By Sarah E Taylor-Oracle on Jul 16, 2012
In this blog post, Claudio Cavacini from Oracle Retail gives us an insight into Oracle Retail Customer Analytics, the latest data analytics tool from Oracle Retail to help retailers better understand their customers and what drives their buying decisions.
Oracle Retail Customer Analytics is a powerful business intelligence tool complementing Oracle Retail Merchandising Analytics, which was launched last year and created to enable retailers to better organise and understand merchandising data, providing visibility to item and store performance, inventory turn, sales and profit trends, and potential out-of-stocks.
Oracle Retail Customer Analytics uses the same intuitive approach to visualising data but draws on customer behaviour, adding a new dimension to Oracle Retail's industry-leading actionable insight solutions. For example, a merchandiser can see purchasing trends in different demographic groups or see what items are regularly bought together by customers, and use those insights to deliver more effective stock management, recommendations and store design both in store and online.
Today, retailers are notoriously “data-rich but information-poor.” Over the years they’ve accumulated millions of rows of data involving sales, inventory, suppliers, customers, promotions, employees and more, but fail to fully utilise this data to make more informed decisions.
Key functional BI opportunities exist both with the “buying” and the “selling” sides of retail, and involve managing both “top-line” and “bottom-line” concerns.
And especially today, knowing both customers and consumers and basing store selection, product assortments, pricing and promotional decisions on a deep understanding of those customers is something that EVERY retailer wants.
With Oracle Retail Customer Analytics, hundreds of different data sets can be combined to create unique dashboards specific to the user - whether these be category managers, merchandise managers, buyers or pricing analysts, and allowing them to quickly access the data relevant to them and act on the insight provided. Claudio's introduction to Oracle Retail Customer Analytics offers several examples of the metrics, with dashboards and reports being set up to answer specific questions. For example:
'How are my products selling across various customer demographics?' - A retailer can choose which demographic attributes are important to them and see sales broken down by those attributes, including income, household makeup, area of residence, etc.
'What are my top product affinities?' - That is, when the retailer promotes a certain category, is there another category that experiences a corresponding increase in sales? A retailer can then use this information to improve promotional activities.
With Oracle Customer Analytics, Oracle offers best-in-class business intelligence tools with retail-specific expertise that are optimised to run on Oracle Exadata Database Machine and Oracle Exalogic Elastic Cloud. This means these tools are designed to deliver the extreme performance and scalability required to accommodate high data volumes common to retail environments without sacrificing depth or speed of analysis.
With Oracle Retail Analytics, our intention is to bring this stack and our deep retail knowledge together in a cohesive solution that is built for retail, and offers actionable insights from storage to scorecard, covering enterprise-level BI needs, yet in a manner that is complete, open, integrated and dedicated to retail.
If you'd like to find out more about Oracle Retail Customer Analytics, visit the Oracle Retail site.