The marketing industry has always relied on data. But the difference in data we have today is the sheer magnitude of it. The fact that most big data is unstructured makes it difficult for marketers to gain actionable insights from it. Lately, marketers are learning that artificial intelligence, specifically machine learning (ML), are perfectly suited for this task. By iteratively learning from data, machine learning algorithms allow computer programs to find hidden insights by detecting patterns in data without being programmed on where to look.
Digital Marketing provides better marketing insights and it helps marketers to plan more accurate and advanced marketing strategies. Engage the customers at the right moment with the right message is the biggest issue for marketers. Big data helps the marketers to create targeted and personalized campaigns. Big data plays an important role in digital marketing. Each day information shared digitally increases significantly.
Predictive advertising is yet another area of marketing that is evolving rapidly thanks to the massive strides in the strain of artificial intelligence called machine learning and wide access to large sets of digital data. In this installment of our MarTech Landscape series, we look at how predictive advertising works and how it's commonly applied. Predictive advertising is a subset of predictive analytics, also covered in our MarTech Landscape series. Predictive analytics uses machine learning to predict future outcomes based on behavioral patterns seen in historical data. Those predictions can be used for any number of purposes: understanding who is likely to pay off a loan, prioritizing leads most likely to close and so on.
AI and machine learning are making the customer experience more personalized and contextual than ever before. Banks and credit unions are using advanced technology to make websites, emails, digital advertising, social media and other content more efficient and effective. This is increasing marketing ROI as well as customer satisfaction. Subscribe to The Financial Brand via email for FREE!There is a great deal of discussion of the potential value of artificial intelligence, machine learning and robotics in banking. Unfortunately, much of the implementation of these technologies lags the potential by a significant margin.