How Trend Analysis Can Help You Plan Your Next Collection

Data-Driven Beauty: How Trend Analysis Can Help You Plan Your Next Collection


The beauty industry has come a long way from the days of roll-on glitter and tanning pills. In today’s digital age, data science is revolutionizing the business world, and the beauty industry is no exception. Innovative brands have begun to harness the power of big data, machine learning, and artificial intelligence to create personalized beauty experiences for their customers.

From individualized skincare routines to trend-inspired makeup palettes and predicting trends, data analytics is changing the face of the cosmetic industry. As more beauty businesses leverage big data, they can provide just the right cosmetic and skincare products that both consumers and retailers are looking for.

For beauty brands looking to expand into wholesale retail, it is critical to understand the requirements of their audience, best practices for using analytics to optimize marketing efforts across all platforms, and using meaningful engagement tactics backed by consumer data to develop long-term connections with devoted customers.


Data-Driven Beauty: How Trend Analysis Can Help Plan Your Next Collection

What is data analytics? 

What exactly is data analytics, and how can brands use it in their business operations? Data analytics, often referred to as trend analytics in the context of the fashion and beauty industry, is the process of collecting, processing, and analyzing data to identify patterns, trends, and insights that can inform business decisions.

In short, data-driven beauty uses data to improve cosmetics and personal care products, taking into account factors such as skin type, sensitivity, and genetics to create bespoke products that cater to individual needs. Data analytics can be used to forecast consumer preferences, design collections, optimize production, and improve marketing strategies.

Creating tailored skincare

Combining genetics with skincare is one of the most revolutionary advances in the beauty field. Gone are the days of one-size-fits-all beauty products. With the advancements in data science, brands can now offer personalized beauty experiences tailored to individual needs and preferences. Brands can achieve this by assessing their customers’ genetic profiles, skin issues, and lifestyle factors to develop customized skincare routines. This level of personalization is made possible through the analysis of genetic data, which provides valuable insights into an individual’s skin characteristics, sensitivities, and predispositions.

Take, for example, GenoBeauty, a Polish skincare brand. GenoBeauty analyzes the genetics of its clients, revealing potential skin issues like predisposition to early wrinkling, pigmentation, or skin sensitivity. With this personalized information, GenoBeauty curates a skincare regimen designed specifically for the individual’s genetic makeup.

It’s an approach that Connect wholesale brand Skinergy Beauty, a Latinx-owned skincare company that is specially formulated for people of color, has also adopted. “I couldn’t find a highly effective product in the US market that did not contain hydroquinone to lighten hyperpigmentation caused by hormonal acne and sun damage,” says founder Priscilla Jiminian. “As a woman of color, a Latina, I needed products to cater to my unique skin needs.” 

Because Latinos are susceptible to having melasma and dark spots, Jiminian created Skinergy’s Dark Spot Correcting Cream, which targets uneven skin tones. It’s filled with potent ingredients, such as ferulic acid, that are proven to protect skin from discoloration.

A simple way of gathering the required information from consumers is to create a quiz or conduct a survey that gets users to share potential skin issues they may have, such as predisposition to early wrinkling, pigmentation, or skin sensitivity. With this information, you can create a range of skincare products designed specifically for the genetic makeup of your clients.


Predicting beauty trends in real-time

Beyond personalized products, data analytics aids in capturing the pulse of global beauty trends. Traditionally, brands relied on seasonal fashion weeks and industry predictions to guide product launches. Today, using machine learning and big data, they can analyze social media chatter, online searches, and even purchasing patterns to predict the next big trend.

Google Trends is a useful tool to get the pulse on what people are searching for in real time. The data can be used to measure search interest in a particular topic, in a particular place, and at a particular time. By leveraging real-time data, you can predict trends with remarkable accuracy, using them to develop products that resonate with consumers or retailers are looking for in the wholesale marketplace.

This data-driven approach gives brands a competitive edge, enabling them to anticipate market demands and deliver innovative products that capture the zeitgeist. By combining data analytics with creative expertise, brands can create products that reflect the latest trends and cater to the ever-evolving preferences of consumers.

A case in point is Spate, a machine intelligence solution for finding the next big consumer trend. Spate’s dashboard examines data from more than 20 billion search signals and some 40 million beauty-related TikTok videos to address pressing health and beauty sector concerns.

Spate uses AI-powered trend-spotting and predictive modeling to establish whether or not a particular fad will endure. The platform also employs market assessments to determine the level of competition, developing brands in the sector, and brand white-space potential. Moreover, Spate selects top ingredients, claims, and concerns to highlight in product messaging and SEO based on consumer priorities.

Data-Driven Beauty: How Trend Analysis Can Help Plan Your Next Collection

AI, the virtual beauty assistant

Although many of us long for human interaction, the beauty industry has not been immune to the effects of artificial intelligence. Using machine learning, several cosmetics companies now provide online consultations and try-ons. These virtual tools use augmented reality and deep learning to analyze your face, skin tone, and lighting conditions to suggest makeup shades or hairstyles.

Take Perfect Corp., a major provider of SaaS artificial intelligence and augmented reality beauty and fashion tech business solutions committed to revolutionizing the consumer purchasing experience through seamless and omnichannel interactions. The company provides results-driven, inclusive, interactive, and long-term solutions readily integrated into a brand’s website and applications and numerous social media channels such as Instagram, Snapchat, and YouTube, among others.

Furthermore, AI-powered chatbots support customers in real-time, making product recommendations based on previous purchases, browsing history, and product reviews. Predictive analytics enables brands to forecast product demands, ensuring that bestsellers are always in stock.

A personalized approach

Data-driven beauty is something that global brand L’Oréal has wholeheartedly embraced. The company values shifted from “beauty for all” to “beauty for each”. The objective is to supply individualized, all-embracing beauty remedies for people’s unique needs.

L’Oréal’s strategy in this area is founded on meticulous consumer attention and a deep respect for their diverse demands, lifestyles, preferences, and traditions. The group also benefits from its portfolio of personalized products and services powered by artificial intelligence, data, and beauty tech.

Sephora is another company that has embraced data-driven beauty. The company uses machine learning algorithms to analyze client data and deliver personalized recommendations that cover skincare, cosmetics, and hair care tips. By using machine learning, other brands can also provide a highly customized experience for each consumer, leading to a more loyal client base.

The road ahead

As data science and beauty continue to intersect, the possibilities seem limitless. Brands, even those outside the beauty industry, are only scratching the surface of what’s achievable when deep insights meet creativity. The ultimate result is goods that are more tailored to the individual, more efficient, and ahead of the curve.

The beauty business has always been a leader in technological advancement. Now, with the help of data analytics, artificial intelligence, and machine learning, it promises to become even more avant-garde, intuitive, and personalized. In the world of data-driven beauty, the future looks radiant indeed.



Words by Faith Katunga
Lead image courtesy of Spate

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