August 14, 2023
| 7 mins read
The race for generative AI-enabled innovation is intensifying across all sectors, from travel to healthcare. Beauty is no exception – an industry already spearheading innovation, where virtual shopping tools and “beauty tech” are changing customer experience from the inside out.
The number speaks for itself: AI usage in beauty and cosmetics will surge by around 20% CAGR through 2031.
From codesigning to accelerating content development, generative AI offers new grounds for creativity. The AI subset uses algorithms to convert “unstructured” data - raw images, text, and videos - into new forms of content, including 3D designs, simulations, and lifelike virtual models for video campaigns.
This article elaborates on some solid use cases of generative AI in the beauty industry.
The beauty industry is tremendously visual. Hairstyles, makeup looks, and packaging designs - all these demand strong aesthetics to attract customers.
Product innovation starts with an idea for a new cosmetic product or a white space for a product to fill. Generative AI helps creative designers speed up either of these processes. It quickly collects massive datasets by analyzing sentiments from online videos or model trends from numerous customer data sources.
Creative heads and their teams must enter desired details, including color palettes, shapes, and patterns, into a generative AI-powered platform. Then, the platform automatically suggests several cosmetic designs for previews as illustrations or photo-realistic depictions.
Finally, creative teams can play with a wide variety of looks and styles before launching the cosmetic product in real life. Additionally, they can create new offerings based on these outputs, putting the brand’s signature touch on each design.
The more detailed the prompts, the better the results. Furthermore, generative beauty AI tools will have more insights to provide tailored product ideas as brands increasingly interact with them about their businesses.
For beauty brands, especially those running in e-commerce, generative AI is considerably beneficial when it comes to the more demanding tasks of selling such great cosmetic products. In other words, writing product descriptions.
After working for long hours ensuring proper packaging, testing, and functioning of a product, now comes the time to advertise it as such on the website.
This process takes significant time, particularly when shoppers are buying hundreds of cosmetic products at the moment. Whether for a head start or making minor changes here and there, the text generation abilities of generative beauty AI tools make them essential to crafting on-site page copy.
Writing content for a single web page requires hours of carefully curated word choices. Fortunately, generative AI tools provide beauty brands with a workable draft in seconds, saving tons of hours a month and boosting non-branded organic traffic.
That said, cosmetic makers need to follow the standard SEO best practices for the rest of their websites’ pages.
Generative beauty AI tools infuse existing AR try-on solutions with advanced capabilities to take virtual shopping experiences to new heights. This powerful combination builds highly detailed and true-to-life simulations of cosmetic products by recreating parts of the neck, face, ears, and head.
All users have to do is upload their images and let generative AI do its job. The algorithms apply (virtual) lipstick shapes, eyeshadows, and multiple hairstyles, to their photos. Users have the creative liberty to mix, match, and discover the perfect look without mess.
Not only this, but generative AI algorithms also consider hair color, face shape, skin tone, and body proportions when adapting simulations to each user’s unique characteristics. The result is a more personalized and interactive shopping experience.
Visual search engines let users upload images of hairstyles, makeup looks, or beauty products they find appealing. The generative AI tool analyses these images and lays out similar products matching their preferences. For instance, a user who loves a particular dressing style can discover makeup looks that complement their fashion sense.
Customers often search for affordable alternatives or "dupes" of high-end beauty products. Generative AI-powered engines help users find similar products that match the desired product's texture, colour, and finish.
Further, customers can look for makeup looks and hairstyles inspired by their favourite celebrities, influencers, or iconic characters. Visual search engines, driven by generative AI, provide users with tutorials, products, and step-by-step guides to recreate those looks.
Personalisation is a huge selling point for beauty companies. Generative beauty AI tools build virtual beauty assistants that offer customers personalized tutorials, advice, and product recommendations.
Similar to AR try-on solutions, shoppers need to upload their skin images for diagnosis. Generative AI algorithms then evaluate these images to examine the skin’s condition, identify specific concerns, and recommend tailored skincare routines. In addition, they predict how their skins change over time and prescribe the right cosmetic products for users accordingly.
These simulations are derived from the cosmetic product’s medical claims and data from tests about its effectiveness, alongside environmental factors, including the impacts of pollution and the sun on the skin.
For beauty brands that bake these insights into their strategies and preserve them, generative AI consistently learns and adapts its recommendations based on evolving trends and customer feedback.
The rising prevalence of AI in the beauty industry translates into increasing demand for more eye-pleasing, engaging content.
Thankfully, generative AI helps marketers brainstorm campaign strategies, set timelines for deliverables, and ideate product campaign content – do it fast. It identifies patterns within complex and diverse datasets. By analyzing large data chunks, generative AI algorithms detect emerging trends in makeup styles, skincare routines, and colour preferences. These insights highlight customers’ sentiments and opinions, helping beauty brands predict upcoming trends and tweak their marketing campaigns accordingly.
Moreover, generative AI performs sentiment analysis on textual data, such as reviews, comments, and social media posts. That way, beauty brands can understand how users feel about specific products, trends, or experiences. Evaluating these sentiments enables brands to gauge the popularity of certain styles and identify potential areas for improvement.
Prompting generative AI-powered tools to create content for social media platforms and other digital forums saves brands time and costs associated with pumping out online content.
Generative AI is ubiquitous, and beauty should not lag. It drives levels of innovation, transparency, and personalisation in the beauty industry. From pattern designs to skincare simulations, technology is transforming how people engage with beauty.
True, generative AI in the beauty industry is in its early days and is still brimming with potential bugs and kinks. Despite that, the cutting-edge tool can improve rapidly and become a turning point in multiple business aspects.
By combining the power of data and algorithms, generative AI will likely change how cosmetic products are developed, experienced, and used. While it will not replace human creativity anytime soon, it is fast becoming a critical tool for efficiency, speed, and productivity.
Brands that embrace generative beauty AI will move ahead.
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