Let’s hear what SmartFrame had to say about their product and the role of contextual targeting today...
PJW: Tell me about SmartFrame – who are you, what do you do?
SmartFrame: SmartFrame is the world’s largest image-streaming network that unites content creators, publishers and advertisers. A key part of what we do is in-image contextual advertising to a diverse global audience.
We aim to create a fairer and more transparent media supply chain, helping advertisers deliver high-impact messaging to carefully targeted audiences, all in a privacy-focused manner.
Our technology enables the streaming of up to 100 mega pixel images in place of the traditional JPEG. This provides users with much more engaging high-resolution images and interactivity through hyper zoom and full screen features. Additionally, the image is protected from theft, no right clicks or screen grabbing of images is possible.
Furthermore, our ad tech serves ads in these highly engaging images, our in-image contextual targeting system combines AI technologies with comprehensive and diverse image metadata for greater targeting accuracy than AI-based systems achieve on their own. Given our unique relationship with image creators, we can offer bespoke profile creation, including hand-picked images and hand-picked publishers lists for premium placement.
We are an ambitious bunch, and we are aiming to change the way images are displayed for the entire internet!
PJW: Should contextual advertising be the default choice for brands running targeted advertising campaigns, given ongoing industry changes about how to reach audiences in walled garden environments?
SmartFrame: Marketers are attracted to the huge user base of walled gardens like Facebook, Amazon, and Google, but they only account for 34% of online time. Overdependence on these platforms has been cited by 30% of UK marketers, with 38% saying that their campaigns don't target the right people. The discrepancy between where people spend their time online and where advertisers focus their money is clear, with 66% of online time spent outside walled gardens, but only 37% of ad spend there.
To address this issue, marketers should look beyond walled gardens towards a more diversified and encompassing open internet. Advanced contextual targeting can bring brands closer to customers by matching different sites with the most suitable advertisers and products. This approach allows advertisers to reach an audience already interested in their offering and offers a clear value exchange without disrupting the user experience or raising privacy concerns.
This technology can now connect first-party commerce data with real-time contextual signals, enabling marketers to drive and measure incremental revenue in a post-cookie world. With 69% of consumers more likely to engage with contextual ads, fresh solutions that offer better, more personalised experiences will likely increase this number.
While contextual targeting is becoming increasingly important for marketers, a balanced approach is necessary as it is unlikely to be the only source of effective advertising.
PJW: What does the evolution of contextual solutions look like from a technology perspective? How are advancements in machine learning and AI driving forward the contextual agenda?
SmartFrame: Technology is driving the contextual advertising agenda, the advances mean that from a targeting perspective alignment between ad, environment and image is possible to provide relevance when it matters most. However, that is really the tip of the iceberg, advanced AI for example neural networks can also harness more data such as purchase history or recent digital interactions with the brand and create even more relevant and timely ads in real time. Additionally, given the furore surrounds the various iterations of ChatGPT we may end up with ad tech contextual AI that manages the entire process.
PJW: Does contextual advertising require a step change in how campaigns are measured and attributed? Is attention-based measurement the answer? Is ‘attention’ the new ‘viewability’?
SmartFrame: As we’ve started to move into the next evolution of digital advertising, the importance of metrics that are typically used to measure performance – cost per mile (CPM), click-through ratio (CTR), impressions, and so on – has started to be questioned. While these clearly have utility and are unlikely to be abandoned, marketers and advertisers are increasingly looking beyond this to the idea of measuring attention.
The attention economy is built on the premise that attention is a scarce resource. As advertising can only be effective if it is noticed to some degree by its audience, it follows that understanding how different ad formats, placements, and other variables affect attention can help determine which kinds of campaigns are likely to be most effective.
When you consider the ever-increasing number of channels and range of devices in which ads are served, and the array of visual, oral, and audio-visual formats that advertisers now have to choose from, it’s easy to understand why this information is more valuable than ever before.
But part of the appeal of understanding attention can also be attributed to the shortcomings of existing metrics. For example, we may be able to find that an ad is more viewable, or be gaining more impressions, than another, but this doesn’t necessarily mean that it is getting more attention because of it.
One key difference between conventional performance metrics and the measurement of attention is that the latter is measured qualitatively, rather than quantitatively. This means that data on attention cannot be gathered on demand in the same way as it can with clicks and impressions.
PJW: What is the role of creativity in contextual advertising, how does data-driven creative help marketers reach audiences and what tools are available to refine and enhance this process?
Contextual Dynamic Creative Optimization (DCO) is an effective way to improve advertising. Contextual DCO takes into account the signals of the moment where an ad unit is placed on the web, updating the creative to make it more native to the surrounding content. This approach goes beyond contextual targeting, as it adapts the creative to fit the context around it, resulting in a more appealing ad.
Contextual DCO enables ads to be more aligned with what users are interested in at any given moment, with a high level of granularity. By using contextual DCO, an ad can be tied to what the user is reading at that moment, which can make the ad feel like an extension of the article itself instead of an interruption. For instance, if a user is reading an article about a particular topic and sees an ad that provides more information about that topic, the ad can significantly reduce the journey towards conversion, leading to higher click-through rates, views, and engagement.
However, contextual DCO may not be the right strategy for all brands, especially those that have a single product with a limited number of use cases. Therefore, it's essential to have a diverse set of products and marketing segments to take full advantage of this creative strategy. Brands should also use other types of targeting strategies, such as first-party data targeting and traditional user-data-based DCO, and test various creative and targeting strategies to figure out the best mix for different consumer segments, geographies, and environments.