Retail marketers are tasked with the challenge of creating highly engaging online experiences that drive sales and revenue. However, this goal can be difficult to achieve for retailers that are stuck with obsolete and underpowered analytics tools.
Baynote released VUE, a self-service merchandising application to equip marketers and merchandisers with the tools they need to create more relevant online shopping experiences. Leveraging data technologies such as Hadoop, VUE combines Big Data storage, processing and machine learning with Baynote’s retail algorithms and real-time server architecture to create personalized product recommendations.
Pre-installed algorithms and data models available in VUE enable merchandisers to optimize shopper engagement. The solution also includes a user interface that allows merchandisers to design, test and deploy strategies across touch points. Team members can promptly make site changes that typically take weeks.
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Once chances are made to the e-Commerce site, retailers can track performance on a comprehensive reporting dashboard. Reports are created in a more automated fashion and data can be transferred to other in-house systems through secure APIs.
