood-quality output, according to Reface AI co-founder Dima Shvets.

Experiential marketing tends to be associated with the physical environment, like pop-up stores, but deepfake technology can bring experiential marketing online, directly to consumers, explains Dhillon. Examples could include interactive fashion weeks or gaming experiences, he says.

Dynamic influencer marketing

Dynamic campaigns, the term for large-scale, targeted micro-ads, are becoming a key tool in the arsenal of marketers. Deepfakes has the potential to help brands reach customers with highly targeted and personalized messaging. For influencers and celebrities, deepfakes help them easily expand their reach by agreeing to feature a fashion and model clothing ad campaign without even showing up for a photoshoot. Millions of different deepfake ads can be served instantly on platforms like Facebook, while up to 100 different influencer ads targeted to different audiences could be served, says Simon Lejeune, growth marketing consultant.

This is not a giant leap in a world where digital identities such as game avatars already overlap with real identities, while CGI models intermingle with real influencers. Imagine a new type of agreement, where an influencer provides a brand with a 15-minute sample of audio content and a few video clips. Using deepfake technology, a brand can turn that content into thousands of hyper-targeted ads. Influencers could start ceding their faces and voices to brands, says Lejeune. A computer can take their faces and voices and reproduce them in 16 different languages ​​or poses, and select the most compelling.

Over the past year, brands have moved towards acquiring licenses and rights to use content produced by influencers and use the content as advertisements from their brand channels, rather than paying the fees. influencers to post on their own feeds, says Emily Hall, campaign manager at marketing agency Goat, which has offices in London, New York and Singapore. By acquiring usage rights, brands can choose captions that better match their tone of voice or produce different cuts and edits to the content to be posted on social media that they find most effective, with metrics available. . It gives brands an element of control, says Hall.

Influencer organic content typically costs 5% more, but acquiring usage rights could cost 20-30% more than the original fee. It’s still great value for money, says Hall. Influencers always create content and do the heavy lifting for brands.

Dynamic voiceover and deepfake videos offer enormous potential for marketers in many industries. A 2019 malaria awareness advertisement featuring David Beckham speaking nine languages ​​showed how deepfakes can expand the reach of a public message, receiving 400 million impressions worldwide in two months.

Deepfakes can also support influencers and content creators who are asked to create more live content, but who may not be outstanding artists in all media, explains Dhillon. Hall agrees: you’re removing that risk from a human element, while still retaining a human touch.

Hyper-personalized advertising

Chinese tech companies are more advanced in using deepfakes in marketing. In a white paper from July 2020 On its AI projects, Chinese tech giant Tencent points out that deepfakes aren’t just about rigging and cheating, but highly creative and revolutionary technology. The company urged regulators to avoid clamping down on this burgeoning tech trend. For fashion, Tencent cited how deepfakes can show off outfits on a wider variety of models with different skin tones, heights and weights. When consumers see products as extensions of themselves, they are willing to buy more, pay a higher price, and advocate with their friends, Harvard business review found.

Deepfakes can provide a very quick way of understanding for customers looking at a brand’s new collections, says Matthew Drinkwater, director of the Fashion Innovation Agency (FIA) at London College of Fashion. He started running deepfake experiments in 2019, when Microsoft sponsored a project that allowed his team to insert consumers into ads. It is not a question of form. It’s about giving you a first impression of what something might look like.

This month, Gucci teamed up with software company Niantic to kick off a new collaboration with The North Face in a Pokmon Go game. Imagine if Gucci could take it one step further and send its top 50 customers personalized videos of the game. ‘themselves wearing the new collection, explains Reface AI’s Shvets. In 2020, Reface AI allowed users to virtually try on Gucci clothing as part of a trial with Kering, resulting in a million swaps in a single day.

A demonstration of how the FIA, Superpersonal and Hanger use deepfake technology to capture a user.

© Fashion innovation agency

Retailers can also over-personalize the service using a deep assistant to respond to online inquiries, which matches exact customer demographics and speaks their language. Rather than talking to a faceless robot, shoppers could talk to a real face, which could build confidence, Drinkwater says. All indications are that if you are able to personalize the content, consumers are more likely to engage, so there is a real practical application for the industry to start using it more widely.

Some form of regulation is likely, notes marketer Lejeune. Potential discretion could include labels stating that deepfakes aren’t real people, he says. Dhillon adds that blockchain has potential as a future means of tracking authenticity.

Another hot topic is consumer data protection. Deepfakes supporters claim that the success of existing face swap apps shows consumers are comfortable with sharing their data. In 2019, the AI ​​FaceApp photo editor, which allows users to change their facial expressions, appearance and age, was a viral hit. In 2020, Sway, an AI-powered app that allows users to visualize themselves dancing, became the third most downloaded app in the United States during Super Bowl weekend.

The ethical implications of deepfakes have yet to be fully explored, suggests FIA Drinkwater. But he’s convinced deepfakes are here to stay. The technologies surrounding artificial intelligence and machine learning are already central to how brands can manage different aspects of their business, from their supply chain to marketing and communications. [Adoption] is not so much a backbone but a growing commitment to technology and deep learning.

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