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Fully exploit the value of your big data and inform your decisions and innovations with modern retail analytics.
Connect users to the real-time information they need for detailed analysis of business critical KPIs via Oracle Retail Home.
Senior executive, merchants, marketers, store managers, data scientists, and everyone in between gain immediate customer insights with packaged dashboards.
Explore and visualize your data and gain analytical synergies with mashups between governed retail-insights data and external data such as flat files, etc.
Embedded machine learning continually improves customer segmentation, store clusters, item affinities, assortment optimization, and more.
Retailers can acquire, model, prepare, and serve structured, semi-structured and unstructured data for advanced use with the Oracle Retail Science Platform and Oracle Retail Insights Suite.
Your single access point to the Oracle Retail Insights Suite. Retail Home simplifies user interactions with the data and applications most relevant to their roles and empowers users to take informed actions with real-time insights.
A powerful, flexible, mobile-enabled solution that provides data-driven and science-powered insights into a retailer’s merchandising performance. Make more informed decisions, execute with confidence, and know that you are positively impacting the top and bottom lines.
Bring an unprecedented level of insight to retail marketing teams looking to better understand their existing customers and optimize new customer acquisition campaigns, and to other teams to support consumer-data-driven buying decisions, personalization and more.
Gain a better understanding of who your customers are, how they behave and why, so you can make intelligent product and promotion decisions. Leverage complete visibility into what motivates customers at each stage of their journey and how they are interacting with your brand across all touchpoints.
Retail business users can conduct advanced analyses to better understand and optimize affinity, store clustering, customer segmentation, consumer decision trees, demand transference, and item attributes. Business analysts and data science teams can leverage innovation workbench for additional ad hoc analysis.