Every company is in the process of understanding how () will affect their industry. It can be intimidating and even discomforting to consider the consequences of using machines to make decisions. But if there’s an industry that should be comfortable with this potential shift, it’s the marketing industry.
Making decisions based on data isn’t a new concept. It’s long been at the core of any successful marketing strategy or campaign, including at my own agency. So how can digital agencies use their data literacy to take full advantage of ? And perhaps more importantly, how can digital agencies use to improve agency culture and even inspire innovation?
Digital Agencies Are Already Using
Before we dive in, let’s first specify what we mean when we talk about . In the context of digital marketing, is closely tied to , where computer systems are capable of learning and improving performance through data analysis without human intervention.
One example of already in action can be seen in programmatic media buying using a demand-side platform (DSP) such as Google’s DoubleClick Bid Manager. The programmatic buying platform incorporates a variety of features, including automated targeting using real-time bidding models, a simplified buying process, automated budget pacing, and real-time reporting and optimization toward the key performance indicator a campaign manager selects. can also be used in serving dynamic creative, as algorithms begin to learn which audiences respond to various creative versions or featured products.
Another example of digital agencies integrating into their operations is the use of ad rotation settings in Google AdWords. When using the “optimize” setting, the technology prioritizes search ads that are statistically more likely to perform more efficiently based on keywords, search term, device and location, among other variables.
Tools like Google Analytics are great for collecting data, but similar to DoubleClick, the real value in is its ability to analyze that data and endorse strategic action. PaveAI, for example, is doing more than simply communicating information through graphs and charts. It’s using statistical models to recommend actions that are focused on generating leads and sales as opposed to site traffic.
Facebook has also been a major proponent of , with a global team (Facebook Research, or “FAIR”) dedicated to helping communities further understand how automated systems and processes can achieve human-level intelligence. Despite the fact that Facebook has recently severed ties with many third-party data providers as a result of its public shakeup, -influenced advertising campaigns (“smart ads”) on the social media giant’s pages are still impactful when we consider the wealth of targeting information users explicitly make available to Facebook.
It’s important to note that many applications of are still in their infancy, and that’s especially true in the content marketing arena. While organizations like the Associated Press are using algorithms to produce basic content like stock reports, we’re likely still a long way from replacing the entire creative process. But many agencies are exploring how can help their content marketing, and some are already delivering personalized content at scale based on collected data and analysis. […]