Retailers that have a higher percentage of identifiable transactions (for example, BOP traffic) will be able to predict with higher precision what offers are most likely to land with their customers as well as are in a better position to create and forecast traffic.
Helping retailers compete by making better use of their data, Oracle continues to weave significant artificial intelligence (AI) and machine learning capabilities into its Retail Insights and Science Suite.
Customer-focused retailers who deliver the right product and promotion through the most effective channel, at the right time, individualize promotion. Learn how a fit-for-retail-purpose customer relationship management (CRM) platform integrates customer insights to drive and support omnichannel customer journeys.
Learn how AI and Machine Learning are changing loss prevention analytics. The latest enhancement to Oracle Retail XBRi Loss Prevention Cloud Service leverages the power of Oracle Retail Science by using machine learning to help retailers detect fraud by working in concert and enhancing rules-based techniques.
Oracle Retail Cross Talk is an exclusive conference that draws retail executives together in a collaborative format. It features informative sessions and interactive discussions led by industry visionaries.
The changing retail KPIs is a hot topic. Learn how by employing Retail Science, you can not only exploit the flexibility of a more advanced CLV calculus through the configurability afforded by Innovation Workbench, but also parlay CLV into more advanced customer segmentation, targeted offers, and better promotion halo and cannibalization prediction across more intelligent customer segmentations.
Learn more about the build-or-buy dilemma through the lens of data retail science with an emphasis on the importance of flexibility and control over analytical software. We will also examine the cost/benefit of buying packaged applications “off the shelf” versus a hybrid approach.