The digital industry is facing threats to its status quo that are forcing all stakeholders to ask whether it deserved to be the status quo in the first place. New data policies are pushing companies to change the way they handle their users’ data. Those legal pressures – combined with the complexity of targeting and measuring across platforms like Mobile and OTT – are shaking the foundation of Digital Advertising. Premium publishers are standing up for user experience that encourages user loyalty over time, while brand safety concerns have made advertisers more cautious about where they spend.
Understanding the current state of contextual not only naturally leads us to question the old status quo but it also gives us important answers that will help advertisers and publishers better meet their goals.
If we’re seriously asking whether that foundation was ever sustainable, that’s a good thing. The goal of advertising is to connect with a target audience—and more than that, to connect without wasted ad spend or deterioration of UX. And you can easily argue that seemingly limitless third-party data (much of it is only questionably useful) and inexpensive ad inventory wasn’t always great for pursuing those goals.
The industry has always hoped for less waste, and better-performing and more valuable ad inventory. Now is the right time to demand it. We need to build off the old “right message, right person, right time” handle and add the right sentiment, mindset, or environment.
Fortunately, this industry has been preparing for this moment. Environment, or context, has been held up as a factor that can help lift us into the next phase of digital advertising. But there’s also been a lot of confusion over what contextual targeting’s capabilities are today, and how they can best be deployed to help advertisers and publishers meet their goals. We need to take a moment to catch up with contextual as the industry quickly moves on from the old status quo.
First off, behavioral targeting and contextual targeting work very well together. Layering these targeting strategies allow you to dial in your overall targeting and gain valuable insights about your best audiences and where they can be found. You can extrapolate from those combined behavioral and contextual data insights to develop methodologies for finding the target audience through contextual alone. Given the diminishing availability of user data, there is actually some imperative to developing that cross-indexed targeting insight portfolio now.
Also, consider that contextual data allows you to better understand your strategies before the media buy itself. Where do you find the deepest engagement on the publisher’s page? What contextual sentiments align with a campaign’s message and KPIs? Understanding these elements in advance allows advertisers to get their message across with fewer impressions. It also allows publishers to place the right value on their inventory and environments. All of this reduces guesswork on both sides of the transaction and enhances both accuracy and confidence.
Contextual can shine a light into the unknown in other ways as well. Discovery is an obvious advantage for advertisers and publishers alike. For advertisers, the right context for your campaign could very well exist on publisher sites that are not on your radar at all. There is quality content – and quality engaged audiences – on pages that may not be associated with the big names or reputations that brands traditionally feel comfortable advertising against. Even reputable publishers have content — particularly in the news category — that brands would exploit if they had more clarity on the nature of the content. And when advertisers benefit from reaching target audiences by unearthing viable inventory, publishers benefit from a revenue boost.
Both sides also benefit from contextual’s emergent ability to go beyond broad vertical categorization (e.g. news, lifestyle, health) or narrower content taxonomies (e.g. dining out, Super Bowl, alternative health, etc.) to categorize by sentiment. Sentiment targeting allows advertisers to capitalize on powerful, relevant, and valuable connections between the content and their advertising. It can help minimize concerns over brand safety—it reduces reliance on assumptions around the type of content appropriate for a particular message. Things get even more interesting with sentiment when you begin layering in behavioral data: What else are the users on a particular sports site interested in, aside from the sport they’re watching or reading about?
These insights—getting deep into sentiment, going beyond the self-explanatory, reflecting the nuances of a content category or how a developing story shifts in tone over time—are more accurate and valuable than ever, thanks to AI and Machine Learning. These tactics have brought semantic tech to new heights. We, as humans, recognize subtleties in language and visuals, because we understand how meaning changes depending on these simple signifiers are ordered. AI allows semantic tech to understand words and images the way a human would. Over time, semantic tech develops an increasingly nuanced understanding of any page it’s analyzing.
Contextual targeting has made remarkable advances while the industry’s focus has been on audience. And contextual is in a prime position to point us forward—toward something that’s better than what we’ve been accustomed to. Understanding the current state of contextual not only naturally leads us to question the old status quo but it also gives us important answers that will help advertisers and publishers better meet their goals.
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