New Tealium Predict Machine Learning Solution Helps Marketers Proactively Understand CX Data to Deliver ROI Faster
Tealium, the trusted leader in real-time customer data orchestration, announced the general availability of Tealium Predict ML, built-in machine learning technology for Tealium AudienceStream, its market-leading Customer Data Platform (CDP). With more than 30 million predictions amassed already, Tealium Predict ML seamlessly pairs with Tealium AudienceStream CDP to continuously anticipate customer behaviours – using machine learning to power more effective audience segmentation for better customer engagement, conversion rates, and lifetime value.
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“While more organisations are realising the value of data collection and insight activation each day, they’re also realising these projects can be extremely resource-intensive without the right solutions in place”
Amidst budget reductions and heightened emphasis on customer retention, marketers are being asked to deliver greater results with fewer resources. Tealium Predict ML was built with the marketer in mind and is a simple and cost-effective way to allow teams to inject the value of machine learning powered insights into their existing tech stack. By creating custom-tailored predictions in a matter of clicks, marketers gain insights into the likelihood of customer behaviours, as well as full visibility into the data used to generate them. With these insights, brands can effectively and efficiently engage and delight the right customers while improving business outcomes.
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“When focusing on real-time, data-driven decision making to optimise marketing investment, I’ve found there is a need to move beyond historical methods and shift toward machine learning and AI to predict the optimal audiences to go after,” said Amin Foda, Director of Marketing Infrastructure at Monash University. “Using Tealium Predict ML helps us build real-time audience attributes based on their likelihood to take an action and engage with them on the next best conversation across all identifiable channels at the right moments.”
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