The industry has been talking about machine learning for years, but what’s different today is that marketers have begun to implement machine learning tools and tactics to advance their marketing efforts towards advanced personalization strategies. Machine learning is taking over personalization by disrupting content management, how marketer’s approach analytics and one’s ability to reach customers across channel at scale. So how can marketers achieve this level of personalization through machine learning? By taking a collect, detect and act approach.
Epsilon’s Retail Strategic Consulting practice counsels clients on CRM and loyalty strategies that help drive profitable growth. Advising on best practices to optimize customer acquisition, retention and personalization, the team helps clients navigate through customer-centric transformation. This Meet a Marketing Expert series is designed to pull the curtain back on new viewpoints from across Epsilon, its affiliates and partners, on deepening customer intelligence and implementing programs with impact.
Machine learning is a highly talked about topic. Amidst all this noise, it’s important to understand the meaning and relevance of machine learning to marketing and how it helps to enhance customer engagement, and do it at scale. Machine learning can be defined as an application of artificial intelligence that provides systems the ability to automatically learn and improve from the experience (without explicitly being programmed to do so). The benefit to marketers is that it helps them to collect and process massive amounts of data, enabling them to better get to know their customers in real-time, and act in milliseconds to provide relevant offers creating a personalized and engaging experience. And more marketers are adapting machine learning into their marketing programs. 48 percent of companies plan to use machine learning to gain a greater competitive advantage.