Image streaming: why it’s revolutionizing the photography and advertising industries

Contextual advertising appears as the strongest candidate to fill this void, and for good reason. Whereas cookie-based behavioral targeting relies on historic user activity, contextual targeting considers what a user is viewing at that moment. By taking the online environment in which an advertisement is displayed into account, the user is served advertising that’s likely to be far more relevant to them at the time. By increasing relevance, the chance of engagement is higher, which, in turn, maximizes the potential ROI for the brand in question.

Research has already indicated that such a model is one that online audiences will be willing to embrace. A recent study published by Integral Ad Science (IAS), for example, found that 73% of users find it more appealing when an ad is related to the content of an article.

But even though the data backs this up, the mechanics of any such system still need to be addressed. How exactly do we determine what is and isn’t relevant? The website and keywords may be a good fit for an ad, but what about the images that accompany it? Arguably just as important, how can we be sure that such ads are actually viewed and effective?

At SmartFrame Technologies, we believe that images are key to this model having the greatest impact. While their role of illustrating an article and providing more context for the reader has always been understood, in a post-cookie landscape they also contribute two critical components to the success of an advertising system based on contextual relevance.

The first is positioning. Given that images occupy the most prominent areas of the page, they are ideal vehicles for advertising. Why hope that users will notice banner ads around the content they’re interested in when you can simply serve them within the images as they are being viewed, in the body of the article itself? And why restrict this to a small banner lining the bottom of the image when you can momentarily occupy its entire area for maximum visibility?

The second component is the data that images contribute. AI-based image recognition is sophisticated enough to give us an idea of an image’s subject, but even the most advanced systems can only do so much. SmartFrame’s unique relationships with image libraries allow us to access comprehensive metadata sets, which give us a far better idea of what’s going on in an image. In a sporting image, for example, this kind of information may include the name of a specific player, the location in which a game is being played, and even the specific game itself. Combining this level of information with (anonymized) user location and device information creates a highly-informed foundation for contextual ad targeting.

Banner ads have long been hampered by their poor placement and lack of relevance, and part of the strength of SmartFrame’s contextually relevant in-image advertising system is that it directly addresses both issues. Recent research carried out by Nielsen showed display ads within SmartFrame images to be 34% more relevant, 14% more memorable, 13% more engaging and 11% more enjoyable than a site that employs conventional advertising. Video advertising delivered in the same way was also shown to be more engaging; among those who recalled advertising from a website, 57% of people claimed not to have interacted with conventional advertising in any way, while only 35% of people claimed the same for SmartFrames in-image video advertising.

It’s easy to view the deprecation of third-party cookies as an obstacle toward reaching the right audience with the appropriate message, but, if anything, it should be seen as a blessing. Instead of trying to improve a model that’s always had its shortcomings, contextual in-image advertising allows advertisers to deliver high-quality ads with the user’s current focus and interests for maximum relevancy, and with a more prominent placement for high visibility and maximum ROI. SmartFrame’s patented image-streaming technology is revolutionizing both the photography and advertising industries.

Nielsen Digital Content Evaluation measures the impact of native, social or branded digital content by exposing a relevant and representative sample of online panelists to a campaign’s content. Commissioned by SmartFrame, this study assessed whether the content generates better engagement for advertisers by providing a better visual experience for users. This research analyzes 1200 responses surveyed in August 2021.