Machine learning is a discipline of artificial intelligence combining science, statistics and computer coding that aims to make predictions based on patterns discovered in data. As opposed to rule-based decision systems, which follow an explicit set of instructions known by the developers in advance, machine learning algorithms are designed to analyze data and discover patterns that humans are unable to find efficiently, if at all.
In other words, machine learning leverages the massive power and objectivity of computers to see things in big data that slow and biased humans cannot – and then use those insights to determine how new data can be used to accurately predict results.
How does Machine Learning Help Marketers?
One of the biggest challenges facing marketers is how to personalize messaging to individual prospects and customers so that it most strongly resonates with the recipient. The results of successful, highly relevant marketing include increased customer loyalty, engagement, and spending.
Without machine learning, it is simply too difficult to compile and process the huge amounts of data coming from multiple sources (e.g., purchase behavior, website visit flow, mobile app usage and responses to previous campaigns) required to predict what marketing offers and incentives will be most effective for each individual customer. However, when all of this data is made available to computers programmed to perform data mining and machine learning, very accurate next best action predictions can be made.
Other areas in which a machine learning application can help marketers include:
Customer segmentation – Machine learning customer segmentation models are very effective at extracting small, homogeneous groups of customers with similar behaviors and preferences. Successful customer segmentation is a critical tool in every marketer’s toolbox.
Customer churn prediction – By discovering patterns in the data generated by many customers who churned in the past, churn prediction machine learning forecasting can accurately predict which current customers are at a high risk of churning. This allows marketers to engage in proactive churn prevention, an important way to increase revenues.
Customer lifetime value forecasting – CRM machine learning systems are an excellent way to predict the customer lifetime value (LTV) of existing customers, both new and veteran. LTV is a valuable tool for segmenting customers, and for measuring the future value of a business and predicting growth.
Implementing Machine Learning in Marketing
Pattern recognition and machine learning software have come a long way since their early days in the 1960s. New algorithms and technologies are constantly emerging, suggesting new possibilities and applications. Despite this, most marketers are not using any form of machine learning in their day-to-day efforts because it remains a complex field, requiring the involvement of data scientists and developers. Consequently, effective implementations of machine learning algorithms in marketing remain beyond the reach of many small- and medium-sized businesses.
However, specialized applications developed specifically to address marketing challenges – and to be very easy for marketers to use – are now available for smaller businesses with modest budgets. This is a game changer for savvy marketers because machine learning can eliminate the guesswork involved in many of the most challenging – and valuable – aspects of data-driven marketing.
Much of Optimove’s power comes from the machine learning algorithms that contribute to its highly accurate customer modeling, customer segmentation, LTV predictions and next best action recommendations. The Web-based software is designed to deliver the advantages of advanced machine learning algorithms to marketers, without any need to understand data modeling, statistical analysis or algorithm development.
As opposed to many other marketing technologies which feature “bolt-on” AI, Optimove’s AI is a core capability: the technology is built around the AI “brain”, making the platform much more robust and coherent. Optimove’s machine learning system plans, personalizes and optimizes every interaction across the customer journey, running thousands of recursive tests to continuously optimize every customer communications and adapt to rapidly changing consumer behavior, at a scale that is not humanly possible.
Yohai heads up Optimove’s data lab. He is a top-tier data guru with extensive experience applying the fields of business intelligence and advanced data analytics to practical business challenges. Yohai holds a master’s degree in machine learning and information systems.
