The social media landscape is becoming increasingly visual. Gone are the days when users on platforms such as Facebook and Twitter had to rely on expressing themselves with text-based posts. Now, visuals from GIFs and emojis to selfies and videos dominate these platforms and others. And with the rising popularity of image-based platforms such as Instagram and Tik Tok, image-based content has become the primary mode of expression for many users. Consumer research has advanced to keep up with this trend, utilizing image analysis to understand how consumers express themselves in this increasingly visual social media landscape.
What Is Image Analysis?
Image Analysis involves utilizing AI to analyze images and discern meaning, particularly emotional meaning. In consumer research applications, the images analyzed could include emojis, GIFs and memes, and photographs and videos featured in social media posts or other consumer-generated online content.
The AI performing image analysis can process large amounts of visual data posted on online platforms and identify emotional trends across this content. For example, NetBase Quid AI’s image analysis techniques include analyzing the emotional expression of faces and identifying how facial expressions of emotion relate to other visual content in the image analyzed, including logos and other brand-relevant images.
Image Analysis Advances Consumer Research
When used as a social listening tool, image analysis can provide brands with a variety of valuable information about how consumers relate to their brand and how they present brand-relevant visual content online.
Even if a brand is not tagged in a post, image analysis can identify the presence of the brand’s logo in an image. Positive posts that tend to feature the brand’s logo can provide inspiration for marketing campaigns and identify relevant links between the brand’s products and consumers’ activities and interests. Using image analysis, brands learn about what their customers are posting about while using their products. Customers may post about the role of a particular brand of coffee for starting their workday, or a particular fast-food item for satisfying late night cravings. These customers may not mention the brand by name in the post or tag the brand, but image analysis can recognize the presence of a logo and make connections about how customers tend to use and post about these products.
Image analysis can also work in conjunction with text analysis to analyze posts on platforms such as Instagram, TikTok, and YouTube that include both images and text descriptions. Like image analysis, text analysis utilizes AI to process large amounts of data and assess emotional content. Using text analysis, posts can be identified as positive or negative based on the text of their description. This analysis can then be combined with image analysis to discern which types of brand-relevant images, perhaps a particular product or logo, are featured in more positive posts.
Another beneficial application of image analysis involves uncovering relationships with other brands that can result in productive partnerships. Image analysis identifies trends in the contexts in which a brand’s product is featured, and part of this contextual information involves the presence of other products. For example, a particular food item might often be featured in posts with a particular kind of beverage, or posts at a particular kind of event such as a concert or sporting event.
Successfully Navigating a Visual Landscape
Successful brands understand that consumers are increasingly displaying their brand loyalties via image-based posts. These brands use image analysis to better understand the visual context underlying how their existing customers relate their values to the brand. They also use image analysis to identify market gaps, consumers who share their customers values and visual aesthetic but may not know about their brand. The applications of image analysis continue to evolve, and it is clear that the technology is here to stay as a valuable tool for consumer research in today’s image-based online environment.
