Brands are in the midst of a great user disengagement.
The advertising market has never been as saturated as it is today. For many advertisers, capturing the attention of your audience has begun to feel like a game of chance. Now more than ever, survival hangs on a brand’s ability to reach its audience with authentic messaging, at the moment users are ready to hear them.
Yet many brands have a blind spot that keeps them from delivering ads results. Without data to rely on, publishers frequently fail to foresee their users’ needs and over-optimize their web pages exclusively for viewability. More often than not, this drags down the user experience, which subsequently leads to low user engagement and disappointing campaign results.
Marketers do their best to find creative solutions to the problem of delivering the right ads, at the right time and place, to the right users. But their solutions can only go so far without data to back up their assumptions.
At MGID, we have all the information we need to make the objectively best ad placement decisions, backed by results of the latest studies of user engagement and attention.
Why this breakthrough in ad placement is possible
When it comes to ad placement solutions, the need to move beyond bounce rates and dwell time for data has been obvious for some time. While dwell time does provide a decent idea about user engagement levels, it doesn’t reveal much about how users interact with content once they’ve opened the link. In other words, there’s no telling where you’re grabbing users (or where you’re missing them).
Without any kind of data that reveals the parts of the article that most engage audiences, marketers can’t optimize ad placements in an objective, data-driven way. To raise the odds of getting noticed in the absence of data, marketers are tending to choose generic placements or bomb users with multiple ads on the same page.
Our innovation in the in-content impact widgets is a reaction to this well-intentioned but ineffective trend. We don’t flood articles with ads that won’t stand a chance of getting noticed. Instead, our attention-based placement algorithm relies on empirical evidence gathered from thousands of news articles, showing how users engage with the content and what grabs their attention the most.
We found the inspiration for our attention-based placement algorithm from two crucial studies pertaining to modeling sub-document attention and measuring user engagement.
Using viewport data, i.e., data that shows how long certain page elements were displayed on the users’ screens, researchers were able to study user engagement at a level deeper than ever before, HTML-level within the page. They were able to extract precise data about user attention across different web page elements by analyzing scrolling and viewport metrics. The results were more specific than what they would have achieved by simply observing dwell time.
How does MGID’s attention-based algorithm work?
At MGID, we’ve developed an AI-based algorithm that relies on the viewport data to identify the best potential placement within the article. The algorithm automatically inserts advertising into the “hottest” part of any given piece of content, putting brands literally front-and-center for potential leads.
We used a sample of more than 100 million page views spanning upwards of 120 thousand articles from major online news sites to develop our auto-placement algorithm. Thanks to user activity data we derived from MGID’s publishing partners, we were able to create an excellent predictive system that pinpoints elements that get the most attention. Our analysis was focused on the amount of time users spent at each section of the article, how they interacted with each element on the page, and even the length of the article and geographical data.
This analysis allowed us to develop our attention-based auto-placement algorithm. Our technology predicts the perfect time and place to automatically display contextually relevant in-content impact widgets users will most likely engage with.
The targeted widget placement and the native format of our ads grant higher viewability for the ad. Together with other optimization features and know-how’s such as cross-format yield optimization, it results in enhanced performance for MGID’s advertising and publishing partners:
- the average vCPM within our platform increased by 18%
- average CTR increased by 10%, average CR – by 23%, compared to other ad formats
Bottom line
MGID’s attention-based auto-placement algorithm is an innovative marketing tool backed by years of research and content analyses. With all the data at your disposal and an AI solution to act on it, finding your warm audience is no longer a game of chance.
Thanks to our advanced ad placement techniques, we can confidently guarantee both publisher and advertiser satisfaction. Advertisers no longer have to overspend on unnecessary ads that clutter the page and disrupt the user journey, while the publishers get more returns on all ad placements.
Our data-driven approach combined with the native format of our ads is a sure-fire method to optimize your advertising efforts. The algorithm we developed is proof that ad placement can be so much more than just a guessing game.
