BlueConic, providers of a customer data platform, has launched the BlueConic Recommendations Engine, enabling marketers to automatically deliver one-to-one content and product recommendations in real time to website visitors.
Using machine learning and proprietary algorithms, the BlueConic Recommendations Engine combines individual user profile data with key attributes and metrics to deliver recommendations that are aligned with individual user behaviors and preferences. Customers have seen between 30 percent and 50 percent higher click-through-rates compared with existing recommendations tools, according to the company.
BlueConic uses Apache Spark big data processing technology to handle the high-volume machine learning tasks required for real-time recommendations. Functionality available with the BlueConic Recommendation Engine includes the following:
"Companies are seeking more effective ways to connect with and engage with consumers, as online competition grows daily," said Bart Heilbron, fFounder and CEO of BlueConic, in a statement. "Recommendations for a single person challenges the industry standard in order to help marketers increase customer loyalty and sales. BlueConic has developed an incredibly easy way to integrate high-value recommendations into existing marketing processes and campaigns."