We all know how marketing in the twentieth century included surveys and looking for ad placements in primetime shows. The present age of technology has provided companies with huge amount of data and equally genius ideas to analyze it.

However, in terms of understanding visual data, a lot of companies have been unsuccessful in keeping up with it. The marketing industry is still trying to get back in the big picture and handle big visual content. They are trying to handle visual data with text based tools but that is just causing more complications and wasting time.  Computer vision on the other hand lets brands categorize and give a whole new meaning to visual data. It helps with speech recognition, facial recognition, and collects information from every frame. This can help the brands to put ad campaigns more targeted towards the particular user.

We all know how marketing in the twentieth century included surveys and looking for ad placements in primetime shows. The present age of technology has provided companies with huge amount of data and equally genius ideas to analyze it. However, in terms of understanding visual data, a lot of companies have been unsuccessful in keeping up with it. The marketing industry is still trying to get back in the big picture and handle big visual content. They are trying to handle visual data with text based tools but that is just causing more complications and wasting time.  Computer vision on the other hand lets brands categorize and give a whole new meaning to visual data. It helps with speech recognition, facial recognition, and collects information from every frame. This can help the brands to put ad campaigns more targeted towards the particular user.

User-generated content with computer vision is another way that affects how the brand attracts its audience. Users of today have several social media platforms including Snapchat, WhatsApp, and Facebook and majority of them share their videos, pictures and go through pages they like. They also go through YouTube, watching videos that they like and sharing them on their social media accounts. The brands can use this to gather user insight in order to derive personal experiences, tastes and characteristics of the consumer. For example, GumGum, a VI software scans visual content from social media and provides the brands’ marketing teams to take action accordingly. The firm worked with L’Oréal to target women with colored hair with customized ads. This can help the brand to offer specific products and services to the right audience, automatically improving their own performance.

Another way the brands can work on their performance is by playing synchronized ads. Computer vision now takes care of when an ad is playing on the television. This offers tailored actions and calls in sync with paid commercials or television content. This also gives them the brands a chance to play their ad when the competitor’s ad is playing on TV.  Furthermore, computer vision also gives the brands a chance to collect emotional triggers and reactions of the consumer when they see a certain ad. M&C Saatchi, a company in London, used this technology to analyze facial expressions to create artificial intelligence posters.

Brands when paired with technology can offer a far better performance. Their collection of insights through computer vision is a huge step forward in marketing as well as building brand image. Computer vision is a guide to all brands and a way to stand out from their competitors.