September 24, 2022

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herner-aerztenetz

With Image Analysis, Brands Turn Their Attention to Consumers’ Visual Storytelling

Social media is a visual medium. From captioning Instagram photos with emojis to tweeting GIFs while watching a live event, social media users communicate in a highly visual language. Now, brands are harnessing image analysis to better understand this language. This powerful social listening tool is helping brands connect with the visual storytelling driving online conversations.

What Is Image Analysis?

Image analysis involves gathering data from images such as social media posts, memes, and brand logos, and determining how this data should impact business and marketing strategies.

As the conversation around products and brands has moved online and become dominated by images, image analysis has emerged as an invaluable tool for understanding how consumers relate to brands.

Image analysis is part of a broader class of social listening tools that use AI to collect, aggregate, and analyze large amounts of data from consumers’ online posts. This includes data from social media platforms such as Twitter, Instagram, and Facebook. While social listening often involves analyzing the text of a post, focusing only on text means you are ignoring a significant amount of content that consumers use to express themselves.

Imagine an Instagram post of a happy customer enjoying their favorite brand of ice cream, captioned with heart emojis. Without image analysis to analyze this type of post, the ice cream brand would miss out on a valuable opportunity to identify both how customers are enjoying their products and where they are sharing that information.

Sentiment Analysis Captures the Emotion in an Image

Sentiment analysis involves using AI to identify the underlying opinions and emotional reactions in either images or text. It is the most common application of image analysis for the purpose of consumer research.

While social listening might simply involve tracking where and when a logo or product appears in a picture and is posted online, it is more valuable to understand the emotional context of images that are relevant to your brand.

For example, NetBase Quid, a leader in sentiment analysis, utilizes AI that can identify whether images and emojis express a positive or negative tone, and even whether they are expressing specific emotions such as excitement or disgust. This tool allows you to go beyond simply tracking frequency and location of brand-relevant images to identify audience targets based on their opinions about your brand.

Once this data is captured, it can be aggregated to identify audience segments to target in future marketing campaigns. Maybe image analysis indicates consumers tend to take positive pictures that include your brand logo at a particular kind of event such as a football game or a concert, and you can focus more social media attention on connecting your brand to similar events in the future. 

You can also use image analysis to identify consumers’ sentiments towards competitors. Identifying groups of users that tend to post positive images of a competitor’s product but not your own can identify gaps in your strategy that are helpful to target as you compete for the lion’s share of an audience.

Most photos that feature a brand’s logo will not mention or tag the brand in the description, but even these photos clarify consumer behavior. When a consumer takes the time to include an image of your product or logo as part of their visual story on social media, they are signaling that they are the kind of consumer that cares about your brand.

With image analysis, brands can pick up these signals and identify their emotional content, even when no text is present.

Advancements in Image Analysis and Consumer Research

Image recognition is an active area of AI research and it continues to improve. Improvements in AI’s ability to recognize and sort images, coupled with the increasing ability to handle large data sets, should continue to drive innovative consumer research applications for image analysis.

For example, one potential application is creating shoppable images on social media platforms, so users can buy products simply by clicking on an image that connects with positive brand associations.

Ultimately, the true potential of image analysis for consumer research lies in its ability to help companies better understand the stories that their customers are connecting to their brands via social media. As these stories continue to emphasize images, companies that utilize image analysis will be better equipped to understand and serve their customers.