The legacy digital advertising industry has been disrupted by recent moves by leading industry players like Apple and Google to tighten consumer data security that plays to their strengths and further centralises their dominance of the digital advertising universe.
Outside of walled gardens, advertisers are questioning if this signals an end to the legacy digital advertising model that many of us grew up with. A number of alternatives have been promoted, including identity verification, interest-based advertising, and contextual alignment.
The legacy programmatic digital advertising model has been dominated by Facebook and Google with a significant share of advertising spend going to this data-rich duopoly, which has not evolved in decades.
However, there is light at the end of the tunnel. New data intelligence techniques enabled by sophisticated Customer Data Platforms (CDP’s) and fuelled by first-party data focussing on contextual data will result in a digital advertising renaissance.
Contextual data, facilitated by advances in automation and artificial intelligence (AI), will allow the industry to move beyond the era of retargeting, which rightly so has alarmed consumers and regulators alike, .and will result in greater revenue equity for publishers. By utilising these advanced capabilities, built on valuable first-party data, Advertisers will be offered new innovative audience targeting tools without compromising performance or consumers privacy.
These techniques will further strengthen traditional relationships between advertisers and publishers which were largely disintermediated by programmatic networks.
Historically, with contextual buying, advertisers would partner with publishers to target interest categories that these publishers established and maintained based on their visitor behaviours. For publishers, this meant much manual work to tag articles or videos with appropriate keywords For advertisers, this meant partnering with publishers, who invariably utilised different taxonomies and audience demographics thereby making the process both complex, inefficient, and often ineffective.
In more recent time, progressive publishers have adopted systems that automatically index all forms of digital content at scale, with more speed and accuracy. Furthermore, technology can now identify people and brands in a video or image, and natural language processing can automatically extrapolate key political figures discussed in a podcast. There is even research to understand the overall sentiment of videos and articles. These innovations and many more currently in research and development will unlock the power of context at scale. Advertisers will target audiences using an entirely new generation of contextually derived data. Examples of context targeting include video content analysed to identify product appearances or a health and wellness brand that will target content featuring their celebrity brand representatives.
There are numerous contextual signals and patterns that we cannot currently identify that will become invaluable for advertisers. As contextual data analytics improves we will surely be able to predict individual behaviour through context.
With these advances in CDP, we will better understand the advertising implications of any item of content consumed and how a person’s mindset might impact their ad receptivity at any given moment in time. Relate that to specific consumer feedback and we deliver far more powerful, efficient, and effective campaign targeting than we have today.
With thanks to AW360