For years, the marketing community has worked to establish, sustain, and extend relationships with consumers. Marketers have sought a means to not only understand current consumer behaviors but also to develop well-defined vision for the consumer's future.
Some 77% of 374 surveyed client-side marketers believe that within the next three years they will need to clearly define customer journeys to better understand and gauge the marketing program focus, according to a recent survey conducted by ANA (Association of National Advertisers).
However, only half of the 77% surveyed have the capabilities to do so today.
As more consumer information becomes available through Big Data, machine learning is the elusive puzzle piece that will enable marketers to complete the picture.
Machine Learning Defined
Although machine learning might be new tool in the campaign to develop better connections with consumers, it is far from a new business practice. Today, all over the world, machine learning is used daily to improve and expedite routine tasks, such as eliminating spam emails from our inbox and recommending new movies based on our choice. It can even be used to predict the winner of the FIFA World Cup.
Machine learning can be defined as "a subfield of computer science and statistics that deals with the construction and study of systems that can learn data rather than follow only explicitly programmed instructions."
That definition may make machine learning seem too analytical—almost counterintuitive in the effort to forge a better connection with the consumer. However, the opposite is proving true. If Big Data is the 800-pound gorilla in the room, machine learning has become the savvy animal trainer, working to not only understand the beast but also to optimize its performance.