The first image recognition system for Influencer Marketing

In our mind, eyesight appears to be something simple. It is easy for us to understand whether the image we are looking at is actually an animal, a person or a landscape at sunset.

However, what may seem natural to us, might be an extremely complex process for machines. Yet, in recent years there has been an unprecedented development thanks to progress in the field of machine learning and in particular, with regard to deep convolutional networks, which are now able to match and – in some cases – outdo human performance. 

Several studies have shown considerable progress in visual recognition in machines through validation of their work on ImageNet. Research after research and model after model, increasingly advanced architectures have been developed, allowing us to obtain extremely accurate image recognition.

GAIIA’s eyes

Since we already have a well-structured convolutional network, our task is to continue training it by focusing on the aspect that interests us the most, that is the Influencer Marketing industry. What does this mean? A “generic” image recognition system has the potential for a higher risk of error than a highly specialised one. What we are trying to do at Buzzoole is to develop vertical models for specific sectors, such as food, fashion, travel, etc. In this way, we will not only be able to meet the needs of the Brands that will choose to work with us, more effectively but also to pick profiles with maximum affinity.

We are able to do this thanks to our very large database of Influencers and to an even greater number of images that we have processed in anonymous form in order to improve our image categorisation system. Another key aspect of our technology is that we can retrieve images as well as the context in which they are produced. This huge amount of information collected from various social channels, combined with a categorisation process through NLP (Natural Language Processing), helps us gain a deeper understanding of our users.

Image recognition for visual communication

Why is image recognition essential in Influencer Marketing? Social platforms based on purely visual content, such as Instagram, are now increasingly becoming an integral part of marketing strategies for Brands, which is why visual communication cannot be underestimated. Hence, it is important to have a means of interpreting and understanding these images and their context. For example, a group of people could represent a group of friends or a football team on the pitch. A well-trained image recognition system can recognise all the elements in the image and contextualise them in order to extract the right meaning.

This allows:

  • for Influencers, an even more detailed profile analysis that integrates with data related to topics of influence and the performance of the various related channels;
  • for Brands, the opportunity to rely on the first image recognition system specifically designed for Influencer Marketing and thus, capable of identifying sector specialists with maximum affinity.

example of image recognition system

GAIIA: Artificial Intelligence at the disposal of users

All this is part of GAIIA, the artificial intelligence technology developed by Buzzoole, which combines image recognition, Natural Language Understanding and Big Data, making Buzzoole the first Influencer Marketing technology platform on the market. GAIIA is the result of the work I have been carrying out daily together with the Research & Development team and that I somewhat consider to be our “creature”. In fact, GAIIA, like a child, is nourished and trained with new information so that it can grow, thus helping Brands and Influencers, with the aim to achieve more productive cooperation for all parties involved. 

If you would like to know how our technology can help your Brand, please contact us at brands@buzzoole.com.

This post is also available in: Italian

gennaro varriale

Gennaro is Buzzoole’s CTO and co-founder. He started developing at the age of 8 and since then has never stopped exploring the world of programming. In 2013 he developed Pingram.me (now pinhere.me) in just 6 hours. The app went viral in no time and quickly appeared on popular review sites. Gennaro is not only passionate about Data Science, Machine Learning, and Big Data, he also loves photography and creative copywriting. Get in touch with him on Twitter or Facebook.

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