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.
Holiday giving is emotional. Consumers scour the Internet on Cyber Monday for the perfect gift to wrap carefully under the tree waiting in anticipation as gifts are opened; “Do they like it? Did I pick well?”
One of the inherent benefits of loyalty programs is the data and insights marketers can glean about their best customers. Yet, as I talk with clients I often find marketers have the perception that their data strategy and loyalty programs do not belong together, and they are treated as separate marketing entities with unique teams, goals and plans. But data is an integral part of loyalty programs. Data fuels customer identity so loyalty marketers can better understand the behavior of their members, predict future behaviors and as a result drive more loyalty to their brand.