As the landscape of modern marketing shifts, Marketers are struggling to effectively leverage the full potential of the complex web of MarTech tools available to them. Artificial intelligence may be the only path out of digital chaos and back to marketing sanity.
As the Wall Street Journal reports, new research has indicated that, among the top hundred American ad spenders, the average CMO tenure decreased from 44 months in 2015 to 42 months in 2016. Although two months isn’t itself an astonishing drop, this is only the most recent data point on an extended trend-line that has seen CMOs become far and away the shortest-tenured members of the average company’s C-suite.
There are a number of factors informing this trajectory, but perhaps foremost among them is the rapidly changing landscape of modern marketing practices. Among the many other responsibilities of CMOs is that of equipping marketers with the MarTech tools they need to drive consistently better results from their marketing efforts. What many are discovering, however, is that every suite of brand new tools, no matter how powerful, don’t add up to a simpler marketing world — in fact, more tools often only bring more complexity.
The Challenge Big Data Presents to the Modern CMO
For starters, CMOs are investing in technologies and strategies that enable them to understand, track, and adjust the relationships between marketing, sales, and revenue. At the heart of this relational web is the ability to determine the return on each dollar a company spends on advertising, a task that entails collecting, processing, and analyzing thousands upon thousands of ad campaign data points spanning dozens of channels, devices, and formats. Only then does it become clear which ad deployments deserve additional investment and which should be tweaked or discontinued.
Fortunately, a January 2017 survey conducted by the Interactive Advertising Bureau and the Winterberry Group shows that a majority of marketers understand what they should be doing. According to the survey, cross-channel measurement and attribution has become a more popular method for collecting, evaluating, and acting upon ad performance data than older approaches, like general audience analytics and programmatic media buying. Nearly 60% of US-based digital marketing and media practitioners indicating that they “expect to be engaged in cross-channel measurement and attribution” over the course of the coming year.
The only problem is that this type of measurement and attribution is incredibly complex, and requires a set of MarTech tools curated according to the duties and ambitions of every marketing department. While these tools can be very useful, they are most often siloed to particular channels or devices, and no single one of them can provide a holistic, real-time view of campaign performance. Try as they might, no CMO will be able to put together a MarTech stack that allows them to achieve these ambitions without hiring a team of data scientists to work around the clock performing cross-channel analysis.
AI Marketing Platforms Offer a Solution
That’s because cross-channel, cross-device attribution and well-informed ad buys require far too much data crunching for any one marketer to perform, even if it was the only function of their job. The volume of information involved with modern ad campaigns far surpasses the processing power of the human brain, meaning computers have become vital players in the marketing arena. But for a computer to truly unburden modern marketers to achieve the ambitions of their CMOs, it must be capable of learning and applying insights derived from the ins and outs of modern marketing. In other words, it must be programmed with artificial intelligence.
A platform like Albert™, the world’s first AI marketing platform, combines deep learning, predictive analytics, and natural language processing to not only collect and organize ad campaign data, but to detect patterns in and draw conclusions from the data in real-time as well. When authorized to do so, Albert™ can even act upon his own analyses by piloting thousands of micro-campaigns simultaneously and, based on high-volume multivariate testing, scaling up ads that perform well and discontinuing those that do not. By leveraging his AI capabilities, a CMO is able to use Albert™ to maximize the efficiency of her company’s marketing spend and bring the real results she needs to prove she belongs in that executive role.
The modern CMO has embraced the MarTech revolution, but without the help of advanced tools like Albert™, his/her department will remain mired in the complexity that MarTech was designed to eliminate. CMOs can make decisions based on accurate attribution figures and, produce impressive outcomes by incorporating cutting-edge technology on top of their existing tech stacks. Want to find out how you do that? Check out our latest white paper on how AI fits into your marketing stack.