How to Use Database-Driven Analytics to Flourish Despite Economic Crisis - Page 3

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7. Improve profitability analytics

Create more accurate measurements of profitability by calculating a behavioral-based, enterprise-wide view of value-by customer, product, sales channel or organization. Now more than ever, retailers must see the whole profit picture! Learn which relationships to fight for, which to grow and which, if any, may be futile.

8. Use integrated analytical and operational CRM tools

Integrate your customer relationship management (CRM) programs so that analytical insight is actionable in near-real time for extremely relevant, customer-facing operational communications. Get the software integrated and connected to POS, Web, kiosk, e-mail, mobile and call center, so that you can not only respond to customer selling opportunities, but the information you get from the interaction can be captured and transformed for additional insight and leverage.

9. Improve forecasting and demand chain management

Use more detailed, integrated and timely data to more accurately forecast demand. Having a more accurate view of demand at the store level enables retailers to reduce out-of-stocks (preserving sales), while also minimizing inventory (reducing costs). The result is stronger, more collaborative relationships with suppliers while improving customer interactions and relationships.

10. Remember: analytics run on data!

We strongly encourage business evolution to an enterprise data warehouse, so that your analytical intelligence is based on a complete view of the business, not a partial view. An enterprise data warehouse improves accuracy and reduces the time to deliver knowledge across all organizations. However, even more to the point, the quality of your analytical intelligence depends on the quality and completeness of your data. The data is the heart of a company's knowledge assets and must be integrated for a holistic picture.

Data environments vary widely as to the quality, scope and freshness of data they hold. Data sources for analysis can range from a single data mart to a motley collection of data marts-and extend upward to include a centralized, cross-organization reservoir of detailed, dynamically-refreshed data: the enterprise data warehouse.

The environment chosen by the analytics power players of tomorrow is profoundly important to the quality, scope and freshness of intelligence that they can deliver and act upon. It matters immensely. That's why the analytics power player wants rapid access to enterprise-class intelligence, which is integrated from across the whole organization and centralized, for a complete and accurate view of the core business and its many constituencies. It is fed continuously from data portals, transactions and countless sources, and includes deep histories of data detail while also absorbing new data in real time.

/images/stories/heads/knowledge_center/franks_bill70x70.jpg Bill Franks is Managing Partner of the Retail Advanced Business Analytics Practice for the Americas region at Teradata Corporation. In this role, Bill helps Teradata's clients implement advanced analytics and data mining techniques to improve their business and gain value from their corporate data. Bill has extensive background helping clients derive value through the use of data analysis and modeling, with a focus on making results accessible to the business community. Bill's work has spanned clients in a variety of industries, ranging in size from Fortune 100 companies to small non-profit organizations. He can be reached at