Image Analysis Drives Consumer Research as Social Media Becomes Increasingly Visual

AI continues to improve its ability to recognize and analyze images. We see the applications of digital image analysis all around us, from spotting cancer to detecting home intruders. As the technology improves, viable applications have emerged throughout science and industry. One such application is consumer research; brands are now leveraging powerful AI to recognize and analyze images on social media and other online platforms. Using image analysis, brands can recognize valuable consumer insights and generate actionable strategies grounded in the ability to see how their customers engage with their brand in an increasingly image-based online environment.

What Is Image Analysis?

Image analysis involves extracting data from images using digital image processing techniques. This can involve anything from facial recognition to recognizing the presence of a particular kind of object, such as a coffee cup.

When it comes to consumer research, the primary images analyzed include photographs, videos, GIFs, emojis, and brand logos. The relevant data could be anything from an appearance of a brand’s logo in a positive post that didn’t tag the brand to an excited facial expression in a post in which the brand is mentioned. Determining where and in what context brand-relevant images appear in online content can help a company recognize marketing opportunities and understand how consumers feel about its brand.

Image analysis is a social listening tool, utilizing AI to recognize and analyze image-based data from consumers’ online posts on platforms such as Instagram, Facebook, and Twitter. Powerful AI enables brands to process large amounts of visual content from these platforms that would be impossible to analyze manually, resulting in the recognition of brand-relevant trends.

A Visual Conversation

As platforms such as Instagram and Tik Tok have gained popularity, the online conversation has become increasingly image based. Image analysis is ideally suited to this visual online environment, identifying consumer insights that text analysis alone would overlook.

Logo recognition allows brands to analyze what kind of posts feature their products, even if the product is not mentioned in the post. More powerful image analysis tools such as NetBase Quid AI use sentiment analysis to go beyond mere logo recognition and analyze the emotional content of posts that feature a brand’s logo. This is valuable information, helping brands understand contexts in which images of their products appear in a positive or negative light so they can target the appropriate contexts when developing marketing strategies.

Image analysis extends beyond logo recognition. Sentiment analysis enables brands to analyze facial expressions and recognize positive or negative sentiment in brand-relevant posts. NetBase Quid AI users can aggregate this information to identify feel-alike audience segments and understand other connections that their customers share. For example, fans of a certain beverage brand might tend to enjoy a particular kind of concert. The brand could then build marketing campaigns around similar concerts in the future. Image analysis is a valuable tool for identifying partnership and co-branding opportunities.

Brands can also use image analysis to determine how consumers feel about their competitors. If groups of users tend to post positive image-based content that mentions a competitor or that features a competitor’s logo, brands can identify connections among these users and posts and create targeted campaigns to address these potential customers.

What’s Next for Image Analysis in Consumer Research?

While image analysis has made tremendous strides in recent years and is currently capable of gathering and analyzing a wide variety of valuable data, the technology is still improving. As AI continues to learn to see, image analysis will only get better at recognizing the visual context in which brands and products appear online.

Image analysis is constantly improving in its ability to recognize places, people, activities, and products, empowering brands with an innovative social listening tool and a fine-grained understanding of their brand’s role in an increasingly visual online conversation.