The popular idiom “A picture is worth a thousand words” is no offhanded or inflated saying. Variations of this timeless and still-relevant concept date back to advertising copy from the early 1900s, and in some cases its origins are attributed to an unknown Japanese philosopher or a Chinese proverb. No source is certain, but image-based advertising has been around for a very long time, not just for its capacity to effectively distill complex messaging into visual essence, but because visual over text-based targeting is now a key driver in helping marketers apply a far more exacting audience segmenting and page analysis strategy to their advertising campaigns.
The terms of engagement between advertiser and consumer is now based on respect, relevance, and seamlessness, and marketers have just seconds, if that, to inspire a sentiment, make a connection, and leave a lasting impression. The marketer’s tool kit needs all the intelligence and sophistication it can possibly apply to connect the dots between content, user experience, and advertising at an optimum level. Computer vision and natural language technologies allow contextually relevant ads to appear where users are most likely to see them and when they are most likely to be receptive by not only displaying ads over images or video, but by contextually identifying what is in the image and displaying ads based on the image itself.
A Dominantly Visual World
We process visual data faster than any other type of data. Not only do we experience visual images more quickly than text, we have tailored the majority of our experiences to feature visual elements. Just look at the five most popular social media platforms and the dominance of visual content: Facebook, Pinterest, Instagram, Twitter, and YouTube. Visual content is more than 40 times more likely to be shared on social media than other types of content, and that metric is quickly shifting into the higher digits.
In research published by MIT News and funded by The National Institutes of Health, a team of neuroscientists found that the human brain can process entire images that the eye sees in as little as 13 milliseconds. According to Mary Potter, an MIT professor of brain and cognitive sciences and the senior author of this research, these “rapid-fire speeds” are a clear indication that what vision does is find concepts. According to Potter’s team, after visual input hits the retina, the information flows into the brain where information such as shape, color, and orientation is processed.
“That’s what the brain is doing all day long — trying to understand what we’re looking at,” said Potter. “The job of the eyes is not only to get the information into the brain, but to allow the brain to think about it rapidly enough to know what you should look at next. So in general, we’re calibrating our eyes so they move around just as often as possible consistent with understanding what we’re seeing.”
Something Old, Something New
According to recent research, the computer vision and hardware market is expected to hit $48.6 billion by 2022, a clear indication that this technology is in stealth mode and growing demand.
Without computer vision, marketers cannot comprehend the full content of a web page. A good example of applying image-based advertising is with an image that features mountain bikes as a good place to advertise energy drinks, or an image of a tropical beach as a perfect match for holiday rentals in the Bahamas. This technology and the precise insights it provides can help brands more effectively connect their message with that image in a highly contextual way and tap into the emotion or state-of-mind that a user is experiencing when looking at a photo or video.
And computer vision goes hand-in-hand with brand safety based purely on the inherent vetting of machine learning as it processes billions of images to determine the content of those images. In addition, natural language processing is used to extract keywords and classifications from the textual content available on the page.
It sounds so basic, using images and video for ad targeting. Call it a pull not a push strategy, call it a return to the simple tenets of advertising when Fred R. Barnard promoted the use of images on the sides of streetcars in a 1920 ad trade journal. We have an opportunity to use digital tech to tell great stories while respecting and valuing the time and experience of the consumer in exchange for context and value as we distill the literal essence of our advertising through image-based ads. There is history here, and our future.
About the Author
Ben Plomion is the Chief Marketing Officer at GumGum, with responsibility for brand management, integrated marketing programs and corporate communications. He oversees the planning, execution and distribution of consistent industry-leading content marketing campaigns. Ben helped significantly raise GumGum’s profile as a leading voice in the computer vision and digital marketing spaces. Ben is a guest columnist for top trade publications such as The Economist Marketing Unbound, MediaPost and CMO.com. He also regularly speaks at industry events such as AMA, OMMA and Contently.