Contextual Targeting’s Resurgence In The Year Ahead

The Sell Sider” is a column written by the sell side of the digital media community.

Today’s column is by Paul Bannister, co-founder and executive vice president at CafeMedia.

Contextual targeting is one of the original forms of targeted marketing, hearkening back to the days when Chevrolet might have run an ad next to a local newspaper’s feature story on new cars for the coming year. That crude model for contextual targeting migrated onto the web in the early days of digital advertising in the ’90s. If users browsed a video game website, they were assumed to like video games, and video game advertisers would buy ads there.

Over the years, contextual advertising declined in popularity as digital marketers opted for flashier methods, such as audience-based buying, retargeting and CRM onboarding. Context has taken a back seat to user-data driven marketing, but in 2018, I believe contextual targeting will enjoy a resurgence as new technologies and approaches enhance its capabilities and marketers learn more about the limitations of other tactics.

Before we dive in, it’s worth revisiting the user experience around contextual targeting. When consumers are in the mindset of making a purchase, they seek content to help make the right decision. A given user is usually researching products across many days, weeks or months before the purchase, so reaching that consumer across that entire timeframe is critical. And, this means marketing based on context pays dividends over time – as some consumers will purchase today and others six months later.

Contextual Marketing’s Historic Challenges

Measurement has always been a challenge for contextual targeting since the experience is such a long process. Attribution models relying on click-through and view-through measurement favor targeting at the very bottom of the funnel. That minimizes the value of all other touch points that contributed to driving a consumer toward a purchase.

This impacted the use of contextual targeting, as context is always a great indicator of intent, but pinpointing the “moment of truth,” when consumers are about to make a purchase, is hard to combine with contextual targeting. Marketers were biased toward scaled mediums that purport to find consumers at that last moment before purchase, but rarely had any real impact on their purchasing decisions.

Another limitation has been the rarity of great content for contextual targeting. Much of a consumer’s time online is spent playing games, sharing with friends, reading the news or other activities unrelated to purchasing decisions. While marketers might want to target consumers when they’re researching a purchase, that rarity limited their ability to find consumers at the right time but also drove the pricing up. The combination of flawed attribution models with limited and expensive access curtailed buyer interest significantly.

What’s New In 2018

I believe that 2018 will see a number of changes that will push marketers back toward context in a big way. First is the long-standing need to improve attribution systems. Existing models haven’t been effective, and the technology wasn’t there to improve them. That’s changing now, with much more sophisticated multitouch attribution systems that will uncover the long-term value driven by media targeted to context.

Apple’s ITP, GDPR and other pro-privacy moves by governments and industry will continue to limit marketers’ ability to target consumers across sites and devices. These limitations won’t necessarily decrease digital budgets but will drive advertising toward cookieless targeting methodologies, with contextual targeting being at the top of that list.

Much work is also being done to categorize and organize available content. Earlier, less sophisticated contextual targeting systems could categorize content into simple groupings such as “style and fashion/women’s fashion” or “automotive/SUV,” but newer approaches can drive much deeper understanding of the content. This deeper knowledge can make the connection between content and intent, which are closely tied but often hard to link.

Overall, the rise in advanced attribution modeling, an increase in the scale and value of contextual targeting systems and larger trends toward privacy should make 2018 a year for strong growth in contextually targeted digital advertising. Buyers want to be where consumers are making decisions, and relevant content is the gold standard in that regard. Now the technology finally has caught up with buyers’ intent.

Follow Paul Bannister (@pbannist), CafeMedia (@CafeMedia_) and AdExchanger (@adexchanger) on Twitter.

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  1. Great article Paul, GDPR will definitely be a big deal for marketeers in 2018 and in our view help drive a shift towards context as a way of getting to the right user at the right moment.

  2. Great job connecting attribution modeling back to contextual targeting.

    Agreed, contextual targeting looks poised to reclaim some of its former glory. I would add (and you hint at this) that we will almost certainly see the definition of “context” become broader, more holistic, and ultimately far more effective.

    I can only assume that relatively SUBJECTIVE contextual attributes (many of which apply to the customer, not the publisher or content) such as mood, style, aesthetic, personality, and so forth are perhaps even more powerful than OBJECTIVE yet simplistic rules of thumb such as “automotive website = good place for car ads.” Building enduring brands has always relied on calculated subjectivity, but machine learning is now reaching a state where it can start to emulate at mass scale the kinds of contextual opportunities that heretofore needed to be manually and painstakingly discovered and cultivated by great CMOs, CEOs, creative directors, media strategists, and so forth.