Every company is in the process of understanding how artificial intelligence (AI) 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.
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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 AI? And perhaps more importantly, how can digital agencies use AI to improve agency culture and even inspire innovation?
Digital Agencies Are Already Using AI
Before we dive in, let’s first specify what we mean when we talk about AI. In the context of digital marketing, AI is closely tied to machine learning, where computer systems are capable of learning and improving performance through data analysis without human intervention.
One example of AI 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 AI 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. AI 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 AI into their operations is the use of ad rotation settings in Google AdWords. When using the “optimize” setting, the machine learning 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 AI 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 AI, with a global team (Facebook AI 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, AI-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 AI 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 AI can help their content marketing, and some are already delivering personalized content at scale based on collected data and analysis. […]
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read more – copyright by www.forbes.com
Every company is in the process of understanding how artificial intelligence (AI) 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.
copyright by www.forbes.com
Digital Agencies Are Already Using AI
Before we dive in, let’s first specify what we mean when we talk about AI. In the context of digital marketing, AI is closely tied to machine learning, where computer systems are capable of learning and improving performance through data analysis without human intervention.
One example of AI 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 AI 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. AI 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 AI into their operations is the use of ad rotation settings in Google AdWords. When using the “optimize” setting, the machine learning 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 AI 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 AI, with a global team (Facebook AI 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, AI-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 AI 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 AI can help their content marketing, and some are already delivering personalized content at scale based on collected data and analysis. […]
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
read more – copyright by www.forbes.com
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