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Seeing the future: How advertisers can prepare for the visual revolution in 2019

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By Peter Wallace, commercial director at GumGum UK. 

When Twitter exploded onto the scene a decade ago to roaring success, it was at a time when text-based communication was all the rage. But now visual content is taking centre stage, with younger consumers particularly preferring the likes of Instagram, YouTube, Snapchat and Pinterest over Twitter and Facebook.

In tandem with this shift in focus from consumers, the digital landscape is also evolving, with big tech companies making major changes to the way they do things. Google, for example, just announced that it's making its search tools more visual so that people can navigate results as easily as they can on visual social networks.

This trend toward visual communication is only set to continue into 2019. That means the race is on for today’s marketers to learn how to navigate new territory and continue delivering seamless experiences to consumers across all their devices, while also remaining protected against online risks.

Taking this into consideration, it’s no surprise that the computer vision and hardware market is expected to reach US$48.6 bn by 2022. But what exactly does artificial intelligence (AI)-powered computer vision do, and why will it be so central to the marketing toolkits of 2019?

Unlocking visual data

Put simply, computer vision describes the ability of a machine to receive and analyse visual data on its own and then make decisions about it.

We’re already seeing computer vision help consumers organise and access their photo collections without needing to add tags in, say, Google Photos. But within the marketing world, this technology has the power to deliver highly visible advertising campaigns and rich insights on brands and agencies.

That’s because the vast quantity of shared, saved and viewed images across the web opens up the possibility of serving image-based ads that are contextually relevant to the content people are viewing and sharing. The visual branch of AI plays a key role here in automating the analysis of this information treasure trove to provide contextually intelligent solutions.

AI can spot trends, identify patterns and therefore personalise content at a faster and more accurate level than cookie data could ever achieve. With AI, marketers can seamlessly bridge the gap between engaged, receptive audiences and brand messaging. This could change how marketers approach consumers and, in turn, prove themselves worthier of consumer attention.

The prospect of automated image recognition is also particularly exciting when considering where it can feed into creative work. Augmented and virtual reality campaigns embedded directly into content that the user is already paying attention to, for example, can boost emotional impact and encourage positive brand affinity simultaneously.

A safer place for brands

But beyond its obvious benefits for boosting over marketing efficiency, as we move into 2019, we’ll also see computer vision take a more prominent role in brands’ online safety strategies.

Safeguarding against damaging content online is an ongoing battle for our industry. Mars and Spotify have both fallen foul to the perils of ad-misplacement this year, and our own research on the topic revealed that 75% of brands have experienced at least one unsafe brand exposure in the past 12 months.

And unfortunately, with the internet shifting toward a much more visual future, this issue is only going to become more complex. A simple blacklist is no longer going to be sufficient for combating against threatening videos and images – in fact, relying too much on these techniques may put brands at serious risk, as there could be potentially unsafe visual content flying under the radar that’s not being identified.

That’s why, in 2019 it will be imperative that brands prioritise visual content when building their brand safety plans, which is where AI-powered computer vision tools come into their own.

That’s because computer vision can not only identify damaging visual content before ads are placed, but it can act on risks in real-time and ensure any threats are immediately averted. It can even work in tandem with text-based techniques to add an additional layer to the overall brand safety strategy.

Agility is pivotal

Digital advertising is still a relatively new branch of marketing and one that is used to continual change and development. So if any industry is prepared to tackle such a drastic over-haul in consumer behaviour, it’s this one.

Already computer vision is making head waves in the online advertising space. But with digital bleeding into other media channels as well, such as TV and OOH, there will be increased need and application of computer vision across traditional media channels.

As we enter the new year, the priority then for advertisers should be to get to grips with these tools so they can continue delivering relevant content to users through the channels and formats they like best – images.

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