ADOTAS — The online advertising industry is constantly searching for ways to make advertising more effective and more efficient. Essentially, we always want to find ways to make more money while investing fewer resources on the front end. As such, we have sought to improve delivery methods, relevance, flexibility, scale and more.
Over the years, this search has led us to the development and widespread adoption of game changing technologies and approaches. Basic display began with the placement of ads on the sites that had the most views, regardless of who those viewers actually were. It was simply about visibility and hoping that you’d see a jump in revenue numbers.
Advertisers quickly learned that this was not a sustainable model; paying for ads without any way of knowing how effective they were was tremendously wasteful. So we started tracking certain KPIs, the most important of which was the click. If we knew that someone clicked the ad, then we could at least say that we had reached that person with our message.
But of course, we eventually learned that that wasn’t enough either. As consumers began to use digital channels in new ways, especially as mobile and social technologies became more prolific and accessible, we learned that we couldn’t simply associate clicks and impressions with sales because the path between them wasn’t always direct.
So we had to start thinking in terms of deep customer engagement, building relationships with customers through advertising rather than simply driving clicks. That meant using data to find out who they were as people, not just as profiles. We began to harness data from as many digital channels as possible to derive insight that we could use to inform campaigns. This led to the development of behavioral targeting platforms, which were quickly snapped up by the large ad networks and became the gold standard of digital engagement.
As we know, however, the fragmentation of media only continued in the ensuing years and the flow of data became a flood. Consumers became more and more active across a variety of channels and devices, making them harder and harder to track as they jumped between them. Not to mention, their attention spans were getting shorter, meaning if you could reach them in the first place, you had very limited time in which to capture their attention, so it had to be as timely and relevant as possible.
We not only had to change our philosophy toward engaging customers; we also had to start figuring out how to accomplish that goal at scale and in a timely (read: immediate) manner. That meant developing platforms that could quickly parse data, turn it into insight and then deliver an ad that was (hopefully) relevant based upon that insight.
Ad networks, targeting platforms and bidding platforms handled the majority of those tasks until the last two or three years, which saw the widespread adoption of programmatic technology as the norm for buying and selling advertising inventory. Those networks and platforms then either had to adapt or perish, as programmatic quickly proved to be the most advanced method for driving efficiency, relevance and scale, which translates directly to revenue.
But as beneficial and cost-effective as programmatic is — and the success metrics are staggering — there is growing awareness among digital marketers that ad creative still poses a time and budget crunch for campaign strategies.
Just ask Don Draper: the creative is what should resonate with each individual customer in an emotional or intellectual way, meaning it should be relevant to both their general interests and what they need at that precise moment. Yet how can advertisers be sure that a) they are putting the right creative in front of the right customer and b) they are reaching as much of their potential customer pool as possible?
Intent-based ad targeting and programmatic buying has done wonders for ensuring the relevance of an ad across large audiences, but there is still a major disconnect for most advertisers when it comes to reconciling that all-important individual resonance and the scalability of reaching large audiences.
Creative in general is limited without nonstandard sizes and formats, and analyzing creative data performance can be daunting at best. As we reach the pinnacle of adoption of programmatic buying, it is only natural that our next step be the widespread adoption of a programmatic creative solution. In fact, it is not only natural — it is vital if advertisers want to preserve the engagement power of good creative while maintaining the speed and scale of programmatic buying.
Most advertisers can’t spend the countless dollars and hours it would take to manually create the dozens, if not hundreds, of ad formats that it would require to keep up with the pace of programmatic, nor should they have to. Programmatic creative solutions can ensure that ads are tailored to audiences and relevant to both context and intent, and they can do so automatically.
It’s time for us to take the burden off creative departments and take advantage of the next natural step in the evolution of digital advertising toward maximum efficiency, agility and results.