Image Recognition Is the New Mobile Frontier

Jillian MacNulty Picture

by Jillian MacNulty | Last Updated: Mar 18, 2019

Did you catch what Lush just did at SXSW? Attendees that stopped by the beauty brand’s concept shop in Austin could “scan” bath bombs via the Lush mobile app, and unlock exclusive, “digital packaging” content like product names, ingredients, prices, and videos. The tech powering this “wow-worthy” moment? Image recognition! While the use cases for image recognition are endless (more on that later), what Lush is doing with the technology is really telling to where the market for consumer brands is heading. But first, let’s start with some basics. What Is Image Recognition? Before we dive into how it’s being used, it’s important to understand how it works–at least on a basic level. Image recognition (also called computer vision) is a subset of AI that allows devices to interpret images and “react”. This may be as simple as the ability to recognize a color or a pattern, and can be as complex as determining whether or not auto damage was staged or accidental–a lot of range there, and a lot of potential! The technology is on the rise, with 27 percent of all searches across 10 major web properties being for images, and the market predicted to grow to $26.2 billion by 2025. The Big Picture Since image recognition powers technologies like visual search, AR, and facial recognition, that means the potential use cases are virtually endless. We’ve got the obvious ones–like Apple using facial recognition technology in their iPhone X models and beyond, and Google allowing you to search with images instead of text queries–but if we look past our everyday tasks, we’ll see that image recognition tech is a game changer for some big-picture organizations. For example, the manufacturing industry uses it to detect defects not visible to the human eye, and the U.S. treasury uses it to spot counterfeit cash. Computer Vision Visionaries Ok, so image recognition is making a substantial difference for some hot button issues across many industries, but there are also some great consumer-facing use cases for image recognition that brands are beginning to implement. Like Pinterest, for example. They added a visual search feature (not unlike Google’s) to their app, but they didn’t stop there. They let users upload their own photos and get suggestions for outfit pairings with their “Lens Your Look” tool. Another favorite? 19 Crimes Wine. They use image recognition tech within their app to launch users into an AR experience where their wine bottle labels come to life. What’s Next for Image Recognition? Most consumer-facing use cases for image recognition have one thing in common: they use mobile as the activation point. I predict that consumer facing brands will look more toward image recognition tech as a way to launch mobile content (a la 19 Crimes and Lush), and continue to optimize their products and packaging to support image-based campaigns and strategies. But with great technology comes great responsibility–we as marketers have the responsibility to ensure that a wow-worthy image recognition experience is part of an equally as compelling mobile strategy.

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