The “visual Web” is just about past its prime as a buzzword at this point. In general, the phrase is used in a couple of ways. First, it describes the general shift of Web design from being primarily text-oriented to being primarily image-oriented. High-bandwidth Internet connections, larger and higher resolution screens on all devices, and the rise of tablets have helped drive this trend. Second, it also describes the rise of images as a way people communicate. I won’t repeat the stats on the growth of Instagram, Tumblr, Vine, Snapchat, et. al. here – or review the displacement of punctuation-based emoticons by complex and infinitely varied emoji 🙂 – but suffice it to say the rise of smartphones has made it arguably faster and easier for people to share images than to type out words.
Brands are already becoming adept at harnessing this trend. A Gillette Nordic campaign from last year that invited Swedish women to upload pictures of awful winter weather to Instagram is a great example (and won a 2013 IAB MIXX Award).
While this is a fascinating shift in how we as humans communicate, all of it so far has the feel of “Visual Web 1.0” to me. I’m unilaterally declaring that Visual Web 2.0 begins when images shift from being a unit of communication to a user interface – when image recognition becomes a significant way that people query the internet for information, services, or entertainment.
Of course, image recognition is not new. Google Goggles (not to be confused with Google Glass) has been around since 2009, and is a great, pioneering example of image recognition as a UI. But to date, image recognition has been niche, relegated to relatively obscure apps (or obscure corners of popular apps), or used only for specific kinds of images (I’m looking at you, QR code/barcode scanners).
Where can image recognition go? The possibilities feel endless – and can definitely improve on conventional user interfaces. For example, the first time I deposited a check via a smartphone photo was one of those amazing moments where the technology felt like magic. As I was talking with a colleague about my Visual Web 2.0 concept this week, I joked that the transition could be summarized as going from oversharing pictures of our restaurant meals to having an app that could estimate the calories in the photo. Inevitably, a minimal amount of research revealed that someone is already working on this.
Like any new user interface development, image recognition needs two things to really take off: it needs to be easy – easier than typing something into a search box or talking to a virtual assistant – and it needs people to be comfortable and familiar with doing it. On this front, what Amazon’s new Fire smartphone does with “Firefly” (the image recognition technology available at the press of a button) is going to be worth watching. It’ll make more people aware that image recognition exists, that it can be useful, and likely will get owners of other smartphones wondering whether their devices can do the same.
What should marketers be thinking about Visual Web 2.0? It’s still early. As a UI shift, image recognition will enable some entirely new kinds of apps or services, but mostly it’ll make existing tasks and activities faster and easier – so many of the advertising opportunities around these applications already exist. Companies thinking about building smartphone apps for marketing purposes should consider the possibilities created by the camera and image recognition – creative uses of the technology will garner consumer and media attention. And of course everyone thinking about Visual Web 2.0 needs to look at privacy very carefully, too. It’s one thing when consumer images are shared via public social media channels like Instagram, and quite another when deployed for automated image recognition. Clear disclosure on who sees such images, when and where (if anywhere) they are stored, and for how long is going to be important.
Visual Web 2.0 could be a few months away, or it may still be a few years off. But just as voice is becoming a common way we communicate with the Internet, images inevitably will as well. As image recognition gets more seamless and our devices start keeping both an eye and an ear out for us, they will only get better, and more indispensable, as the remote controls of our everyday lives.
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