Implicit vs. Explicit Visual Mentions

Using image recognition to go beyond surface personas

In 2016, researchers at the University of Pittsburgh School of Medicine conducted a study that linked heavy Facebook and social media usage to depression. More specifically, the study found that “highly idealized representations of peers on social media elicits feelings of envy and the distorted belief that others lead happier, more successful lives.”

It’s no secret that on social media people put forth a gilded version of themselves for the world to see. Consequently, this can create a less than complete picture of reality and other social media users are not the only ones at risk of being misled. Brands, too, can come to the wrong conclusions if they’re simply taking consumer posts at face value. Brands that really want to understand pertinent conversations or target likely customers must go past the surface and dive into the subtext and implications underlying many social posts.

visual mentions image 1Advanced image analytics can help brands understand the whole story behind consumers’ posts — even if consumers don’t know they’re saying it.

This is where image analytics can really come in handy for brands. As an example, let’s look at a tweet from a consumer showing off her new handbag.

Neiman Marcus may be interested in identifying and targeting affluent social media users and do so by looking for explicit text mentions of luxury brands like Louis Vuitton in tweets. However, that tweet only tells part of the story…the part that the individual explicitly wants us to know (e.g. the gilded version.).

The main takeaway here is that images and image analysis can provide a better way to understand customers/uncover insights that go beyond the gilded versions that they are explicitly communicating on social.

For more explanation on the value of image analysis, download our Fundamentals of Image Analytics Guide.

Fundamentals of Image Analytics

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