Upgrade your analysis with Logos Recognition
As machine learning and AI have become more and more prominent and intelligent, logo recognition has grown too. With a solid logo recognition software, you can see where your logo is popping up on social media conversation, recognize consumer scenarios from which you can obtain users’ insight and reviews, analyze events, and identify opinion leaders.
How does it work in recognizing the brand in beauty and skincare pics? Let’s take a look.
Would you like to know how a Digital Consumer Intelligence approach can help your Business? Book a Demo to get a free hands-on demonstration of our platform.
If you think about it, our whole life is branded. We are surrounded by logos everywhere, from morning ‘till night our eyes see thousands of different brands and our brains memorize them all.
They store the colors, the brand, or sometimes just the slogan or the advertising jingle. If there ever was a television quiz on logos recognition, we would all be winners. It is impossible not to recognize the bitten apple, the capital M or a puma (to name the most famous).
There are many examples of companies that have made their fortune on choosing a brand of great impact, which knows how to communicate on its own and that knows how to create a lifestyle, leading to the “Brand Affection“.
There are many branches of Brand Communication that keep studying how a brand can, consciously and unconsciously, influence people’s lifestyle and consumer behavior.
In everyday life, we show our photos on social networks with many brands: on our clothes, on our glasses, while we have breakfast or cook, while we are training.
Thanks to the huge success of Instagram, Snapchat or Pinterest, the social media world has become visual-based. Posts on these platforms are mainly visual, and only a few hints are available in the caption of the content.
Identifying what’s in these posts was virtually impossible in the past. Fortunately, that’s where deep learning and AI come to the rescue. These systems can now recognize logos, faces, and objects, in both images and videos.
Thanks to the machine learning and AI tools, it is possible, therefore, to recognize not only the content of images by macro-topics but to recognize the presence of certain brands. A feature that KPI6 cannot absolutely miss and that has integrated with its Digital Consumer Intelligence technologies.
Google Vision Image Recognition
Artificial intelligence and machine learning are transforming the way consumers use certain services and products. Google has made available various development tools capable of enabling new experiences and infinite possibilities.
Google Vision API is a particular type of API that allows developers to analyze the content of images, using machine learning models.
Thanks to this technology, we can have contextualized information on a given image and be able to quickly classify images in various categories and sub-categories.
Google Vision API allows you to identify the content of an image with great precision, detect if there are explicit content, places, artistic monuments, and product logos.
KPI6 has decided to connect Google Vision technologies to its platform to make more performing the classification of online conversations and to provide its customers with enriched insights.
Logos Recognition in beauty care online conversation
The idea was: how many logos can be recognized within a non-branded search? How many brands can the machine recognize without a real mention to them?
For a brand of the Beauty and Skin Care industry, how important is it to know the main brands used by male consumers?
All questions that can be answered via a simple switch-on in our app.
The first step was to listen to all the online conversations about skin and beauty care by men. We created a broad search query on our platform that included references to beard and skincare products, including keywords, hashtags, and phrases generally used by users.
The online conversations generated by listening have been empowered by AI features in the classification phase, in order to have a perfect overview of the brands recognized in users’ photos.
As we can see, logos recognition has managed to identify many brands of male beauty care. First of all, Proraso, which won the most used shaving foam prize. A good shave, however, also involves the use of shaving brushes, which is why the machine has also recognized Omega, famous for its line of shaving accessories.
What about creams? Statistics say that over the years, men are vastly outpacing women in the use of daily, cleansers, or anti-age creams. Nivea is present in the image tag cloud, with its cream from the Nivea Men line.
Many other brands have been recognized by the logo detection: Moschino, Adidas, Philips, Wilkinson.
Through this analysis, it was not only possible to understand which brands are most used in this sector by men or the most “unconsciously photographed” brands, but it was also possible to discover the presence of brands outside the beauty industry, such as Subway or Fortnite (so that you can take advantage of useful insights for any co-branding activities).
Logos recognition has, therefore, become a very important feature in conversation monitoring actions and in undercover consumer habits and behaviors. It is possible to use this technology to understand which is the brand most associated with a particular product, a particular moment or above all it is interesting to find out other brands (of your industry or not) that are used combined to your, and this can be the starting point to create co-branding activities of product, events and communication actions.
Would you like to know how a Digital Consumer Intelligence approach can help your Business?
Book a Demo to get a free hands-on demonstration of our platform.