Loyalty practices and programs have traditionally been associated with engaging individual consumers.
Today’s customers expect supreme services and an easy way to achieve their goals.
Machine learning techniques enable marketers to go beyond traditional personalization methods by processing huge datasets and detecting patterns within customers’ behavior.
Large-scale loyalty platforms process millions of transactions originating from hundreds of locations while managing thousands of member accounts at any given moment.
The concept of personalizing marketing activities goes back to the 1990s. However, simply targeting an offer based on manually pre-defined segments or personalizing a message by using the recipient’s name is no longer enough to engage the desired audience.
According to a report by CyberSource (a Visa subsidiary), 90% out of 120 respondents that run complex loyalty programs experienced fraud in 2016.
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