Breakthrough AI technology quickly recognizes fast-changing consumption patterns to help retailers boost conversions up to 50%
ZineOne, whose Intelligent Customer Engagement (ICE) platform provides enterprise brands the power to offer consumers superior online shopping experiences, announced Speed to Sense™, a new predictive hyper-personalization technology. Developed by ZineOne in partnership with global financial services firms and retailers, Speed to Sense uses short term data analytics to help major retailers boost conversion rates up to 50% while maintaining a 90+% predictive accuracy. Compared to the pre-COVID-19 conversion rates of 3%, these gains represent significant boon for the retail, QSR, and banking industries.
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With the advent of COVID-19, pandemic consumer consumption patterns have swiftly shifted, making much of data analytics based on historical data obsolete. Typically, data from many sources such as clickstream activity, profile, and transactional data is aggregated over long periods of time. The belief is that the more data collected, the better the prediction results. However, using data over extended periods of time reduces the accuracy of predicting current behavior as the pandemic has created very different consumer behavior.
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Speed to Sense blends advanced data analytics with AI and Machine Learning to increase the rate at which the ICE platform can learn consumer behaviors while maintaining up to a 90%+ predictive accuracy. The result is unique offers that are more relevant and appealing to the visitor, especially those that need a nudge to purchase. Further, this is done at the moment the consumer is shopping, creating a win-win scenario for consumers and brands.
“What we have created is a new way to model short-term behaviors from using only clickstream data – which contains customer activity on a site – as an ordered sequence, which we termed as Customer DNA™,” states Manish Malhotra, Chief of Products for ZineOne. “Just as the encoding and analysis of human DNA revolutionized scientific insight, our patented algorithms sequence spatial and temporal consumer traits, fundamentally changing our ability to anticipate behavior and influence outcomes. These algorithms successfully boost learnings from short-term behaviors and dampen or diminish those from data seen over a longer period of time.”
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