This article introduces the role of business intelligence and data warehousing in a Oracle Retail Analytics environment. The article briefly describes the implementation of Oracle Retail Analytics and its data sources, and the Retail Analytics user interface through Oracle Business Intelligence Enterprise Edition.
Oracle BI is built using several processes, and applications that maintain these processes, using the latest tools and technologies. One of the main components of BI is a data warehouse.
A data warehouse is the repository that stores the data extracted from multiple source systems, modeled to perform for both data loading, reporting, and ad hoc analysis needs.
The Oracle Retail Analytics is integrated with the following Oracle Retail applications:
- Retail Merchandising System (RMS)
- Oracle Retail Sales Audit (ReSA)
- Retail Invoice Matching (ReIM)
- Oracle Retail Price Management (RPM)
- Retail Merchandise Financial Planning (MFP)
Oracle Retail Analytics offers a rich BI solution to retail industry users. Retail Analytics is built using the latest Oracle technologies and uses Oracle Data Integrator (ODI) for extracting, transforming, and loading (ETL) the data to Oracle Business Intelligence Enterprise Edition for end user reporting and analysis.
This solution provides complete, enterprise-wide insight for the retail users, enabling fact-based actions and intelligent interactions.
Oracle Retail Analytics Modules
- Merchandising Analytics
- Customer Analytics
Retail Analytics starts with customer and merchandising data. It embraces the existing corporate data sources, and it integrates with Oracle Retail solutions to increase effectiveness across the entire merchandising life cycle.
Retail Analytics can integrate with other Oracle applications, as well as applications from other vendors. Retail Analytics can be implemented alone, or integrated with other applications, to accommodate each retailer’s unique information needs and applications environment.
The prebuilt nature of the solution allows you to achieve the fastest time to value, by reducing deployment time and helping to lower total cost of ownership.
1. Merchandising Analytics Module
The Merchandising Analytics module is a merchandising-specific BI module of the Retail Analytics application. It provides insight to the critical performance indicators such as item sales, store performance, markdowns, inventory turns, sales and profit trends, and current and potential out-of-stocks.
The Merchandising Analytics dashboards provide the ability to act on those insights. They allow you to order more stock, reallocate merchandise, or begin a promotion, triggered by metric thresholds.
The Customer Order subject area of the Merchandising Analytics module facilitates analysis of the Oracle’s Commerce Anywhere solution.
Commerce Anywhere integrates the Oracle Retail applications with on-line order capture (OOC) and order management (OMS) applications to support the ability to do real-time available inventory lookups into Oracle Retail applications, creation of the customer orders, fulfilled from suppliers or retailer locations, and fulfillment of these customer orders.
2. Customer Analytics Module
The Customer Analytics module allows you to perform retail analysis of customers and customer segments. It features three new subject areas:
- Customer Analysis
- Market Basket Analysis
- Promotion Analysis
The Customer Analytics module gives fact-based insight into the following:
- Customer price sensitivity
- Customer loyalty to merchandise
- RFM scores
- Overall promotion effectiveness
Customer segment analysis in the Customer Analytics is available based on the following:
- Demographics – ability to analyze segments by income, ethnicity, geography, and other factors.
- RFM scoring – used for analyzing the customer behavior and defining market segments.
- Customer loyalty analysis and scoring
Market basket analysis offered by Customer Analytics module provides insight into which products might make effective bundles. The Customer behavior data is obtained from mining the transaction history, and it is correlated with customer segment attributes to inform promotion strategies.
The ability to understand the market basket affinities allows the marketers to calculate, monitor, and build promotion strategies based on critical metrics such as customer profitability.
The Promotion analysis can be done based on the following:
- Promotional halo and cannibalization, which highlights the promotions effect on other items in the category.
- The Promotional try and repeat, which shows the promotion’s effect on initial and repeat purchases.
- Promotional response rate and offer conversion, which speaks about the effectiveness of the promotion.
These are some characteristics of Oracle Retail Analytics:
- Rich reporting capabilities
- Comprehensive Solution
- High-performance extract, transform, and load (ETL) code
- High-performance reporting
- Robust data model
Locus IT provides Retail Analytics services like Oracle Retail training, Oracle Retail support, Oracle Retail implementation, Oracle Retail migration. For more information on how Oracle Retail Analytics can help your business please contact us.