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The Secret to Successful Customer Analytics
Organizations looking to implement forward-looking customer analytics should consider these issues:
Posted Jun 7, 2004
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As organizations resume investments in technology, business intelligence (BI) and analytic applications consistently rank at the top of the CIO's priority list. Where existing query-and-reporting tools have traditionally provided a backward-looking view at operations, today's analytics play a more integrated role in helping an organization direct its resources effectively by providing fact-based insights to every employee in the contexts of their jobs. Organizations looking to implement forward-looking customer analytics should consider the following issues. Insights for everyone to drive action Organizations can use customer analytic applications to guide long-term planning and help employees make better business decisions more quickly. Traditional query and reporting tools were designed for expert analysts who could understand the underlying data structure. Executive dashboards attempt to distribute information more broadly, but fail to guide insight and drive people to take action. To achieve the greatest value from customer information, analytic insights should be driven to the broadest set of employees and partners. The best analytic applications are those the user doesn't even recognize but rather introduce hints and guidance regarding job activities in the context of everyday tasks. For example, bank tellers don't have time to explore data> However, they can easily cross-sell new services or intervene to prevent churn when analytically based guidance appears on the screen embedded into their transactional application. Complete and timely information By their design data warehouses are robust sources of information. Data warehouses, however, often fall short: They rarely contain the complete view of the customer. To ensure that relevant information is incorporated, customer analytics applications must be able to augment historical information from the data warehouse from other sources, including CRM, order management, and financials. Consider a typical request to analyze an organization's year-to-date sales and how the sales team is performing on quota. The data warehouse might only have information through last week. By incorporating the historical data in the warehouse with supply quota and real-time sales information, the sales team can be armed with insight into the exact sales performance and be directed to take immediate actions.
Scale and performance To accommodate the high volume of users necessitated by a broad deployment strategy, a new level of scalability and performance is required. Traditional queries and reporting tools are notoriously sluggish on a large scale. The best of today's analytic applications rely on a server-based design that inherently delivers massive scalability and great performance. In fact, there have been analytic deployments of thousands of users supported by just a few modest Windows servers. Faster time-to-value + decreased risk = better results A key driver for adopting analytic applications is the additional value they generate from existing CRM solutions. Many customers are scared off by the labor-intensive process involved in assembling an in-house analytic platform and undertaking the cost and risk of building customer analytic applications. Packaged customer analytic applications are inherently designed to recognize source data elements, to adapt to whatever data architecture is already in place, and to incorporate best practices. Analytic applications that are further packaged according to the best practices of a specific industry can provide additional advantages. Packaged analytic applications built on a powerful enterprise BI platform can help organizations reduce the risk involved in deploying an analytic solution and speed up time-to-value, while still enabling flexibility. About the Author Paul Rodwick is vice president of Siebel Analytics at Siebel Systems, a provider of business applications software. With more than 18 years experience in marketing, product development, and business leadership, Rodwick is responsible for driving awareness of Siebel's analytics products, technology, and customer success in the enterprise business intelligence market. Contact him through Kortney Oliver at kortney.oliver@siebel.com
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