Oracle Retail has combined three of its services into a new Oracle Retail Insights Cloud Service Suite.
By combining these science and insight cloud services, the company can provide a range of analytics that align with KPIs for the retail community. The metrics offered create a user-friendly experience with dashboards organized by persona and organizational responsibilities in Oracle Retail Home to encourage strategic decisions that help drive growth and operational efficiency.
“We are working with several retailers who are anxious to adopt cloud to bridge the gap between operations and innovations,” said Jeff Warren, vice president of Oracle Retail. “To capitalize on the surge of unstructured and structured data in retail, we have applied advanced techniques for analyzing retail data from multiple perspectives into a single cloud services suite that integrates with retail-rich applications and cloud services. With these tools we can deliver analysis on what happened (descriptive), what is going to happen (predictive) and what a retailer should do about it going forward (prescriptive).”
With the Oracle Retail Insights Cloud Service Suite, retail organizations can experience benefits such as:
Enhanced user experience and relevance: The cloud suite leverages Oracle Retail Home to provide a single, modern access point to the data. The user experience streamlines and simplifies access to data and applications to provide relevant and actionable information based on roles and responsibilities. The federated user interfaces support integrated insights-to-action loops.
Speed to value: With one rapidly deployed cloud service, the solution represents the application of Oracle's analytical core to modern retailing: a comprehensive big data warehouse founded on industry best practices and the scalability, reliability, and economy of a complete Oracle analytic tech stack.
Understanding of customer context: Users gain a better understanding of who customers are, how they behave and why so they can make more intelligent product and promotion decisions. They also can leverage complete visibility into what motivates customers and how they are interacting with the brand across all touchpoints.
Merchandising intelligence: Users can identify actionable merchandising opportunities across touch points, including back order and returns, top/bottom sellers, demand/fulfillment and price and promotion analysis.
Customer loyalty: Users leverage a visual, end-to-end workflow to define and execute local market assortments, improve conversion of traffic into sales, and increase customer satisfaction.
Artificial intelligence and machine learning: Retail business users can conduct advanced analyses to understand and optimize affinity, store clustering, customer segmentation, consumer decision trees, demand transference, and attribute extraction.
Flexibility and ad hoc reporting: Business analysts and data science teams can leverage an innovation workbench for additional ad hoc analysis.
Common foundational data architecture: The suite can leverage the data generated by Oracle Retail's comprehensive application footprint to provide properly filtered and secured descriptive, predictive and prescriptive analytics.
Retail investment drivers: Users optimize assortments to available space to maximize planogram performance, return-on-space, sales, revenue, and profits while improving customer satisfaction with an optimal variety for each store.
Gross margin improvement: Users drive recommendations for promotions, markdowns, and targeted offers that help maximize profits and sell through leveraging prescriptive analytics.