By Marika Roque, Chief Innovation and Chief Operating Officer at KERV Interactive
In a world where technology is advancing at lightning speed, data, AI, and adtech are transforming the way brands connect with consumers, opening up a host of new channels and formats that captivate audiences like never before.
Interactive and dynamic video ads particularly offer immense promise as they pull branding down the funnel and they create more personalized experiences that welcome interaction with the consumer while collecting metadata and object-level interaction data, which help brands better understand the interests and intentions of their audiences while powering the most precise forms of measurement and optimization.
But expanded channels and additional data mean new challenges, such as integrating with existing technology, leveraging in-flight data, and finding alignment formulas for industry-wide metrics. If these challenges can be overcome, everyone—agency, brand, and consumer alike—stands to gain.
The Creative Agency Challenge
In today’s challenging economic climate, brands are increasingly looking for new ways to optimize their marketing budgets, which is why data and key performance metrics are so important.
However, working with creative agencies who make video ads can be tricky. They often have emotional ties to the content they create and aren’t always eager to make even data-informed changes.
The good news is there’s a new metric and technology that will change this game forever: Attention.
Metrics platform Adelaide is working to develop this metric and help publishers make more informed decisions as it pertains to page level placement for programmatic media decisioning. It’s also pushing for more transparency so that publishers can fix issues like page clutter and ad fraud.
But now, a game-changing alternative has emerged: the Active Attention Index.
The Attention Paradigm
This index is a simplified version of multi-touch data insights, providing brands a snapshot of their ads’ performance–more closely related to business results and consumer intention. The index makes data more accessible and useful for advertisers by considering factors like average time spent, interaction, latency during the consumer’s experience, and the number of interactions per user session in video ads.
For an athleticwear brand, for example, this index paired with metadata insights can determine which creatives are more impactful to the consumer while also indicating which featured products within those creatives are popping more than others and then tie this result back to actual sales.
Attention metrics can also tell brands which videos had the highest (or lowest) attention quality—and why. This allows for quick testing and adjustments, enabling agencies to safeguard their branding and awareness budgets, which is more important now than ever.
Attention is a more useful insight than just click-through rate (CTR) because the latter does not necessarily tell the whole story of the content engagement. And, of course, understanding how users engage with content—including time spent on page and scroll depth—is critical to creating effective marketing strategies that drive engagement and increase revenue.
The results speak for themselves.
In early tests sampling video advertising units over the past few years, there has been a significant increase in the average interactivity across all units—with some units doubling interactivity—or more. The average data elements collected per unique user has also continued to increase as well, increasing by upwards of 15 percent year over year.
Increasing object-level interactivity in video advertising has also helped improve ad measurement and thus optimization opportunities.
At the end of the day, this helps brands work with creative agencies to make data-informed decisions as attention data bridges the gap between the emotional and the digital, allowing for the optimization of creative content based on frequency, recency, and monetary value.
The RFM Model
Data has proven to be a great way to connect ad campaigns to business results—and to make them easier to understand. This has contributed to a renaissance of the Recency, Frequency, Monetary (RFM) model in video advertising.
This model segments customers based on their behavior and value, which allows brands to tailor their content to different groups of consumers at various stages of the funnel. This can help improve engagement, increase conversions, and drive revenue growth.
Whole Foods is one brand that uses this model. With attention-based technology, however, the grocery chain can change its creative on the fly based on frequency. This includes identifying the video content with the lowest attention quality and optimizing at both the creative and user frequency level for better performance.
Adoption of these models by publishers, however, has been mixed so far as they continue to focus on content production. They recognize engagement and attention are key to creating effective content. By zeroing in on attention in particular, publishers can create content that is more likely to be shared—and, in turn, generates more engagement, revenue and value for advertisers.
Attention quality technology allows publishers to analyze their content and ads to ensure they are engaging audiences and capturing attention. By focusing on the quality of attention, publishers can ensure they are creating content and ads that resonate with users, ultimately driving engagement and revenue. However, many publishers still rely on impressions to generate revenue and are reluctant to shift from traditional success metrics, like clicks and views.
Nevertheless, the attention paradigm is gaining traction as other publishers recognize the importance of high-quality content that engages their audiences and drives loyalty and consumer interaction instead of simply generating as many impressions as possible.
In addition to revenue, the attention paradigm is critical to helping publishers resonate with users, who are bombarded by more content than ever before, and capture their attention.
This is a pivotal moment for the ad industry. We’re seeing the ultimate convergence point between art and science, creative and data, as well as creativity and calculation, which opens up a world of opportunity to brands, creators, and publishers. Real-time optimization is a crucial part of this convergence, allowing advertisers to optimize their campaigns as they run, rather than relying solely on post-activation analysis.
This metric and index is meant to help creative agencies enhance their work while also empowering both creative and media to make changes on the fly, maximizing the potential for better client results. But alignment and education must come first to maximize the potential for all. The industry must clearly define what attention means and work together to establish metrics everyone can understand and agree upon in order to capitalize on this revolutionary NEW metric.
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